Overview

In my opinion, there is an interesting paradox with geospatial analysis and crisis management - we continually develop new and improved methods for handling disaster situations, but our increasingly complicated societies, economies, and infrastructures increase the challenges associated with disasters. People and their environments are more interconnected than ever, and spatial data science and related technologies are in many cases the most appropriate mechanism for analyzing and rectifying emergency situations.

There are four key phases of emergency management: vulnerability assessment, preparedness, response, and recovery. In subsequent lessons, we will explore each of those topics in detail. Later, we will work together to research and apply methods from spatial data science to emergency management contexts, and we will explore how geospatial perspectives and technologies have been used in a variety of ways in recent disasters.

Each week, you will learn about an emerging technology trend and how it relates to geospatial analysis and crisis management. One of my goals is to make sure you learn about and consider new trends and themes in technology, and imagine how those advances can and will impact Spatial Data Science for Emergency Management in the future. The geospatial planning activities you participate in now should take into account new types of technologies that will be commonplace in the next 5-10 years.

Example - Changing approaches to rapid damage assessment after a disaster

Crowdsourcing approaches for damage assessment have been popular, with micro-tasking platforms like Tomnod used to leverage digital volunteers, as shown here for the 2015 Nepal Earthquake. Volunteers look at images of structures and rate the level of damage.

What You Will Learn

By the successful completion of this lesson, you should be able to:

• articulate the role of spatial data science, including geospatial perspectives and technologies, in emergency management;
• evaluate and discuss how recent technology trends in geospatial interaction relate to emergency management;
• understand the final project assignment for this class and brainstorm some ideas;
• discuss the role of spatial data science in emergency management with your classmates.

What You Will Do

Lesson 1 is one week in length. To finish this lesson, you must complete the activities listed below.

Please refer to the Course Calendar for specific due dates.

Questions?

If you have questions about the content or lesson activities, please post them to the General Questions and Discussion forum in Canvas. While you are there, feel free to post your own responses if you, too, are able to help a classmate. If your question is of a personal nature, please email me directly through Canvas.

I’d like oj, bread (sliced or not, wheat or whole grain), 2 bagels (wheat or plain), we’re out of rosemary if you can get a small and a big or a few small, my fake dairy popsicles. We don’t seem to have any spray dish soap for the sink that I can find.

Image of the Royal Commission Annual Report from October 2020

Source: Royal Commission into Natural Disaster Arrangements

Before going any further, I'd like you to consider the devastating 2019-20 Black Summer Bushfires in Australia. I focus on event because it has prompted a major National Review of disaster and emergency management arrangements. The Royal Commission into Natural Disaster Arrangements released their final report at the end of last year. Royal Commissions are basically a big investigation that relies on submissions from all kinds of stakeholders, from academics, to frontline workers, to citizens. This process results in a series of recommendations that the government considers. While the bushfires prompted this review, the recommendations take a multi-hazard approach. So, how can you manage fires, smoke, heatwaves, floods, cyclones in a more coordinated way.

I'd like you to look at a few sections of this report and also keep it on hand as we go through the course. It has a lot of information relevant to the topics we cover, albeit we are exploring geospatial dimensions in greater depth. First, have a look at some photos and videos from the Bushfire History Project (below) to get a feel for what happened last year.

Source: Royal Commission into Natural Disaster Arrangements

2019-20 Bushfire History Project - Fires (3:51 minutes)

2019-20 Bushfire History Project - Damage (2:54 minutes)

2019-20 Bushfire History Project - Recovery (2:06 minutes)

Now, look at the download the report from this direct link or go to the Commission's website.

Royal Commission into National Natural Disaster Arrangements Report

Royal Commission into National Natural Disaster Arrangements Appendices

Please read the following sections (don't worry if these seem a bit technical given you just started the course):

• Forward - page 5-7
• The 2019-20 disaster season - page 19
• Disasters have changed & We need to act on multiple fronts - page 22
• A national picture needs national data - page 28-29
• The impact of natural disasters on essential services (Figure 35) - page 227-229
• Mental health and natural disasters - page 345-348
• Earth observation systems - page 498

I'd like you to consider a few questions (nothing to submit now!):

• From these sections of the report, does anything jump out at you with regard to data needs in emergency management?
• Do you think the Australia situation is similar to your home country?
• From what you know so far (and it is early in the course!) do you think geospatial data is most useful for:
  • Preparing for a disaster?
  • Responding when it is in progress?
  • Recovering and rebuilding?

I hope this has provided a concrete and current picture of the complexity of emergency management. I'll refer you back to the Royal Commission report later in the class.

It is generally agreed upon that there are four key stages of emergency management problems.

• Planning & Mitigation
• Preparedness
• Response
• Recovery

You can probably imagine a wide array of possible geospatial applications that would make sense for each of these stages of emergency management. Lesson 2 in this class will talk about hazards more generally, and then, in Lessons 3-6, we'll start a deep dive into how geospatial perspectives and technologies can be used in these four stages. In Lessons 7-9, we'll explore scenarios and cover a few case studies to see how geospatial analysis has been used in real-world emergency situations.

Here are brief definitions for each stage of emergency management:

Planning & Mitigation: Evaluation of the potential types of disasters and the development of plans for reducing their probability or their impact on life & resources.

Preparedness: Actions undertaken when mitigation efforts have not prevented or are unable to prevent a disaster from taking place. 

Response: Activities that occur in the wake of a disaster that are intended to identify and assist victims and stabilize the overall disaster situation.

Recovery: Actions following a disaster that aim to restore human and environmental systems back to normal.

We will begin our consideration of geospatial approaches and technologies related to emergency management by contrasting four perspectives. On this page, the role of geospatial analysis in the work of the Federal Emergency Management Agency (FEMA) is described. This includes some historical perspective on how FEMA's mission has evolved over the last 10 years or so. Next, we will focus on emergency management related applications developed by Esri, the peak GIS software company globally. Then, for a very different perspective, you will consider what the 'digital humanitarian' community is doing in response to factors like big data, volunteered geographic information (VGI) and social media. Finally, we will consider emergency management in light of cutting-edge technologies. Of course, all of these areas are interrelated, and we will cover much more as the course proceeds! The idea is to start building a context and framework for developing a deep understanding of the topics to come.

First, we will take a look at the Federal Emergency Management Administration (FEMA). If you're not familiar, FEMA is part of the US Department of Homeland Security and is the lead agency for preparing for, responding to and assisting with recovery from major disasters. Have a look at their website if you want to learn more. (As we move through the course, pay attention to the different roles that emergency management organizations play, particularly at local, state and federal levels, and the types of incidents they are responsible for).

For a little context, here's what FEMA Enterprise GIS Services considers its mission with respect to GIS and Emergency Management.

FEMA Enterprise GIS Services
Our primary mission is administration, coordination, collection, and dissemination of geographic information for FEMA and the Emergency Management Community under Emergency Support Function #5 (Information and Planning) of the National Response Framework and in support of the Robert T. Stafford Disaster Relief and Emergency Assistance Act (PL 93-288) as amended. Our current concept of operations includes a full range of GIS services to all FEMA program offices that encompasses sophisticated geospatial analytics through the Mapping and Analysis Center (MAC) and deployable GIS technology through the Deployable Emergency GIS program (DEGS).

Let's dig deeper into this. First, consider this excerpt from FEMA's Mapping and Analysis Center in 2008 (note it is no longer maintained by FEMA and the MAC has evolved into other departments). Make a mental note of the range of functions that they focused on and some of the ways they went about their work. I wanted you to look at this old description, so you can contrast it with what FEMA does now, and more importantly to highlight how much has changed in a short period of time with regard to the ways geospatial products are generated and distributed.

Now, let's jump ahead 10 years! Start with the interesting 2018 presentation slides from Chris Vaughan on GIS @ FEMA Working Smarter Through Data Analytics. Finally, have a look at the 20 September 2017 FEMA Geospatial Coordination Call briefing. This is a summary of 'situation awareness' for the day Hurricane Maria hit landfall in Puerto Rico and is quite comprehensive.

With this historical context, have a look at some of FEMA's current offerings at the FEMA Geospatial Resource Center "Hub". Notice the dashboard with a summary of current hazard events. Click on a few of the hazards and look at what's available.

Consider these artifacts and reflect on what you see that may have changed in recent years, e.g., increasing focus on analytics and real-time.

How Reading Assignments Work

For each lesson, I will ask you to read parts of your textbooks and/or selected online materials and articles. As you can see below, I'll try to make it as clear as possible what you're expected to do by always identifying specific reading assignments in a separate box.

You can access the readings right in the course website, and they are also available in Canvas.

Lesson 1 Reading and Writing Assignment

For our first set of readings, we will focus on setting the stage for the rest of the lessons this term. First, I'd like you to read the white papers developed by folks at Esri and contrast it with the company’s current software and service offerings. These provide a simple overview of the common terms and topics associated with GIS for Emergency Management, and they show you how the GIS Goliath perceives the role of geospatial tools and methods in the context of Emergency Management. You just read a bit about how FEMA sees the state of affairs, and I think you'll notice some key similarities (and differences) in how the world is viewed from these two perspectives.

Second, I've selected a chapter from a National Academies of Science report written in 2007 that sets a research agenda for GIS in Emergency Management. The specific chapter I've picked for this week focuses on how GIS was or could have been used in a few different disaster scenarios. Unfortunately, these are examples that are still relevant today, over 10 years on.

Finally, you’ll contrast these perspectives with the emerging field of Spatial Data Science. First, you will look at a journal article focused on spatial data science and how it is shaping cartography/visualization. You'll see throughout this course that visualization is an essential part of understanding and addressing problems in emergency management. So, it is useful to explore spatial data science through this lens. The book chapter from Digital Humanitarians introduces how the disaster and humanitarian community is opening up and engaging with big data and volunteered geographic information (VGI) at a remarkable pace.

1. READ

ESRI White Paper on GIS for Emergency Management, which outlines how Esri sees a role for ArcGIS in Emergency Management (in 2012!). Contrast this with Esri’s current ArcGIS for Disaster Management tools on their website.

2. READ

Chapter 2: Thinking About Worst Cases from Successful Response Starts With a Map: Improving Geospatial Support for Disaster Management. Please visit The National Academies Press and read the chapter online or, you can create an account and download the chapter for free. This chapter is VERY OLD now (2007), but I think it will provide a good background for thinking about different disasters and how geospatial approaches can help us understand what might happen. Reflect on how things may be in 2023. For example, scenario two talks about a hurricane hitting the New York region, and this actually happened with Hurricane Sandy. We will talk about Sandy later in the course.

3. READ

Robinson, A.C. et al. 2017. Geospatial big data and cartography: research challenges and opportunities for making maps that matter. International Journal of Cartography 3: 32-60.

If you are having trouble accessing the paper through the link above, you can download the PDF directly here.

4. READ

This short web article - Becoming a digital humanitarian, one deployment at a time and Chapter 1: The Rise of Digital Humanitarians from Digital Humanitarians. See the Library Resources menu to read the chapter.

Deliverable

Complete the writing assignment - Details on the next page! 
​​​​​

Based on this week's lesson, address the following:

1. As you read the three different worst-case scenarios, it should be apparent that a key challenge is simply developing a rapid picture of the spatial extent of a disaster. If you assume that a given disaster will disable local EOCs and their accompanying geospatial tools and data, describe at least two ways that emergency managers brought in from afield could quickly assemble data that describes the extent of the disaster. How would folks from the digital humanitarian community approach this problem?

2. What do you consider to be the one or two key challenges facing the application of Spatial Data Science to Emergency Management in (a) temporally short, geographically local event(s) versus (b) temporally extended, geographically regional events? Assume your audience is a group of emergency management planners considering incorporating geospatial data and analysis into their operations. They don't have a lot of time, so be direct and succinct in your analysis.   

Make clear how your response relates to the readings.

This response should be between 500 - 600 words in length.

This class is writing intensive. I'll be editing and commenting on your written work throughout the term. The Effective Technical Writing in the Information Age resource can be a huge help if it's been a while since you've written for a course like this.

Submission Instructions

It is important for you to save your files in the following format so that I can match each submission up with the correct student. 

L1_assign_firstinitialLastName.doc  For example, my file would be named "L1_assign_mBeaty.doc" 

Upload your assignment to the Writing Assignment (L1) dropbox. See the Course Calendar for specific due dates.

Grading Criteria

This assignment is worth 4% of your total course grade and will be graded out of 20 points using the following rubric.

OK, you might think, "Well - isn't GIS already something most people consider high tech?" The answer to that question is a little complicated. In comparison to where we were about 20 years ago, yes, current GIS systems are pretty high tech. In comparison to recent advances in software, interfaces, and the ways in which regular people can participate in the development of data and tools - no, off-the-shelf desktop GIS software isn't so radical anymore.

What I hope to do in this course is to bring in new trends and themes in technology and imagine how those advances can and will impact spatial data science in the future, with particular emphasis on how those technologies fit or could be adapted to support geospatial analysis for emergency management.

Emerging Themes

Each lesson features an Emerging Theme page that presents a technology and encourages you to envision its potential impact on GIS systems for Emergency Management. I draw upon video lectures, links to live demonstrations, and other multimedia as much as possible to make these modules as engaging as possible.

The themes we will cover this term are:

1. New Methods of Geospatial Interaction
2. GIS and Unmanned Aerial Systems (UAS) - includes an exercise working with UAS data
3. Volunteered Geographic Information (VGI) - includes an exercise
4. Spatial Data Science - Data and analytics
5. Real-time GIS and Analytics - includes an exercise working with operations dashboards
6. Humanitarian Logistics and Supply Chains
7. Social Media and Crisis Mapping
8. Geospatial Artificial Intelligence (geoAI)
9. Digital Twin
10. Work on Term Project

The following 4:30 minute video, Geospatial - A Golden Thread in the Fourth Industrial Revolution is from the geospatial industry website, Geospatial World. It is a bit sensationalized but does cram in a lot of interesting content about technology and geospatial and provides some viewpoints from industry leaders. I hope it makes you want to learn more about these emerging themes!

On the next page, you'll find your first Emerging Theme assignment. In this assignment, we will examine new types of mobile interfaces and discuss how they could be integrated into future GIS systems for emergency management.

This week, I’d like you to take a look at a few very exciting technology demonstrations that I think are relevant to spatial data science applications for emergency management. These videos show the cutting edge of what is possible with computers, and I think it’s quite reasonable to expect that in the next 5 years or so these things will become quite common in consumer and professional systems.

Throughout this course, we will be considering information from different viewpoints, including industry, government, NGO, and academia.

Let's start with this video about the ways spatial data and technology are being used (to varying effect) to address different aspects of the COVID-19 response.

How geospatial technologies can help combat COVID-19 (3:15 minutes)

The next video is from the DHS Science and Technology Directorate’s Next Generation First Responder Program and describe how emerging technology, including geospatial, are being incorporated in first response situations. They both describe a high level of integration amongst technology. Think about how this might fall down in a real emergency situation.

Next Generation First Responder (5:22 minutes)

Finally, take a look at the I-React project funded by the European Commission that use augmented reality in an disaster response situation. Visit this website and watch the video below.

Emergency Management with Augmented Reality (4:00 minutes)

Digital Twins (4:24 minutes)

Deliverable

1. Post a comment in the Emerging Theme Discussion (L1) forum that describes how you envision one or more of these technologies integrating into a spatial data science for emergency management. Do you see any problems with integration, or, perhaps, you don't think we should consider them for emergency situations. That could be a valid position to take as well.
2. The initial post should be completed during the first 5 days of the lesson.
3. Then, I'd like you to offer additional insights, critiques, a counter-example, or something else constructive in response to your colleagues on two of the following 5 days.
4. Brownie points for linking to other technology demos, pictures, blog posts, etc., that you've found to enrich your posts.

NOTE: Respond to this assignment in the Emerging Theme Discussion (L1) forum by the date indicated on the course calendar.

Grading Criteria

This discussion will be graded out of 15 points.

Please see the Discussion Expectations and Grading page under the Orientation and Course Resources module for details.

Term Project Overview

This course is built around a term project that will integrate your understanding of geospatial perspectives and technologies with what you have learned about how they can be applied to emergency management. You will select a project topic from one of the options described below and write a report that includes spatial data analysis and visualization approaches. In some cases, this might take the form of a case study, in others, a proposed geospatial system design or a demonstration (e.g., dashboard or app) that illustrates either current trends in applying geospatial thinking to emergency management or what might be possible in the near future.

To a large degree, you will have the freedom to shape the specifics of your term project around the geospatial and/or emergency management contexts in which you are most interested. I hope that this allows you to either focus on a topic related to your day-to-day work or to choose an area that sparks your curiosity. That said, it should be clear who you are writing for and the role you are playing in preparing this report.

Your analysis will be informed by relevant datasets that you find, analyse, and visualize. A key task early on is identifying a suitable dataset and developing some ideas about what you’d like to do with it. I can help with this process and when you develop the abstract for the project, we will meet to discuss your ideas and make sure they are achievable in the time you have. I will also circulate a list of websites where you can search for suitable data. There are many options, so don’t be too concerned about being able to find suitable data.

You can choose from a wide range of tools to conduct your analysis and visualize the results, including Esri products like ArcGIS Pro or ArcGIS Online/Portal. You have access to a wide range of Esri tools through your Penn State Accounts. But don’t forget about other possibilities such as web mapping tools like MapBox or open-source tools like QGIS and R. In this course, we use a range of data and technologies and you can do the same with your projects. Just keep in mind you’ll need to balance the time you have to do the analysis and write your report with the time you have to learn new software.

Each week, you will notice that at least one page of the lesson is dedicated to a goal or assignment associated with your term project. In about half of those Lessons, you need to complete a graded deliverable related to your final project. I've developed a project schedule that is designed to make sure you make steady progress on the term project and that also ensures that we have one full round of draft editing to refine your work. I don't like classes that end with submitting a final project with no chance to do any revisions. That seems silly to me.

My hope is that you end the semester with a product that has utility beyond just meeting the course requirements. It could end up being a use case or a proposal that you share with others in your organization. This has been the case for some students in past offerings of GEOG 858.

Term Project Options

Here are some options for your term project. You can choose one of these options, or if you'd like to riff on one of these and take it in a different direction, by all means, do so! These are really just suggestions: I want you to be innovative and surprise me with your good ideas for projects. But I also know that many of you want to know what a good example project might look like, which is why I've listed these options here.

• OPTION 1: Develop a case study on the use of specific geospatial data and technologies from a recent crisis or disaster. Using geospatial data and analyses, demonstrate at least one way that geospatial approaches were used effectively and at least one way their use could have been improved. This option should be built on your original analysis and not just a review of what others have done.
• OPTION 2: Develop a vulnerability, hazard assessment, and mitigation case study for a place that has not recently been impacted by a disaster. Develop a concept for a geospatial system to support these activities and build a prototype to illustrate your main points.
• OPTION 3: Address the question, Why is recovery so difficult? For this project, conduct a comparative analysis of recovery after recent disasters (ones that occurred within the last ten years) in two to three case study areas. Use geospatial data and analysis to help illustrate and communicate the comparisons and main points you make.
• OPTION 4: Focus on an emerging technology that is changing how geospatial analysis is applied in emergency management. You may consider a technology we cover in this course, or focus on a different technology (but provide an argument for your choice). Provide context for the technology, but focus on some specific aspects of its use that you can demonstrate using spatial data and analyses.

Deliverables (for Future Lessons)

The term project includes the following deliverables that will be assigned to you in future lessons:

• Project Abstract indicating which project option you have chosen and describing in general terms what you will cover - assigned in Lesson 2 (Worth 5% of total grade)
• Project Outline and Short Video Presentations (headings and several bullets under each heading for the main topics you'll cover). Produce a short 3-5 minute video introducing your topic to the class - assigned in Lesson 4 (worth 8% of total grade)
• Full Draft of your Term Project Report, no longer than 5000 words, not including an appendix where you can outline your methodology in greater detail - assigned in Lesson 6 (worth 12% of total grade)
• Revised Term Project Report, no longer than 5000 words, not including an appendix where you can outline your methodology in greater detail - assigned in Lesson 10 (worth 16% of total grade)
• 5-7 Minute Video Presentation of your Term Project - assigned in Lesson 10 (worth 4% of total grade)

Look for details on each deliverable (including specific due dates and grading criteria) in future lessons.

NOTE: I have provided examples of each term project deliverable in CANVAS. 

Summary

In this lesson, you have received an introduction to some of the major concepts associated with spatial data science for emergency management. You reviewed the four basic stages of emergency management and read some background material that defines common terms to geospatial science and emergency management.

Disasters and emergencies provide a wide range of opportunities for geospatial systems to play an important role, and in future lessons, we will delve into these possibilities in detail.

This week, we covered our first emerging technology theme. I've created a page for every lesson that focuses on a different technology theme that I think is relevant in some way to future geospatial applications for emergency management. When we are concerned about planning future geospatial systems, it is essential to become aware of new technology trends that could significantly impact how systems work in the not-too-distant future.

In the next lesson, we will review the range of hazards and emergencies that may require the use of spatial data science to aid mitigation, preparation, response, and recovery efforts.

Reminder - Complete all of the Lesson 1 tasks!

You have reached the end of Lesson 1! Double-check the to-do list on the Lesson 1 Checklist page to make sure you have completed all of the activities listed there before you begin Lesson 2.

Questions?

If you have any questions, please post to the Canvas Discussion Forum called "General Questions" or email the instructor via Canvas conversations (if the question is personal in nature).

Overview

Threats to people and their property can take many forms. Many of the situations we concern ourselves with in this course are linked to natural events. But it is also important to consider a wide range of social and economic triggers that could cause emergency management situations. In this lesson, we'll take a look at a variety of disaster types and their associated geographic attributes.

What You Will Learn

By the end of this lesson, you should be able to:

• identify the wide array of emergency situations in which geospatial tools could be used;
• evaluate possible term project topics and related datasets, choose a topic, write an abstract and present to the instructor;
• learn more about the growing technological trend of UAV systems and how they relate to geospatial analysis and crises;
• complete a hazard/risk assessment using GIS and UAV date and evaluate the results.

What You Will Do

Lesson 2 is one week in length. To finish this lesson, you must complete the activities listed below.

Please refer to the Course Calendar for specific due dates. 

Questions?

If you have questions about the content or lesson activities, please post them to the General Questions and Discussion forum in Canvas. While you are there, feel free to post your own responses if you, too, are able to help a classmate. If your question is of a personal nature, please email me directly through Canvas.

There is a very wide range of hazards and disasters we must consider when planning and implementing geospatial solutions for emergency management. It is easy to focus on the very large and obvious events - things like hurricanes, earthquakes, and disease epidemics. For many geospatial managers, however, there are day-to-day emergency situations on a local level that deserve plenty of attention: house fires, auto accidents, and violent crimes - just to name a few.

In this lesson, you will consider some of the characteristics of disaster and emergency events in three main ways. On this page, you will explore how different organizations track and provide up to date information on emergencies around the world - A key message that will become evident is that there are many diverse disasters and emergencies occurring at any given time. On the following pages, you will read about some specific hazards and disasters and how they are understood from a geospatial perspective, and you will do a hands-on hazard and damage assessment.

Let's jump in! The Federal Emergency Management Agency (FEMA) keeps a running tab of declared disaster events in the US. You've probably heard of these on the news when the President declares a location a "Federal Disaster Area". In addition to these alerts, FEMA now publishes quite a few interesting summary maps of recent disasters at their GeoPlatform. Please spend some time looking at the various components of the FEMA GeoPlatform. While there, think about what information is provided - DataHubs like this are becoming popular and useful tools for providing external facing data and mapping services. Who is the target audience for this? Is this a potential data source or is it locked down? Some of these pages rely on Esri Story Maps, a tool you will use later in the course. You might want to bookmark this to come back to as we talk about different types of Hazards and Disasters and when new events happen in the United States as we work through this course.

One of the approaches FEMA is taking with GeoPortal is providing Story Maps such as their Hurricane Incident Journal. Take a look at this example for 2018 Hurricane Florence by clicking on this image.

Credit: FEMA

Next, have a quick look at the following presentation prepared for a daily FEMA Geospatial Coordination Conference Call for Hurricane Lane as it passed near Hawaii in the summer of 2018 (You looked at a similar one of these in Lesson 1 focused on Hurricane Maria). These briefings describe the state of Situation Awareness, particularly from a geospatial readiness perspective. We’ll revisit this concept in coming lessons but for now, note the range of actors and their different roles/viewpoints on this event. This is also a much more technical view than what is provided in the GeoPlatform, and you can find some of the data behind this on their GIS portal.

Finally, a complementary example identifying and tracking emergencies and disasters can be found on a map developed by the Emergency and Disaster Information Service (EDIS) to provide information on a wide range of hazards and disasters around the world. Take a look at this application called EventMap.

Hazards and disasters around the world. Click on the image to see an updated map. It is updated every 5 minutes

Credit: Emergency and Disaster Information Service (EDIS)

There are other examples like this that we will come across during this course and as part of future lessons, and we will also look at geospatial tools for understanding particular events on a much more detailed level. Next, you will consider some hazards and disasters in greater detail through this week's readings.

How Reading Assignments Work

Here is a quick recap of how the reading assignments work. For each lesson, I will ask you to read parts of your textbooks, online materials I select, or articles I've found. As you can see below, I'll try to make it as clear as possible what you're expected to do by always identifying specific reading assignments in a separate box.

Part of your class participation grade will be making responses on our discussion board to questions I pose about the readings. Whenever you see a RESPOND prompt, you need to respond to that question as directed. Occasionally, I'll mark items THINK ABOUT when I simply want to direct your thoughts as you read.

You can access most of the readings via the links on this page. Some are also available as files in the Lesson 2 Module of Canvas.

Lesson 2 Reading Assignment

The readings for this week are selected to continue the introduction to spatial data science for emergency management and to hazards and disasters in particular. These are some fundamental concepts you will very likely refer back to as you engage with the course material and develop your own term project. The first reading is from your GIS for Disaster Management textbook and provides a broad background on disaster management and GIS. It also introduces the important point that there are different levels of responsibility for responding to events, some overlapping some distinct. You should think about the role of government (local, state, and federal), non-government organizations, industry and private sector, and the research and education organizations in each phase of emergency management. It is a complex landscape, and this course often considers the ways these actors intersect.

The second reading is a report/handbook developed by the Association of Southeast Asian Nations (ASEAN) on different hazard and disasters, their complex characteristics and how to address them. You will read just a part of the handbook, but it is likely to be of use as you move through the course and encounter different topics you want to learn more about (It could also provide inspiration for your choice of term project topic!).

1. READ

"GIS for Disaster Management" - Chapter 5, "Disaster Management and Geographic Information Systems" (see Library Resources link in Canvas).

2. READ

From the 2017 ASEAN report “Specific Hazards: Handbook on Geospatial Decision Support in ASEAN Countries” read the Preface, pages 1 – 13 and then pick one of the chapters on specific hazards (e.g., “Landslide”). The other chapters will be a good reference as you consider other hazards in this class.

Unmanned Aerial Vehicles (UAVs)

We are probably all familiar with drones, or UAVs, as they are virtually everywhere these days. UAVs are remote controlled airplanes and helicopters that are capable of providing surveillance and attack capabilities for military and civilian uses (no attack capabilities in the civilian case, unless you mount a potato gun). Their development grew out of the need for airborne reconnaissance on missions that are either too dangerous or too tedious for piloted aircraft. Today, UAVs have evolved to the point that some platforms are small enough to be easily deployed by a small support team and require only a hand launch or a very short runway. They are often referred to more generically as Unmanned Aerial Systems (UAS), as the vehicles themselves are just one piece of the overall puzzle in most geospatial workflows You may also be interested to look at another one of the GIS courses we offer, GEOG 892: Geospatial Applications of Unmanned Aerial Systems (UAS). It is focused explicitly on how UAVs and GIS working together.

UAVs for Emergency Management

In the emergency management context, UAVs are already used in a variety of ways and new applications continue to emerge.

UAVs are capable of surveying areas very quickly to provide imagery to - or other types of - remotely-sensed data. Satellite data is always valuable and desirable, but satellites cannot always be overhead at the right times on demand. UAVs can be deployed very quickly and can be easily directed toward different areas as the situational picture develops. It is worth noting that UAV footage combined with new approaches to image processing means emergency responders can have high-quality imagery and maps in a matter of hours rather than days.

Click on the image below to see a great example of how UAV footage was used to create a compelling story and reference document about the 2018 Camp Fire in California.

Drone Mapping of the California Camp Fire

The following 2:28 minute video provides a good illustration of the links between drone mission planning/field operations, image processing, and delivery of products for use in response and recovery activities. Note the time frames involved in this, and how much shorter they are than other traditional aerial or remote sensing efforts. However, the time required to process imagery from those platforms is rapidly shortening as well.

We are all pretty familiar with the use of drones for imagery, but here are a few additional emerging uses for drones in emergency stations. The next video is a bit of a ‘vision’ for drone use and this is followed by a few specific examples of how drones are being used in emergency response.

The following 3:30 minute video: Disaster Response Support with Drones, provides a nice overview.

Payload Drones

It’s not just about Amazon delivering goods to your door… Payload drones are increasingly being used in crises as illustrated in the following videos from WeRobotics and Zipline.

Watch WeRobotics Amazon Rainforest Cargo Drones (2:35 minutes)

If you have some time it is worth checking out WeRobotics on their website or YouTube. Patrick Meier, the author of Digital Humanitarians, is also a co-founder of WeRobotics.

Now watch the 4:05 minute video about airdrops of medical supplies to African Villages.

Cooperating Drones

Drones are also able to work together to complete tasks. You may have seen the insane “swarm” drone light display at the opening ceremony of the Winter Olympics in Pyeong Chang in 2018. Other applications are being developed such as the three drones working together to build a rope bridge that can support humans in the following (3:26 minute video).

Building a rope bridge with flying machines (3:26)

AI and Drones

Finally, I’d like you to consider how drones are being incorporated with other emerging technology such as artificial intelligence. In the video example below (from Australia!) drones are able to identify swimmers, swimmers in need, sharks, stingrays, and many other things. (2:05 minutes)

We've covered a lot so far in this lesson, and now you will start putting things together through an applied exercise. You will be working with GIS and UAV data to help develop situation awareness for first responders and search and rescue teams approaching an impacted area - NOTE that this will be a common theme throughout this exercise. These teams need to know quickly whether it is safe for them to proceed and what the conditions on the ground might be like. Imagine you are a geospatial professional supporting these efforts with existing GIS data and UAV data coming in from the field in near real-time.

Note: You will be setting up some software and downloading some relatively large datasets. Please do this early in the lesson even if you are unable to begin the exercise right away.

Here is a quick overview of what you will be doing and how it links with what we have learned so far.

• Part 1: You will gain experience using UAV-derived data products, in particular very high-resolution orthomosaics and 3D textured mesh models. Three case study areas from Switzerland are examined. Note, these represent situations with the technology and capability to develop these products rapidly and represents the cutting edge of what can be done with drone images and photogrammetry. The imagery you will look at does not come from a place with an active event but, as mentioned above, you will assume the role of a geospatial analyst developing an analysis for first responders and search and rescue teams moving into an area with an active incident. Most of your work will focus on the interpretation of an orthomosaic of a large industrial area. Then, you will consider the additional insights you can get from 3D textured mesh data but focused on smaller areas for the purposes of this exercise.
• Part 2: You will shift your focus to the use of UAV data in the immediate aftermath of the direct hit by Hurricane Irma on the small island nation of Antigua and Barbuda. The imagery is similar to what you examined in Part 1 but is coupled with a high resolution "before" satellite image. You will examine the scope of the damage done to the study area and provide some guidance to search and rescue and damage assessment.
• Deliverable: You will write two short reports for Part 1 and Part 2 that provide advice to emergency responders on what you have observed from the image analysis. As part of this, you will reference and provide some maps/screenshots of relevant parts of the UAV derived scenes.

See the following pages for more details.

Credit: NASA

Introduction

In this section of the exercise, you will work with two types of UAV-derived geospatial products, orthomosaics, and 3D textured mesh datasets. Your goal is to evaluate ways to use these data to support situational awareness for first responders and urban search and rescue teams. For example, think about suggested plans for an evacuation of the area and providing guidance for where search and rescue teams and damage assessment efforts should focus first. Remember to imagine that this is early data coming in from an emergency situation and that you are tasked with quickly providing spatial products for field operations.

Urban Search and Rescue Team Ready to Enter Area

Credit: By Gabriel - Flickr: 20110224-IMG_9637.jpg, CC BY 2.0, Link

Analysis Steps to Support Field Operations with UAS

Import and process UAV mission data using ArcGIS Pro and Pix4D

1. Install ArcGIS Pro and Pix4D
   You will use ArcGIS Pro and Pix4D to manipulate and interrogate 2D and 3D UAS datasets
   • You probably have ArcGIS Desktop and ArcGIS Pro already installed. If you don’t, this can take some time, so make sure you do it right away. Contact the instructor if you have any questions.
   • You will also need to download and install Pix4D Mapper. Instructions are provided in Canvas.
2. Access the Data
   I have already processed the raw UAV data with Pix4D for each step in this section because the computing time can be significant. I advise that you do the lesson with the pre-processed data first. However, feel free to experiment with the data processing steps. There is also an optional exercise that will provide an opportunity for you to process the data on your own using Pix4D.
   1. Begin by accessing the data and associated metadata in the OneDrive folder I shared with you via the the emailed link. Let me know right away if you haven't already downloaded the data.
   2. The datasets include:
      • A Pix4D Project named Building Scene -- This is also a 3D Textured Mesh, but in this case, it provides a detailed 3D view of a cluster of buildings.
      • A Pix4D Project named Forensic Scene -- This is a 3D Textured Mesh that provides an introduction to what can be done with drone imagery these days. You will contrast this interactive 3D view with the more common 2D view.
      • An ArcGIS Pro Project named Orthomosaic Industrial Area -- This is a very high-resolution mosaic of many individual photos taken by the UAV. You will start by interpreting and interrogating this dataset before learning more about how these images are created using photogrammetric techniques in Pix4D.
   3. Explore the Data
      As you copy and unzip these datasets, take a moment to review and identify key information from the metadata document (i.e. the mission report). What do you think is most important to understand about the mission and the data? For example, what is the coordinate system and map projection, and do they match the other datasets you might use?

Pix4D Quick Start

Pix4D is used to develop high-resolution imagery products (2D maps and 3D textured mesh images) based on captured images and their associated location information. So, it is a tool that could be used to develop spatial products in a relatively short period of time. Here, I have provided a quick start tutorial using the buildings dataset.

1. Double click to open the Pix4D project building_1.p4d. If prompted, navigate to the images folder associated with this project.
2. Explore the Map View. This shows the general study area and the locations of where the UAV images were taken, denoted by the red circles. Go ahead and click on one of the circles to see the corresponding image and parameters.
3. Open the Processing Options by selecting the button on the lower left of the display. This is where you set up the parameters for processing the raw imagery. Some of the options for outputs include point cloud, 3D mesh, Digital surface model, or Orthomosaic. There is also a panel that shows Resources and Notifications. You can view the resources available on your computer to do the processing.
4. Look at Processing panel (also at the lower left of the display). This shows the selected options and allows you to launch the model. NOTE: Because Pix4D can be really resource intensive, I have already generated output for you to consider. However, feel free to have a go at running this yourself – it just might take a while.

Now have a look at the processed results and explore some of the options for interrogating the data.

1. Select rayCloud view from the left hand options. Zoom in and note what is being displayed – toggle layers on and off.
2. Deactivate the Tie Point layer and look at the Cameras layer. This shows you the location and orientation of the camera at the time of acquisition by the UAV.
3. Activate the Point Clouds (and Point Groups) layers. This shows the point could be generated from the imagery and location information.
4. Activate Triangle Meshes and deactivate all other layers. This 3D textured mesh combines the 3D geometry with the imagery.
5. Explore the 3D textured mesh with the available tools in the Navigation and View toolbars.
   • Traditional pan and zoom with the standard navigation
   • 3D trackball navigation
   • Focus on the Selection tool
   • View from Top tool

Interrogate 2D Orthomosaic imagery

1. Open the ArcGIS Pro Project and have a look at what’s there. Examine the flight trajectory map and refer back to the mission report if you need to. Note the area covered and any variation in the quality of the mission. It is worth noting that you may not have complete coverage of the impacted area. That's where some historical imagery can be useful, as it allows you to provide advice about other potential nearby hazards, e.g., what do you do if the SAR teams are moving into places that are downstream from floodwater or hazardous facilities?
2. Note that these high resolution images have already been orthorectified and mosaicked by the drone data processing software (in this case Pix4D Mapper). So, soon after the mission, the data are provided to you in ready-to-use form. There are other courses and training you can do if you are interested in photogrammetry and image processing. There are a lot of services that can do this for you as well, and you have the option to work with Pix4D Mapper below.
3. Familiarize yourself with the content of the scene by panning and zooming around the image. Think about the advantages of having such high-resolution imagery when going into an uncertain environment. Start with some general observations about the industrial park, e.g., entrances and exits and then consider specific types of activities that are evident in the imagery through observing things like forklifts, loading areas, and liquid nitrogen stacks.
4. Create a point feature class in ArcGIS Pro and map five or more locations within the study area that you think are important for first responders and search and rescue teams to know about. These locations could include things like barriers (e.g., narrow access points, obstacles, dead ends), access points for responders and equipment, or potential hazards. There are no wrong answers here. The point is for you to get a sense for just how much information you can quickly gain from UAV data products.

Interrogate 3D Textured Mesh Data

1. In this part of the exercise, you will work with UAV-derived 3D Textured Mesh Data data in Pix4D Mapper.
   • You will be using this program as a way to explore the data rather than processing the raw imagery. Processing large UAV datasets can take considerable time (up to several hours) and the idea here is for you to use these products to think about an emergency management problem. That said, in the next OPTIONAL section, you can take a deeper dive and process some imagery yourself if you like.
   • You will look at two examples of 3D Textured Mesh models. These are high-resolution 3D models of locations that also have imagery draped over them in an accurate and realistic way. For example, you could move around a building to view a particular exit or even see fine details such as car headlights. Again, consider the implications of having access to this data product for emergency management operations and situation awareness.
2. Open the Pix4D Mapper project Forensic-1.p4d
   • Go to the Map View. Look at the study area and flight path.
   • Go to the Ray View and note the different Layers.
   • Toggle each layer on and off and note what each is representing and how it illustrates how the final products are derived. For example, note the camera locations and how they are linked to one another and the derived point cloud.
   • Turn off all layers except for the Triangle Meshes dataset. Pan and zoom around the image and make some observations about what you think would be useful for emergency teams with access to this level of detail.
3. Repeat these steps with the Pix4D Mapper project Building-1, but consider the greater complexity in this scene from the point of view of supporting emergency response activities.

Later in the course, you will learn about using geoAI and machine learning for rapid, automated assessment of imagery like this. We will also consider how data like this can be delivered more effectively to first responders and others in the field during emergencies.

Introduction

In 2017, Hurricane Irma had devastating impacts on much of the Caribbean, especially the island nation of Antigua and Barbuda. In fact, nearly all of the buildings on the island of Barbuda were destroyed, and almost the entire population was evacuated to Antigua before or immediately after the storm.

For more context, have a quick look at this reporting from the Guardian, The night Barbuda died: how Hurricane Irma created a Caribbean ghost town. If you have trouble with this link, go to the next page in Canvas. 

In this section, you will compare UAV imagery collected soon after the hurricane hit with ‘baseline’ satellite imagery taken before the storm. I want you to contrast the type of information you can get from high-resolution satellite imagery with that from an insanely high-resolution UAV mission. Approach this from the point of view of an emergency manager coordinating search, rescue, and recovery efforts in the immediate aftermath of the event. Also, consider the damage evident in the imagery in support of overall damage assessment and teams entering the field.

The data you will be working with came from a Canada-based group called UAViators and it is distributed on OpenAerialMap. If you are interested in this type of data (for your term project?), the OpenAerialMap website might be a good place to start looking.

Map of Barbuda - Codrington B

Credit: UViators

Steps to follow:

1. Begin by accessing the data and associated metadata in the OneDrive folder I shared with you via the the emailed link. Let me know right away if you haven't already downloaded the data.
2. Look at the ArcGIS Pro Project that I have created to help support your analysis. There are many different layers in this project, so have a quick look to see what’s there as you consider the specific context in Barbuda. Note the analysis focuses on the main settlement, Codrington. The data have been sourced from:
   1. Humanitarian Data Exchange
   2. OpenStreetMap Barbuda
   3. Global Health Data Exchange – Census Data
   4. The Caribbean Development Portal – Antigua and Barbuda
3. Think about how these easy to obtain datasets can rapidly paint a picture of conditions on the ground and the likely impacts on people and infrastructure. Is there anything major missing data-wise, and do you think you could easily find what you need in a hurry?
4. Next, load the satellite and drone imagery.
   1. The pre-event satellite imagery from Maxxar’s Open Data Program is another source of freely available data for disaster events. You might want to make note of this site when considering your term project.
   2. As mentioned above, the post-event UAV aerial imagery comes from UAViators via OpenAerialMap.
   3. Have a look at the properties of these two images and note their spatial resolutions, keeping in mind how these may influence the information that can be derived from the image.

For each part of this exercise, you'll write a short assessment of the situation on the ground, keeping in mind your role as a geospatial analyst supporting operations and field teams.

Each response should be about 400 words in length. Together, they are worth 50 points.

Submission Instructions

It is important for you to save your files in the following format so that I can match each submission up with the correct student.

L2_exercise_firstinitialLastName.doc For example, my file would be named "L2_exercise_mBeaty.doc"

Upload your assignment to the Deliverable: GIS and UAV Data Exercise Dropbox (L2). See the Course Syllabus or Calendar for specific due dates.

Grading Criteria

This will be graded out of 50 points and will count towards the Exercise portion of your grade. I will assess it using the following rubric.

In Lesson 1, you were introduced to the term project for this class. This week, you will choose one of the project options and decide what your project will cover. Your abstract should be no longer than 400 words. The goal of this exercise is to pave the way for you to write an exemplary term project, therefore, each section of the abstract will be graded on a satisfactory (1 point)/unsatisfactory (0 points) basis.

Your abstract is worth 6 points and should have the following sections and address these questions:

• Problem statement – In concise terms, what is your project about?
• Background – What is the context for your work?
• Objectives – What do you aim to achieve/demonstrate?
• Data and Methods – What data and methods do you anticipate using?
• Implications – What is the significance of your work? How might it be used in Emergency Management?

This week, I would also like you to set up a time to run your ideas by me. I think this will be particularly important with regard to the data component of your project. I can provide you with some feedback on whether the scope of the work seems too big, too small, or just right, and whether I think you’ll be able to get the data you need. This can be a quick discussion or we can take a bit longer if that is helpful.

I know it might be challenging to find a time to meet since we are likely in very different time zones - you probably recall I am based in Melbourne, Australia. That said, there will probably be some overlap where we can set up a voice or video call with Zoom or Skype or communicate via chat. I am fine with getting up early or staying up late to overlap with folks. Have a look at the World Clock Meeting Planner where you can put in your location and my location and see the hours of overlap. Then suggest a time you'd like to talk. I am happy to help with this as well.

Summary

This week, you have been introduced to the range of potential hazards that spatial data science for emergency management must be prepared to handle. In your reading assignment, we began to explore some of the key issues associated with supporting emergency management tasks with geospatial tools. Knowing how to design an effective geospatial system for emergency management depends on understanding hazards as much as it depends on understanding the capabilities and limitations of current geospatial technology.

Now that you have a general understanding of the types of hazards relevant to spatial data science for emergency management, we will begin examining the first of the four stages of emergency management in greater detail. In the next lesson, we will explore the role of geospatial perspectives and technologies for Preparedness activities.

Reminder - Complete all of the Lesson 2 tasks!

You have reached the end of Lesson 2! Double-check the to-do list on the Lesson 2 Overview page to make sure you have completed all of the activities listed there before you begin Lesson 3.

Questions?

If you have any questions, please post to the Canvas Discussion Forum called "General Questions" or email the instructor via Canvas conversations (if the question is personal in nature).

Tokyo, Japan: What would happen if another major earthquake struck Japan and caused a blackout that lasted over a month in a city like Tokyo? How could geospatial applications and technology be used to examine vulnerabilities like that for major cities?

Credit: Anthony Robinson

This week, we focus on the first of the four phases of emergency management - vulnerability assessment and hazard mitigation. We will read about risk mapping and vulnerability assessment using spatial data and GIS. Building on the background knowledge we've gained from previous lessons, each of you will conduct an analysis of Heatwave vulnerability, impacts, and mitigation strategies using social and environmental data. You will also continue making progress on the term project assignment.

Credit: © Penn State University is licensed under CC BY-NC-SA 4.0

Mitigation

The improvement of the built and social environment in order to reduce, withstand, or prevent disaster impacts.

• Hazard Analysis
• Vulnerability Assessment
• Scenario Development
• Community Engagement and Education
• Planning and Infrastructure Work

What You Will Learn

By the successful completion of Lesson 3, you should be able to:

• describe the concepts associated with risk mapping and vulnerability assessment,
• conduct your own vulnerability assessment using social and environmental spatial data and summarize your findings in a short essay,
• conduct background research for your final project,
• and discuss the technology trend of volunteered geographic information (VGI).

What You Will Do

Lesson 3 is one week in length. To finish this lesson, you must complete the activities listed below. 

Please refer to the Calendar in Canvas for specific timeframes and due dates.

Questions? 

If you have questions about the content or lesson activities, please post them to the General Questions and Discussion forum in Canvas. While you are there, feel free to post your own responses if you, too, are able to help a classmate. If your question is of a personal nature, please email me directly through Canvas.

Understanding the Geography of Vulnerability

Developing a clear picture of an area's vulnerability to hazards and disasters is a non-trivial task. It's hard to predict exactly what could happen in a disaster situation. However, even a rough estimate can be a huge help to emergency managers and decision makers who can use that information to develop plans for allocating resources and managing recovery operations. By collecting socio-economic and environmental data sources in a GIS, for instance, we can develop risk maps to highlight the potential impact of disasters on people and infrastructure. In this lesson, we will examine some of the specific analytical methods for doing a vulnerability assessment, and we will reflect on the critical issues associated with planning an emergency management GIS system that includes vulnerability assessment as one of its key functions. Most systems for geospatial and emergency management are designed for reaction, not prediction and mitigation, but that’s changing fast.

There is a wide range of relevant questions to consider when conducting a vulnerability assessment, including answers to the following key questions:

• Who is at risk? How many will be affected?
• What is the spatial and temporal extent of the vulnerability?
• What capacity does the population at risk have for coping with the disaster?
• What is the range of scenarios given different conditions (for example, a Category 2 hurricane vs. a Category 5 hurricane)?
• What happens when multiple disasters occur at the same time (for example, heatwaves during major wild fires; hurricanes during pandemic shutdown)?
• Across all of these is the ‘where’ question, and what roles do spatial relationships play?

Here are a couple of examples of web-based services providing geospatial data on hazards and vulnerability; there are many others!

The first example is a map service developed and maintained by the U.S. Federal Emergency Management Agency (FEMA) that coordinates and conducts a great deal of vulnerability assessment work, including flood mapping. FEMA flood maps are used to help set flood insurance rates, among other things. The flood mapping tool shows an overview of ongoing FEMA flood mapping, levee repair, and other flood-related risk assessment and mitigation tasks. Contrast this with recent research reported in this interactive New York Times page - New Data Reveals Hidden Flood Risk Across America. Note: you shoudl be able to view the interactive maps without a subscription, but if you are having trouble, you can view a copy of the article on the following page in Canvas.

Online tool providing access to FEMA flood maps. Maps like these can be used for a variety of purposes including advanced planning for emergencies or disasters and assessing insurance risk for housing and infrastructure.

Credit: FEMA

OCHA Regional Office for Asia Pacific, Indonesia: Natural Hazards Risks

Credit: OCHA

The United Nations engages with other entities to develop risk maps for developing countries where they are likely to be involved in future disaster situations. If you check out the map above in greater detail, notice who the collaborators are. They include several NGOs, as well as Munich Re, a major re-insurance player. Interesting, huh?

Keep this Indonesia map in mind, because later in the course you will be considering the 2018 Sulawesi Earthquake and Tsunami in greater detail.

Some private sector firms provide what is known as Address Risk Rating products - in essence, you can look up a specific address and get a report outlining all of the vulnerabilities associated with that location. One of our PSU faculty, Dr. James O'Brien, works for Risk Frontiers in Australia, a firm that works on Address Risk Rating products among others. Here is another example, UNHaRMED model, from the University of Adelaide and the Australian Bushfire and Natural Hazard Cooperative Research Centre.

These examples don't explicitly consider people and the wide range of factors that make some people and places vulnerable while others are not. You will see it is not just a matter of whether you are inside or outside of an impacted area. Geographers have done a lot of work on social vulnerability analysis as part of a rich tradition of Hazards Research.

In this week's hands-on exercise, you will be working with some data related to heatwaves in the USA. Through this work, you will gain an understanding of vulnerability assessment approaches using geospatial data and how they can be used to understand some of the priority areas for action leading up to and during a disaster.

Before conducting the analysis and developing the accompanying short report, I would like you to watch a short overview video on Social Vulnerability Indices (SVI), read a chapter from your textbook on GIS and Disaster Mitigation, and read a journal article on Social Vulnerability to Natural Hazards in Brazil. This material will help you gain an understanding of the human dimensions of vulnerability that I mentioned previously.

Watch

Please watch this 3:45 minute video on Social Vulnerability Indices (SVI) from the US Centers for Disease Control and Prevention (CDC).

Read

1. GIS for Disaster Management - Chapter 8 "Geographic Information Systems and Disaster Mitigation (pp. 233-250)
   In this chapter from your textbook, the author goes into some good detail on assessing and modeling risk and vulnerability using GIS, including where to get data to do your own and a few straightforward analysis steps using GIS. It also includes core concepts associated with evaluating mitigation policies as well as the ways in which people can develop social and environmental variables to model risk and resilience.
2. Loyola Hummell, Cutter, Emrich (2016). Social Vulnerability to Natural Hazards in Brazil. International Journal of Disaster Risk Science, volume 7 (issue 2), 111-122. This final reading will serve as a rough model for what we will work on next in the hands-on portion of this exercise.
3. OPTIONAL / FYI - Georgianna Strode et al. (2020). Exploratory Bivariate and Multivariate Geovisualizations of a Social Vulnerabity Index.

Heatwave Vulnerability, Impacts, and Mitigation Options

Unsplash.com

Introduction

The last year has seen extreme heatwaves affecting much of the world including in China, India, the USA, and Europe. Heatwaves damage infrastructure, overload power grids, reduce work safety and productivity, and have negative impacts on quality of life in general. Moreover, more deaths and illness are due to heatwaves than any other natural disaster, and in the case of the USA and Australia, more than all other natural disasters combined.

Heatwaves can also compound the impacts of other types of disasters. For example, earlier this year Australia experienced extreme flooding followed by a heatwave. This led to a situation where people were outside cleaning up when temperatures were dangerously high.

Heatwave deaths and illness are generally thought of as being entirely preventable. That is, proper mitigation, preparedness and response activities can be undertaken to minimize or eliminate harm e.g., through effective heatwave warning systems and providing the public with “cool places” to get out of the heat.

There is also a strong emphasis on planning and implementing mitigation and adaptation strategies to reduce vulnerability and promote resilience when heatwaves strike. For example:

• Urban planning might focus on “green and blue infrastructure” to reduce Urban Heat Island (UHI) effects;
• Social welfare groups (e.g., Red Cross) have “opt-in” systems where vulnerable older people are contacted throughout the heatwave event to make sure they are coping well; and/or
• Heat-health outreach to help educate the community about the dangers of extreme heat, how to respond to warning messages, and what steps to take.

Heatwave vulnerability and impacts are not spread evenly across populations and geography. This has a lot to do with differences in socioeconomic factors and characteristics of the built environment e.g., low tree cover, poorly designed housing. Just as there is a geography to vulnerability and impacts, there is also a geography to potential solutions. We often think of these as “spatially targeted interventions”.

In this exercise, you will consider these issues in greater detail and use spatial data and analysis to identify patterns of vulnerability and potential impact along with ways of addressing risk and reducing vulnerability.

Learning Goals

• Examine what defines a heatwave and its relationship to weather and microclimate
• Describe trends in heatwave occurrence, duration, and severity both in the past and in the context of global warming
• Develop an understanding of heat impacts on people and infrastructure, particularly regarding key socioeconomic vulnerabilities
• Understand how heatwaves are managed and how they can compound other common natural hazards
• Be able to discuss heatwave vulnerability, impacts, mitigation, and adaptation options in the context of the emergency response cycle

Analysis Steps

1. Heatwave trends and impacts
2. Vulnerability mapping and assessment
3. Spatial analysis of mitigation and adaptation options
4. Report to planners and emergency managers

Part 1 - Heatwave trends and impacts

In this section, you will take a close look at key characteristics of heatwaves, trends related to climate change, and some of the direct impacts of heat on people. You will produce a few graphs and maps that will be incorporated into your write-up in Part 4.

A. What are heatwaves?

Understanding Heatwaves (2:05)

From the video, take note of these key characteristics of heatwaves:

• Occurrence - How often do heatwaves occur?
• Duration - How long do they last?
• Severity - How severe are the impacts?
• Diurnal cooling - Is there 'cool relief' overnight e.g., are nights hot too?

Source: Australian Bureau of Meteorology Heatwave Forecast Service

Heatwaves are not defined just based on temperature, rather humidity and longer term trends (acclimatization) need to be incorporated. In the map above based on Excess Heat Factor (EHF), heatwaves are classified into three types, based on intensity. Note these mention potential impacts on people, infrastructure and the environment.

• Low-intensity heatwaves are the most common—most people are able to cope with this level of heat
• Severe heatwaves are less frequent and are challenging for vulnerable people such as the elderly—particularly those with pre-existing medical conditions
• Extreme heatwaves are the rarest kind. They affect the reliability of infrastructure, like power and transport, and are dangerous for anyone who does not take precautions to keep cool—even those who are healthy. People who work or exercise outdoors are particularly at risk

Source: Australian Bureau of Meteorology Heatwave Forecast Service

B. How have heatwaves have changed over time, and why?

Heatwave occurrence, duration and severity have all been changing over time. There are several important drivers of heatwaves, including reduction in vegetation cover and more built-up (impervious) surfaces in cities. Climate change is perhaps the strongest factor causing changes in heatwave characteristics (see list above).

Consider the following series of maps showing annual temperature trends in the USA. These patterns are similar to what we are observing globally.

U.S. Annual Temperature Compared to 20th Century Average

NOAA at climate.gov

In addition to changes in average temperatures, there have also been changes in the occurrence of extreme events. The following diagram illustrates this, where a shift in mean climate results in more hot and extreme days. As an aside, there is a growing interest in the effects 'chronic heat' on health and wellbeing i.e., hot days but not falling into the 'heatwave' range.

Projections of Climate models for Europe: Increase in Mean

Stagge, James & Rizzi, Jonathan & Tallaksen, L.M. & Stahl, Kerstin. (2015). Future Meteorological Drought: Projections of Regional Climate Models for Europe.

You will finish off this section by conducting some analysis of trends in the key heatwave characteristics (mentioned above) in the USA.

1. Create bar charts showing - Heatwave Characteristics in the US by Decade 1961-2021
   • Use the "Heatwave characteristics USA - trends.csv" in the GEOG_858_Lesson_3 project folder (download from class OneDrive folder)
   • You can use Microsoft Excel. Make sure the charts are easy to understand and have appropriate labels and titles. (A 2 x 2 panel of charts would be a good choice!)
2. Create a map - Examine regional differences Heatwave Characteristics in 50 Large US Cities, 1961-2021
   • Use the "Heatwaves_USA_cities_trends" table in the GEOG_858_Lesson_3 ArcGIS Pro project (created for you - GEOG_858_Lesson_2.aprx; download from class OneDrive folder)
   • You will need to spatially enable this table using the latitude and longitude fields in the table
   • Make sure the map is easy to understand and have appropriate symbology and design (graduate circles would be a good choice).
3. Summarize the main trends/messages in a couple of sentences? This will feed into your report in Part 4.

C. Heatwave impacts

This section focuses on some of the "direct effects" of heatwaves on people, including deaths and illness.

The following image is a warning poster produced by the SA Health to help people recognize the signs of heat exhaustion and heat stroke. Note this is advice aimed at everyone and not targeted to specific groups or places.

Heat-Related Illness Signs, Symptoms And Treatment

Know the Signs of Heat Related Illness

Click here for a text alternative of this graphic

Know the Signs

Left Side of the Graphic – Heat Exhaustion

Symptoms:

• Headaches
• Nausea and vomiting
• Fatigue, weakness and restlessness
• Thirsty
• Anxiety
• Poor coordination
• Weak, rapid pulse
• Sweating heavily
• Raised body temperature

What to Do:

• Lie down in shade or air-conditioning
• Drink water
• Cool compress or tea towel
• Cool shower or bath

Right Side of the Graphic – Heat Stroke

Symptoms:

• Headaches
• Nausea and vomiting
• Rapid pulse
• Extremely thirsty
• Dry, swollen tongue
• Disoriented, dizzy or delirious, slurred speech
• Body temperature more than 40°C
• Convulsions, seizures or coma
• May be sweating, skin may feel deceptively cool

What to Do:

• Call 000 immediately
• Reduce temperature until ambulance arrives

Source: Government of South Australia – SA Health

Source: South Australia Health

Public warning message, such as this, provide simple and consistent information. These are linked to dedicated websites focused on heat related health. Have a quick look at these two examples, again noting that heatwave illness and deaths are, in theory, entirely preventable.

• Heat-Related Illness Signs, Symptoms And Treatment page from SA Health.
• CDC's Natural Disasters and Severe Weather website.

Heatwaves also have significant impacts on critical infrastructure and the environment. We won't go into much detail, but watch this short video from the Today Show, noting the reporting on impacts to critical infrastructure and the environment. If you want to learn more, there is no shortage of news coverage and research literature on these impacts.

Record-Shattering Heat Wave Leads To Deaths Across Britain (2:24)

You will finish off this section by looking at some trends in heat related deaths and illness.

1. Create a time-series graph showing - Deaths Classified as "Heat-Related" in the United States, 1979-2018
   • Use the "Heat related deaths USA 1979 - 2020.csv" file in the GEOG_858_Lesson_3 project folder (download from class OneDrive folder)
   • You can use Microsoft Excel. Make sure the charts are easy to understand and have appropriate labels and titles.
2. Use the CDC National Environmental Public Health Tracking Network tool to examine broad patterns in heat related mortality and illness.
   • Navigate to the website and have a look at what information is available. Then launch the Data Explorer Tool (noting this can be a little slow).
   • On the left side map, fill in Steps 1-5 as shown in the image below. On the right side, use the same options but change "Mortality from HRI" to "Emergency Department Visits".
   • Look at different years by adjusting the "Year" pull down menu.You can also click on the "Play" and observe how the number of cases vary by year.
   • Consider taking a few screenshots to have on hand for Part 4.
   • Finally, download the two datasets (Mortality and ED) using the "Export Data" button. Before leaving the site, change one of the maps to heat related Hospitalizations and export that data too.

Enter caption here

Data Explorer Tool Query Panel

3. Create a time-series graph showing changes in mortality, emergency department admissions, and hospitalizations for California versus the national average.
   • Open the Mortality dataset in Microsoft Excel and insert a Pivot Table. Drag "State" to the Filter box, "Years" to the Row box, and "Value" to the Values box (change from Count to Average). In a new worksheet, copy and past the pivot table as values. Rename columns to "Year" and "US_average".
   • Go back to pivot table and select California from the State pull down menu, and change Average of value to Sum of value. Cut and paste the Sum of Value column to the sheet with the US_average. Your columns should have these headings - "Year", "US_average", and "California". Delete the Grand Total row.
   • Plot the two time series together. Make sure the charts are easy to understand and have appropriate labels and titles.
   • Repeat for Emergency Department and Hospitalizations and display the three charts on a single page for easy comparison.
4. Summarize the main trends/messages in a couple of sentences? This will feed into your report in Part 4.
5. Optional: You looked at counts of events. Would it be better to look at rates on a population basis (e.g., per 100,000)?

Part 2 - Vulnerability mapping and assessment

So far we have considered broad trends in heatwave characteristics and direct impacts on people (e.g., heat stroke) and infrastructure. In this section you will consider some of the factors that make a person or community more vulnerable to adverse heatwave impacts. We will be taking a much more granular look at the problem in this and the following sections.

What are the factors contributing to heatwave vulnerability?

We are going to focus on heatwave vulnerability and impacts from the perspective of human health. This figure illustrates the basic problem - people must maintain their body temperature within a specific range to avoid adverse health outcomes. This is influenced by the ambient environment and characteristics of that person e.g., do they have existing health problems that may compromise their ability to thermo-regulate?

Heat Health Vulnerability Indices, Themes and Indicators

Source: Queensland Health and Queensland University of Technology

There are also a set of broader factors influencing heat health. The framework illustrated in this figure was used in a recent study to understand heat health vulnerability. This is similar to the CDC Social Vulnerability Index (SVI) you would have seen in one of the previous videos, however the focus here is explicitly on heatwaves.

Enter caption here

Click here for a text version of this graphic

Index: Exposure

Theme: Heat Exposure

Indicators:

• Land surface temperature
• No vegetation
• Housing age (Pre-war, Post-war, Late 20th Century, Contemporary)
• High rise dwellings (four storeys or more)
• Outdoor workers

Index: Sensitivity

Theme: Socioeconomic Status

Indicators:

• Low equivalised total household income
• High unemployment
• Education – Year 10 or less

Theme: Household Composition

Indicators:

• Aged 65 or older
• Aged 0–4 years
• Disability
• Living alone

Theme: Language and Culture

Indicators:

• English language proficiency
• New arrivals/refugees
• Indigenous

Theme: Housing Conditions

Indicators:

• Flats or apartments
• Rental housing
• Crowding
• No vehicle
• Social housing
• No home internet

Theme: Health Status

Indicators:

• Arthritis
• Asthma
• Circulatory system conditions
• Chronic obstructive pulmonary disease
• Diabetes
• High cholesterol
• Hypertension
• Mental/behavioural problems
• Musculoskeletal system conditions
• Respiratory conditions

Theme: Health Risk Factors

Indicators:

• Alcohol consumption
• Overweight and obesity
• Smokers

Index: Adaptive Capacity

Theme: Access to Health Services

Indicators:

• Hospitals
• General practitioners
• Aged care
• Aboriginal and Torres Strait Islander services
• Community services
• Emergency departments
• Mental health services
• Pharmacy
• Psychiatry

Theme: Access to Cool Places

Indicators:

• Public open space
• Cool places
• Vegetation
• Water bodies

Theme: Social Connectedness

Indicators:

• Household stability – moved last year
• Household stability – moved in the last 5 years
• Volunteerism
• Vehicle at home
• Internet at home

Reducing Illness and Lives Lost from Heatwaves Project

Vulnerability indices

Generally speaking, indices are designed to help us describe concepts that are not able to be measured directly. For example, "Vulnerability" or "Socioeconomic status" are a multidimensional concept that cannot be measured with a single variable. There are many different indices developed for different purposes. Here you will take a closer look at two of the most widely used approaches.

FEMA's National Risk Index (NRI)

Have a closer look at the FEMA's National Risk Index website. There are three components to the NRI:

Enter caption here

Click here for a text version of this graphic

Risk Index Formula Components

The National Risk Index (NRI) is calculated using the following formula:

Risk Index = (Expected Annual Loss × Social Vulnerability) ÷ Community Resilience

Component Descriptions:

• Expected Annual Loss (orange icon with lightning and rain):
  A natural hazards component that represents the average economic loss in dollars resulting from natural hazards each year.
• Social Vulnerability (green icon with family figures):
  A consequence enhancing risk component and community risk factor that represents the susceptibility of social groups to the adverse impacts of natural hazards.
• Community Resilience (purple icon with interlocked hands):
  A consequence reduction risk component and community risk factor that represents the ability of a community to prepare for anticipated natural hazards, adapt to changing conditions, and withstand and recover rapidly from disruptions.

The resulting Risk Index (NRI, shown with a striped icon) represents the potential for negative impacts resulting from natural hazards.

FEMA's National Risk Index

Note that the Social Vulnerability component is based on another index called the Social Vulnerability Index, or SoVI. This is one of the first approaches ever developed for emergency management, and it uses principal components analysis PCA) to reduce a set of variables to one index representing low to high vulnerability.

Similarly, Community Resilience is based on another commonly used approach called Baseline Resilience Indices for Communities (BRIC). BRIC also uses a set of indicators to build up the indices, but it does this through a "standardize and rank approach". To learn more, have a look at the NRI website and/or download the NRI manual.

When considering index approaches such as these (and any dataset for that matter), it is important to consult available metadata and "data dictionaries" (e.g.,here is the NRI data dictionary), sometimes referred to as the Data Item List (DIL), that goes with a given dataset. You will find the NRI data in the ArcGIS Pro Project accompanying this lesson. I have mapped the SoVI component of the NRI. Have a look at the NRI attribute table, scan the field names, and look up a few variables in the data dictionary.

CDC Social Vulnerability Index (SVI)

Next, have a closer look at the CDC Social Vulnerability Index (SVI). The SVI takes an approach that is similar to BRIC, where individual variables are used to calculate sub-indices (Themes) and then the overall index. For example, Socioeconomic Status cannot be measured directly, so "below poverty" line, "Unemployed", "Income", and "No High School Diploma" are combined to get at this construct.

Enter caption here

Click here for a text version of this graphic

Overall Vulnerability Components

Overall Vulnerability is made up of four main themes, each with specific indicators:

1. Socioeconomic Status

• Below Poverty
• Unemployed
• Income
• No High School Diploma

2. Household Composition and Disability

• Aged 65 or Older
• Aged 17 or Younger
• Civilian with a Disability
• Single-Parent Households

3. Minority Status and Language

• Minority
• Speaks English "Less than Well"

4. Housing Type and Transportation

• Multi-Unit Structures
• Mobile Homes
• Crowding
• No Vehicle
• Group Quarters

CDC SVI Documentation 2018

Note the table accompanying the SVI feature class includes the underlying data that is used in the index calculations. If you want to "unpack" a given index, you can look at individual variables. For example, you may observe a "vulnerability hotspot" and wish to know why that is the case. SVI let's you drill down to themes and individual variables. In a particular area, you may find that socioeconomic status is the most important theme and poverty and unemployment may be the most important single indicators. You will take a closer look at the CDC SVI, and, as with NRI, it is important to have any metadata and data item list handy (open a copy with this link SVI data dictionary).

Urban Heat Island and Microclimate

When we hear about heatwaves, we often focus on weather as the main driver. However, heatwaves are experienced differently in different places due to variation in microclimate related to the build and natural environment.

Urban Heat Islands

Heat Island Effect Diagram

"Surface temperatures vary more than atmospheric air temperatures during the day, but they are generally similar at night. The dips and spikes in surface temperatures over the pond area show how water maintains a nearly constant temperature day and night because it does not absorb the sun’s energy the same way as buildings and paved surfaces. Parks, open land, and bodies of water can create cooler areas within a city. Temperatures are typically lower at suburban-rural borders than in downtown areas." 

US EPA Heat Islands

Microclimate

In addition to broader UHI effects, there is considerable variation in microclimate (e.g., local temperature) related to features of the built environment. In the following thermal image from Los Angeles in Summer 2018, you can clearly see higher temperatures in more built up areas. Major roads, downtown LA, and the Port of Long Beach stand out as hot spots while areas such as Beverly Hills and Santa Monica along the coast are cooler. Note how you can actually see the "hot" road network grid in the area around Anaheim. This illustrates very fine variation in land surface temperatures. A key point to takeaway, is that local conditions can enhance or ameliorate heatwaves e.g., think about the simple example of standing in an open parking lot versus standing under a tree during a heatwave!

Los Angeles Heat Wave.

Credit: NASA Jet Propulsion Laboratory

You will finish off this section by continuing to looking heat health vulnerability in Los Angeles County, California. All of the spatial data are provided in the ArcGIS Pro Project, GEOG_858_Lesson_3.aprx.

Mapping social vulnerability

1. Take a closer look at the National Risk Index (NRI) by first looking at the attribute tables and data dictionaries.
2. The NRI data are in the "NRI_LA_County_tract" feature class. Look at the attribute table and data dictionary to get a general idea of what it contains.
   • Create three maps based on these data, and consider putting them together on a single page for easy comparison.
     • Overall NRI
     • Social Vulnerability
     • Community Resilience
   • When mapping these data, use the Quintile classification method with five classes. This will put each census tract into groups of 20% each. Also, note you can copy and paste each feature within the Contents Panel as you create new maps i.e., you don't have to load a new feature class every time.
3. The CDC SVI data are in the "SVI_LA_County_tract" feature class. Look at the attribute table and data dictionary to get a general idea of what it contains.
   • Create four maps based on these data, and consider putting them together on a single page for easy comparison.
     • The overall SVI
     • Socioeconomic Status theme
     • Minority Status and Language Theme
     • Choose a single variable to map e.g., Aged over 65, single parent households,... your choice!
4. Make sure your maps are easy to understand and have appropriate symbology and design.
5. Summarize the main trends/messages in a couple of sentences? This will feed into your report in Part 4.

Urban Heat Island and Microclimate

1. Look at the Urban Heat Island Map for Los Angeles County developed by CalEPA (already in the Lesson 3 ArcGIS Pro project). In 2-3 sentences, describe what this map is showing and how it relates to the social vulnerability mapping you did in the last section e.g., how intense is the UHI effect in vulnerable areas of LA County?
2. Explore variation in microclimate using the California Heat Assessment Tool dataset in your ArcGIS Pro project. You can also use the online tool. Start by looking at the CHAT metadata and data dictionary. Note that the data in the project have been extracted from the CHAT website and represent historical conditions for June, July, and August and for the general population.
3. From the "CHAT_LA_County_historical_JJA_general_population" feature class, map:
   • Historical average maximum temperature
   • Historical average duration
   • Historical average number of events
   • These can be single maps, but feel free to be creative e.g., can you visualize some of this data in a single map?
4. From the "CHAT_LA_County_vulnerability_indicators", map
   • CHAT Heat Health Action Index (heat_health_action_index)
   • Percent population experiencing poverty (perc_poverty)
   • One other vulnerability indicator of your choosing e.g., Elderly, Asthma Prevalence
5. Make sure your maps are easy to understand and have appropriate symbology and design.
6. Summarize the main trends/messages in a couple of sentences? This will feed into your report in Part 4.

Part 3 - Spatial analysis of mitigation and adaptation options

The final part of your analysis will focus on an assessment of a some heatwave mitigation options. The first focuses on "green infrastructure" and the role of tree canopy cover in urban cooling. You will then look at the distribution of "Cooling Centers" in LA County and the populations they serve. For both cases, you will use spatial data to assess the current situation and provide analysis and advice on what could be done in the future.

ASTER Los Angeles from Space

Credit: NASA JPL

Canopy cover, social vulnerability and mitigation

1. In the ArcGIS Pro project, display the Tree Canopy Layer. Note the general patterns across LA County.
2. Create a second map showing one of the other land cover types e.g., Grass, Shrub, buildings.
3. Use bi-variate maps to look at relationship between canopy cover and social vulnerability
   • You will use the "CHAT_LA_County_vulnerability_indicators" layer.
   • Take a look at the bi-variate map of the Heat Health Action Index and Percent No Tree Cover I have already created, and note how the bi-variate maps are set up in Symbology.

   • What does the map show?

     

     Bi-variate map legend for Heat Health Action Index and Percent No Tree Cover. Note "Both High" indicates areas with low tree cover and high heat health vulnerability
4. Next, replace the Heat Health Action Index variable with another variable in the "CHAT_LA_County_vulnerability_indicators" layer e.g., poverty, race, asthma.
   • When choosing think about what you want to investigate regarding the relationship between no canopy cover and social vulnerability.
5. Finally, look at the bi-variate map showing existing versus potential tree cover. This has already been produced for you.
   • The potential tree cover layer is based on whether there is "physical space" for new trees. What does this suggest about the potential for urban greening in vulnerable communities?
6. Make sure your maps are easy to understand and have appropriate symbology and design.
7. Summarize the main trends/messages in a couple of sentences? This will feed into your report in Part 4.

Cool place accessibility

Many cities now have designated "cool places" people can go during heatwaves. In this part of the exercise, you will look at whether officially designated cool places in LA County provide good coverage of the city, are easily accessible, and how they may be improved.

1. Before getting started, make sure you are connected to the Penn State University Portal. You can check this by looking in the upper right side of ArcGIS Pro. You should see your name followed by the text "Penn State University". This is important because the next steps use Esri credits, and we don't want these deducted from your work account!
2. In the Lesson 3 project showing the location of Cooling Centers. Have a look at the distribution and areas supported.
3. Use the Generate Drive Time Trade Areas tool in ArcGIS Pro from the Business Analyst Toolbox.
   • You will consider two cases
     • Cooling centers that are within 15 minute and 30 minute walking times
     • Cooling centers that are within 15 minute and 30 minute driving times
   • Run these tools and view the mapped results
4. Now estimate the proportion of the LA County population that falls within a 15 minute walk of these official cooling centers. Do this by selecting census tracts in the "SVI2018_LA_County_tract" feature class based on the 15 minute walk time areas and summing the population field (E_TOTPOP)
5. Summarize the main trends/messages in a couple of sentences? What are the areas of unmet need? Are cooling centers in vulnerable parts of the city? This will feed into your report in Part 4.

Part 4 - Report to planners and emergency managers

For the final part of this assignment, you will draw upon the analysis and key points developed in Parts 1, 2, and 3 to write a short briefing document (500 words) for planners and emergency managements in Los Angeles County. This should cover:

1. Heatwave trends and impacts - Explain how and why heatwaves are an emergency management problem and the major trends and patterns across the USA.
2. Vulnerability mapping and assessment - Describe social vulnerability to heat within LA County, and relationships with the Urban Heat Island effect and microclimate variation.
3. Spatial analysis of mitigation and adaptation options - Provide an assessment for the potential for urban green in the most vulnerable areas. Share findings and recommendations from your cooling center evaluation.
4. Any overall observations and recommendations not already included in report.

For this week's Emerging Theme, you will review the materials below and engage in a Canvas discussion with your classmates - see details below.

Spatial data has traditionally been developed by government agencies and businesses who could afford the technical and financial expenditure necessary to digitize spatial information. Recent advances in web mapping and GPS technology make it possible for tech-savvy volunteers to develop their own spatial datasets. This sort of geographic data is frequently called "Volunteered Geographic Information" or VGI for short. The following short (31 seconds) video below shows the dramatic VGI response to the 2010 Haiti Earthquake through additions and corrections to OpenStreetMap data for the country. Haiti had previously been a poorly-mapped place, and there was an immediate need in the aftermath of the disaster to develop a much better base-map to help recovery efforts. This was a watershed event in VGI for disaster/humanitarian response as discussed by Meier in the first chapter of Digital Humanitarians you read in Lesson 1.

One of the most effective VGI efforts can be found at OpenStreetMap.org. OpenStreetMap has the goal of developing a basemap of roads, place names, and other common spatial features for the world, based entirely on volunteered contributions. The OpenStreetMap project aims to provide a completely free worldwide geospatial dataset without any legal or technical restrictions on its use. Most popular web mapping resources like Google Maps or Bing Maps tightly constrain how their data can be manipulated, published, or displayed. Quite a few folks take it for granted that these maps are free, but, in fact, they are only free because those companies are providing access to them right now for free. You are not allowed to re-use and re-purpose those resources or download their data yourself, and if Google decided tomorrow to charge you for access to their maps, you would have no recourse to ensure you kept access for free.

Another important trend in VGI is the use of microtasking or ‘micromapping’ campaigns that split up a big task into small chunks that the VGI community can take on. For example, have a look at the this interesting and useful review of microtasksings role in emergency management from the Australian Institute of Disaster Resilience. In some systems, you are presented with tiles from high-resolution imagery and you are asked to search for and tag features like ‘Trash heaps’, ‘Blocked roads’ and ‘Damaged buildings’. It is worth noting that microtasking like this can also be used to train Machine Learning algorithms to detect these same features with high accuracy. You can read more about this in Chapter 6, ‘Artificial Intelligence in the Sky’, of Digital Humanitarians. This is really cutting-edge stuff that is happening now.

Now, I’d like you to consider VGI with “citizens as sensors”. This is where information relevant to the disaster is collected through devices people are carrying around. I am sure you can think of lots of examples of data you could get from smartphones, but I wanted to highlight a project that started in Japan shortly after the Fukushima Daiichi nuclear disaster. The Safecast team developed small devices for radiation, mapping the results which you can see on the web map here. A very recent example of citizens as sensors is the COVIDSafe App being used in Australia. This is a contract tracing app that records all of the people you come in contact with via Bluetooth on mobile phones. The data are encrypted on your phone and only accessed if someone you came in contact with someone who tested positive for COVID-19.

Finally, for a critical perspective, please look at the recent (2018) paper by Billy Tusker Haworth titled, “Implications of Volunteered Geographic Information for Disaster Management and GIScience: A More Complex World of Volunteered Geography".

This week, I will be evaluating the abstracts you developed last week. While I do that, I encourage you to spend some time looking for relevant background information that will help you develop your project. This should include identifying some of the data sources you will need. I am happy to provide suggestions of places to look, but have a go on your own first!

To get started, you could:

• look for background and context information for the topic you have chosen (who has worked in this area before, and what did they accomplish?);
• look for examples you can use to justify your choice of methods;
• look for application examples of the use of geospatial analysis in emergency management;
• identify and compile the data you need for your analysis (and touch base with me if you have any problems – the earlier the better!).

Each project will have quite specific needs, so you will need to think of the additional information you will need to write your report.

Some Suggestions...

• I encourage you to make use of our excellent Penn State library resources. You can skip the overview (but I don't suggest it) and go right to the library search as well. You probably know this, but the search functions include a lot more than books, e,g., reports, journal articles, dissertations, and theses. Many of the references are available in electronic form and can be downloaded. The library also has an "Ask a Librarian" chat that allows you to chat with a librarian in real time.
• Google Scholar is your friend. This is one of the primary ways academics now search for articles. It is also a good way of developing scientific 'social networks' as it is easy to follow links to other works by an author, or who they are working with, etc.
• Finally, have a look at the recent proceedings from the ISCRAM conference. There are tons and tons of good stuff there. Oh, ISCRAM is a professional society for people working in the field of Information Systems for Crisis Response and Management.

Summary

In this lesson, we have learned about the first stage of emergency management - vulnerability assessment and hazard mitigation. We focused attention on how geospatial data and tools can be used to conduct risk mapping analyses to identify places where populations and critical infrastructure are vulnerable to disasters.

An effective vulnerability assessment requires answers to the following questions (among others, of course):

• Who is at risk? How many people will be affected?
• What is the spatial and temporal extent of the vulnerability?
• What capacity does the population at risk have for coping with the disaster?

When developing geospatial system for emergency management, one must consider the analytical tools and data sources necessary to answer these questions. Often, decision makers need information on potential human and financial losses to make their case for resources to mitigate against disasters.

In the next lesson, we will shift focus toward situations in which a disaster is imminent and geospatial analysis is called upon to help prepare for potential impacts. Even in the best case scenarios, there is often very little warning (and sometimes no warning at all) prior to a disaster, so there is a serious need for efficient and effective geospatial systems to evacuate citizens and stage response resources.

Reminder - Complete all of the Lesson 3 tasks!

You have reached the end of Lesson 3! Double-check the to-do list on the Lesson 3 Overview page to make sure you have completed all of the activities listed there before you begin Lesson 4.

Overview

This contraflow map shows available evacuation routes for the New Orleans region during Hurricane emergencies. Newer interactive platforms (including those based on Google Crisis Response) provide evacuation details with a range of other near-real-time data, and in a format that is very familiar. The US ready.com website provides advice about the six "P's) of evacuation response.

Credit: Louisiana Department of Transportation and Development

We are shifting our focus now from vulnerability assessment and hazard mitigation to the next stage of emergency management, preparedness. One way you can think of this phase is that it involves activities to address shortcomings in planning aimed at reducing vulnerability and mitigating hazards. Preparedness is about what you need to be able to do when the worst happens - being ready to respond and promote recovery. 

In this lesson, you will read about ways in which geospatial analysis can be used to target intervention and evacuation efforts to reduce the impact of forecast disasters. You'll respond to one of the readings with a written critique. This week, the emerging theme discussion focuses on Humanitarian Logistics and Supply Chains. Finally, for your term project, you will develop a detailed outline to help guide your progress.

What You Will Learn

At the successful completion of Lesson 4, students should be able to:

• explain disaster preparedness and how it is supported by geospatial perspectives and technology;
• critically evaluate technical literature on geospatial analysis for emergency preparedness;
• evaluate and discuss disaster and humanitarian logistics and supply chains;
• complete an outline for your term project report.

What You Will Do

Lesson 4 is one week in length. To finish this lesson, you must complete the activities listed below. 

Please refer to the Course Calendar for specific due dates.

Questions? 

If you have questions about the content or lesson activities, please post them to the General Questions and Discussion forum in Canvas. While you are there, feel free to post your own responses if you, too, are able to help a classmate. If your question is of a personal nature, please email me directly through Canvas.

Credit: © Penn State University is licensed under CC BY-NC-SA 4.0

Preparedness

Actions taken prior to a disaster with the intent of ensuring a better event response

• Planning
• Training and Exercises
• Logistics
• Technology infrastructure
• Agency and stakeholder coordination
• Provide information and tools to citizens

An Ounce of Preparation...

...is worth a pound of cure, right? Often disaster situations do not present themselves with substantial warning. Some events, like earthquakes or terror attacks, occur with little or no advanced warning. Other events, like hurricanes or tsunamis, may allow for some substantial amount of time (ranging from an hour or two in the case of a tsunami to several days in the case of a hurricane) to prepare for the initial impact. No matter what the type of event, there are ways we can prepare by taking advantage of geospatial capabilities.

In lesson, we will explore geospatial enabled preparedness in several ways. On this page you will contrast different scenario-based activities - one focused on large scale disasters and another on a more localized emergency. Then you will consider some of the science behind forecasting and modeling potential emergencies, and the geospatial technologies that are being used to develop the capacity ahead of time for situation awareness when disasters do strike. Finally, you will once more contrast large and small scale preparedness activities and the role of geospatial data and analysis by looking at Humanitarian and Disaster Logistics and models for improving building evacuation. So the idea is to think about preparedness as a set of activities with multiple dimensions (spatial and temporal scales) and geospatial analysis as a key tool for managing this complexity.

Scenario-based Exercises

A highly regarded method for preparing for disasters involves the use of scenarios to conduct realistic exercises to simulate a crisis situation. Using the examples below, contrast live training exercises on small-scale (such as Active Attacker Situations) with those developed by FEMA for large-scale earthquake scenarios. For disasters that provide no advanced warning, using scenarios may be the only way to really prepare in advance. We'll go in-depth on designing scenarios later on in Lesson 7, but for now, read this short article from GovTech about how GIS can help communities prepare for disasters. How effective do you think these activities would be? Could the community be engaged more actively? How do you think things have changed since the GovTech essay?

FEMA Earthquake Preparedness Scenario

FEMA has developed a wide range of training exercises to aid in disaster preparedness and response. I'd like you to consider the following materials they developed for a catastrophic earthquake in Southern California. Here is their description of this resource.

Scenario for a Catastrophic Earthquake on the Newport-Inglewood Fault

GIS and other geospatial technologies can support a key element of disaster preparation through computational simulation and modeling. A wide array of specialized modeling software extensions for ArcGIS and other GIS platforms are available. This software enables users to tweak disaster parameters and simulate damage patterns due to storms, earthquakes, disease outbreaks, and fires (think back to InaSAFE from the previous lesson). With the rise of cloud computing, near-real-time data streams, and big data analytics, much of this happens at a fast pace including analysis well before the event up to the start of the event itself. For example, thinking about the preparations for Hurricane Florence and how often decisions on pre-deploying assets changed as new information became available to the managers. This will become clearer when we consider disaster and humanitarian logistics later in this lesson.

The output of these models can be viewed in static maps or interactive web tools. Some real-time modeling capabilities exist for emergency managers to test various parameters and visualize their potential impact, but few of these systems are available for free to the general public (very unfortunate!). The  Pacific Disaster Center  in Hawaii does quite a lot of work on modeling and visualizing model outputs for disaster scenarios. Have a closer look at this site and some of the tools and apps PDC offers, including the disaster preparedness training.

One publicly available resource is provided by the USGS in the form of their Prompt Assessment of Global Earthquakes for Response (PAGER) system. PAGER provides rapid reporting on the potential impacts of recent earthquakes on human life and structures in easy-to-consume reports and maps.

The USGS PAGER system provides reports within 30 minutes to estimate the impact of recent earthquakes around the world. These reports can be used by emergency managers in the immediate aftermath to begin making decisions.

Credit: FEMA

A rapidly growing part of preparedness is the development of geospatial tools, data analytics, and visualizations that can be put into place ahead of a disaster. This includes making sure existing datasets, like roads and other infrastructure, demographics, and critical facilities are ready to use. Increasingly, these efforts involve the use of real-time or near real-time information from data feeds including Internet of Things (IoT) devices, reports from field crews, streaming model outputs, and others. We will focus on this in greater detail in Lesson 5 and again later when we consider the emerging technology of IoT. This diverse range of information is often summarized using maps and emergency management dashboards. Below, we'll consider some interesting examples of these trends.

Let's start with something very familiar, Google Maps! While many sophisticated methods for modeling disaster impacts aren't yet publicly available in web tools, there are in fact a very large range of options for free platforms used to evaluate and monitor a situation in progress. The Pacific Disaster Center's Global Hazards Atlas, introduced on the previous page, is one such system. Google Crisis Response, also mentioned earlier, is another example and is more readily available and usable by the responders and the general public alike.

Google crisis map on 21 September 2018 showing the aftermath of Hurricane Florence. Note the up-to-date information on road closures and where new post-hurricane aerial imagery is now available.

Credit: Google Crisis Map

This next example is from the PDC Global Hazard Atlas and shows the position and projected path of a tropical cyclone bearing down on Japan. Note that as with the Google map, there are a lot of other layers that can be examined to gauge likely impact and help make decisions about where resources might need to be pre-positioned. Another way this data can be used is for future planning and mapping of disaster prone areas (think back to the FEMA Southern California Earthquake example). Finally, and you will see this more in the following video, these maps can help emergency managers evaluate the potential for disasters to interact. For example, some areas may be vulnerable to a cyclone and may also have a critical facility like a power station. GIS 101 but very powerful nonetheless.

Finally, check out the impressive Nationwide Operational Assessment of Hazards (NOAH) program from the Philippines. This is a good example of the trend toward multi-hazard approaches to emergency management, rather than focusing on a single hazard type. This site has a lot of functionality including the ability to map the likely impact of different hazards based on historical data. After viewing this short video, take some time to click on a few of the buttons and see what you can learn. For example, display volcano hazards alongside critical facilities to see if there are places particularly at risk.

Video: How Project NOAH helped avert potential disasters (2:14 minutes)

For further information

For more on NOAH, have a look at this journal article: Disseminating near-real-time hazards information and flood maps in the Philippines through Web-GIS. This link takes you to the abstract. To see the entire document, see e-Reserves under Library Resources in Canvas.

The readings this week continue our focus on preparedness. You will read a chapter in your textbook that covers some of the broader issues around GIS and disaster preparedness, continuing some of the themes we've been covering. Next, you will consider a journal article that takes a (very) deep dive into emergency building evacuation modeling. This paper is challenging but has a lot of useful information even if the technical bits are too much!

I like to remind students that, as you read, it is important to read critically and not necessarily accept what you read at face value, even if it appears in a peer-reviewed journal. Many of the course assignments are aimed at helping you build the skills to assess published reports on geospatial technology objectively and critically. There are multiple perspectives from which to critically assess what you read. No papers can cover all issues and no author is all-knowing; thus, it is likely that you know something relevant that the author does not (or that he/she did not consider relevant, but that is relevant from your perspective). Methods of data processing and analysis that might be acceptable in one discipline may be at odds with established methods in another discipline, so you will find disagreement among authors about what methods are “right.” People make mistakes (in their original conceptualization of a problem, in carrying out work, and in interpreting the results) – and your practical experience and/or solid grounding in geospatial analysis may give you special insight to identify these mistakes. In many cases, the authors may have limited practical knowledge, thus, they may completely ignore issues that are critical in a real world context.

1. READ

From "GIS for Disaster Management": Chapter 6 - "Geographic Information Systems and Disaster Planning and Preparedness". See Library Resources in Canvas for the electronic version.

These chapters focuses on the various ways preparation can be characterized in the context of GIS, as well as some of the key methods by which geospatial tools can be used to support near-term preparation when we know a disaster is about to strike.

2. READ

Bo Li and Ali Mostafavi 2022. Location intelligence reveals the extent, timing, and spatial variation of hurricane preparedness. Scientific Reports 12:16121.

This paper examines preparedness for hurricanes based on geospatial data and anlaysis

For this week’s Emerging Theme topic, we are going to take a step back from emergency management and focus on spatial data science (SDS) in general. I want to emphasize that SDS (and terms like Big Data or Machine Learning) can mean several different things.

On the one hand, it is how we talk about GIS and geospatial science in the age of large data sets (e.g., imagery and otherwise), enhanced computing power, and networked data and services. A lot of traditional GIS workflows are described in (spatial) data science terms. For example, variants of regression analysis and hotspot analysis are referred to as machine learning and cluster detection, respectively. This is all fine, but SDS is also the integration of big data, high performance computing, and programming of machine learning/AI algorithms to conduct analysis in some fundamentally different ways from traditional GIS/geospatial analysis. You will explore and discuss some this complexity in this Emerging Theme Discussion. 

To set the stage, I'd like you to have a look at few perspectives on spatial data science, and where it is heading, from two geospatial industry leaders, Esri and Carto, and university researchers at the Center for Spatial Data Science at the University of Chicago. 

What is Spatial Data Science? 

What is Spatial Data Science (6:08)

When considering SDS as a set of activities, we can identify several interrelated parts. These are listed here with some examples of common associated tasks (not exhaustive):

• Data ingestion, cleaning and management
  • Obtain data, formatting, cleaning, and management in database system
• Exploratory data analysis
  • Statistical methods for data reduction, data visualization
• Data enrichment
  • Data linkage, spatially enabling data, calculate new variables
• Spatial analysis
  • Mapping, hot spot analysis, space-time analysis, overlays and spatial queries
• Machine Learning
  • Cluster analysis, regression, predictive analytic, object recognition
• Big Data Analytics
  • Big data, (near) real-time
• Visualization and Communication
  • Maps, graphics, interactive, web, Tableau/Qlik/BA

Visit Carto's Technology Stack Overview page to see a similar list. Take note of the Data ingestion and Management & Analysis steps. Are you familiar with the technologies listed there? Pick a couple e.g., PostGIS, Python SDK, ELT, PostgresSQL that you are not familiar with and look them up. Gaining a general familiarity with the various parts of SDS is a good first step.

Finally, Carto have produced a useful free e-book on Becoming a Spatial Data Scientist (download the PDF here). Read the first chapter and have quick look at the rest of the book. This may be a good resource for you going forward as it lists many of the tools you can use for analytics projects. 

You are probably aware that the dominant player in the GIS space is Esri, the developer of ArcGIS Pro amongst many other offerings. In addition to desktop software, they offer server and cloud based services that allow for big data analytics at scale.  

Visit the Esri Spatial Analysis and Data Science page. Note the components of SDS they outline and a few of the tools on offer. I'd like you to take a closer Machine Learning and AI & Big Data Analytics. 

Machine Learning and AI

Artificial Intelligence is a somewhat generic term for a class of techniques including machine learning and deep learning. On a basic level, AI is all about developing algorithms that can "learn", or can be "trained", to recognize patterns in datasets and then predict likely behavior. For example, algorithms have been written to identify and differentiate sharks from swimmers in real-time UAV camera feeds over beaches in Australia. Post hurricane damage assessment is also commonly done by AI these days, often with the help of volunteers training the algorithms e.g., looking at single buildings and decided on a damage class.

Read this short article on Machine Learning in ArcGIS by Esri Spatial Analyst Lauren Bennent. What are some of the key issues she cites about using ML and GIS? What stands out as being different from what you can do with Desktop GIS alone? Do you think you can get started with ML using ArcGIS Pro? What constraints might you run up against?   

Big data analytics

One way SDS is different from traditional GIS workflows is the ability to deal with large volumes of data including collection and cleaning, storage, analysis and visualization. Analysis of real-time (or near real-time) data is a rapidly growing area for geospatial science and emergency management applications in particular. Have a look at the following video and Esri's Powerful Analytics Using Spatial Data Science website to see a geo-analytics workflow using Esri.   

Real-Time GIS and Analytics (5:42)

Center for Spatial Data Science

The geospatial industry are making great advances in SDS and delivering data and tools to a wide audience, however research groups at universities have been at the cutting edge of developments in (spatial) data science for many years. This includes work in computer science, high performance computing, mathematics, statistics, geography, human-computer interaction, amongst others.

One research group that has been very influential across these areas is Professor Luc Anselin's Center for Spatial Data Science at the University of Chicago. Have a look at a few of the research projects this center has undertaken in recent years. What similarities or differences do you see compared to the problems described in the Carto or Esri sites, or that you have usually thought about in the context of GIS problems?

One of this group's most widely used products is the GeoDA software. This program has a lot of basic GIS functionality but is also loaded with easy to use advanced spatial analysis tools. This is a desktop application, but many of the tools can be used by coding with Python and R, thus making the tools scalable with data and hardware needs. 

Look at the GeoDA pages and also visit their github site which hosts software and training materials. Be sure to scroll down this page to view the desktop spatial analysis program GeoDA. As mentioned, they are also actively developing R libraries. Why would they focus on both? 

Note that you can download and use GeoDA for free (and it works on multiple platforms). It might be worth considering as part of your projects?

Data Science Computing

As mentioned previously, SDS goes beyond desktop GIS and requires the use of a range of computing resources and programming tools to manage different analysis steps.

What about the hardware required for Spatial Data Science. In many ways it is all about scalability. You may be able to accomplish many tasks with desktop software like ArcGIS Pro, but for bigger and more complex analysis you may need to rely on enterprise solutions or high performance computing.

Have a very quick look at this fact sheet for the NVIDIA A100 Tensor Core GPU. This type of hardware is designed for for AI, data analytics and high performance computing in server/cloud applications. 

Hardware like this is used in distributed computing where tasks to be split up and conquered by a stack or cluster of processors. The figure below is from the Riga Technical University and shows how a central computer (head node) is orchestrates analysis jobs undertaken by computing nodes.

Distributed computing is controlled by software systems such as Hadoop. Here is a description from the developers website of what Hadoop does:

Data Science Software and Programming

I'd like to end this section by showing you a useful diagram produced by Carto (again!). It is meant to show the relationships amongst data science tools and geospatial analysis. 

Python and R are the main languages used for data manipulation and analysis in much of SDS. The two languages overlap in functionalist but also offer different capabilities (R is good for some things / Python excels at others). This highlights that you need to be somewhat pragmatic and use whatever tool will work best. The tools hanging off the R and Python circles refer to specific packages e.g., ArcPy is the site package used by Esri for accessing ArcGIS functionality. SQL is the main language for querying and managing databases. Finally, the platforms area refers to the many ways you can interact with the data and run analyses. Are you familiar with any of these? The Carto book recommended above provides some practical help on how to set some of these up for your own analysis.  

Additional Resources

We will come back to the topics of GeoAI and real-time analytics later in the course, but in the meantime Esri and Carto offer many free resources on SDS (some listed above) and this includes free seminars and training materials. Have a look at this page listing current resources and upcoming events - Spatial Data Science Events, Videos, Webinars and Courses.

The growing interest in spatial data science has spawned several conferences that bring together scientists and analysts in the public and private sectors. I encourage you to take a look at the Spatial Data Science Conference website. You can register and attend online for free this year. 

Deliverable

1. Post a comment in the Emerging Theme Discussion (L4) forum that describes similarities and differences between traditional desktop GIS and Spatial Data Science. How you think spatial data science is changing or will change crisis and emergency management approaches?
2. Provide a link and short description to a VGI effort ‘in the news’ or that you have otherwise come across.
3. NOTE: Respond to this assignment in the Emerging Theme Discussion (L4) forum by the date indicated on the course calendar.

Grading Criteria

This discussion will be graded out of 15 points.

Please see the Discussion Expectations and Grading page under the Orientation and Course Resources module for details.

This week, you need to compile and submit an outline for your term project paper. By now, you've received my feedback on your project abstract, and you had time last week to collect some background information.

Outline Description

A good outline will help you complete your term project as efficiently as possible. I like working with an outline, because then I know the gaps that I need to fill. It's also an excellent way of narrowing what your paper will cover given a specific word count constraint.

Your outline should include:

• major sections and subsections of your paper;
• organized sections in a logical flow that guide the reader from start to finish;
• some details about the dataset and analysis you plan to use including where you plan to source data if you haven’t already (now is a good time for me to help out if you are having any problems).

The outline should reflect the limitations you have on word count (no more than 3000 words) for the final product (you won't be able to have dozens of sections covering every possible topic).

I like to add short statements for the key ideas I will cover in each subsection; that way I know exactly what I must cover to complete the paper, but I'll leave it up to you to decide how much detail your outline includes beyond section and subsection headings.

For your term project, you must include the sections/headings provided in the table below. These are the major items I will be looking for. You can create subheadings as you see fit. 

The content of this announcement will not be visible to users until Mar 8 at 0:00

Submission Instructions

Submit your assignment as a word document or PDF to the Term Project: Outline dropbox in Canvas. 

Save your files in the following format: L4_tp_firstinitialLastName.doc.

See our Canvas Course Calendar for specific due dates.

Grading Criteria

The goal of this exercise is to pave the way for you to write an exemplary term project; therefore, each section will be graded on a satisfactory (1 point)/unsatisfactory (0 points) basis. You need to address the following criteria:

• a title is present that reflects the focus of the project,
• clear headings and subheadings are present for each paragraph,
• appropriate and high-quality datasets for your project have been identified,
• a plan for locating and acquiring the data has been determined (and instructor consulted if having problems),
• a clear and detailed plan for analyzing the data has been given.

The outline is worth 5% of your total course grade and will be graded out of 45 points.

The ability to synthesize technical information into a concise package that is appropriate for a broad audience is a skill that is hard to hone and yet highly sought after in the workplace. This assignment provides you an opportunity to do just that. I would like you to create a short (5 - 7 minute) recorded presentation about your term project proposal. The presentation will be shared with your classmates.

Guidelines for your video

• Must be no longer than 5-7 minutes (no exceptions!).
• Outline the topic you chose, brief background, and key contributions of your work.
• Create a slide presentation that includes key points, graphics, photos, etc. to explain the project.
  • Avoid lots of text (and reading your slides) if you can make the same points with a graphic. You want the audience to focus on what you are saying and not on reading the slide!
  • Do not go into extreme detail in five minutes - the idea here is to provide a quick teaser of your work that will entice someone to read your final report.
  • Be creative!

Make Your Video

1. You may choose your own screen recording software, or record your screencast from within Canvas. Here is a link to instructions on how to use Kaltura Capture to record within Canvas. Note: Kaltura Capture is accessed in Canvas by clicking on My Media in the Canvas menu and "Add new". If you do not use Kaltura Capture, you will need to upload your own video file to My Media using these instructions.
2. Record your screen while you give your five to seven-minute slideshow (make sure the slides are visible and the audio is clear - using a headset microphone is normally the best way to ensure decent audio quality).
3. Need more help? Contact the World Campus Helpdesk for assistance.
4. Make sure that you have added your screencast video to My Media in Canvas.

Add Your Video to the Media Gallery

You're almost done! The last step is to add your video to our Term Project Presentation gallery so everyone can see!

1. Click the Media Gallery link in the course navigation on the left side of the page.

2. Click the + Add Media button in the upper right of the page.

3. Select the video you would like to add by checking the checkbox to the left of the video.

4. Click Publish in the upper right of the page.

5. Let me know you've uploaded your video, and I'll approve it for the Media Gallery.

NOTE: The video will not appear in the Media Gallery until I approve it.

Review your peers' presentations

Go to the Media Gallery in Canvas and view your peers' presentations. Please provide comments and feedback to your peers.

Deliverables

• Share your video in the Media Gallery.

The chapter from your book is matched with a journal paper that focused on GIS for emergency management situations that include preparedness components. Your written deliverable for this week’s lesson (beyond what you wrote for the class participation section) is to produce a brief (no more than 400 words) critical assessment of the paper by Lochhead and Hedley. The critical assessment should begin with a one-two sentence summary of the authors’ goals in the project reported. Then, in 2-4 paragraphs, discuss the strengths and weaknesses of the work reported. Consider the following issues:

• the most important contribution that the paper makes to understanding the role of geospatial data and approaches in emergency management (what do we know now that we did not know before this work?);
• critical aspects of the methods applied and/or decisions made about those methods that make the work something that others should emulate (e.g., things that they considered that, if they had been ignored, would make the conclusions unreliable or invalid);
• flaws that you see in the work reported (these might be in methods developed, in the way they were applied, or in the interpretations that the authors make about the applicability of their results).

Submission Instructions

Please name your document using the following as an example: L4_assign1_firstinitialLastName.doc 

Submit your assignment to the Lesson 4 Writing Assignment (L4) Dropbox. See the Course Calendar for specific due dates.

Grading Criteria

For this assignment, I will assign grades with the following rubric. It is worth 4% of your total course grade and will be graded out of 20 points.

Summary

This week, we focused on how GIS can be used to prepare for a disaster. Different disasters present different types of opportunities for preparation - some, like terror attacks or earthquakes, provide little or no warning time at all. Others, like hurricanes or other severe storms, may offer a window of opportunity where geospatial data and tools can be used to coordinate evacuations and other types of preparation efforts (sandbagging levees, for example).

One way to prepare for disasters that offer little or no warning is to develop spatial computational models of disaster impacts and use a GIS to run simulations of hypothetical emergency situations. In this lesson, we looked at how the USGS uses PAGER to quickly estimate damage from earthquakes. When planning a geospatial system for emergency management, it may be very useful to allocate time and resources toward disaster modeling efforts to simulate situations that present very little advanced warning.

In the next lesson, we will shift our attention to the response phase of emergency management. In the time immediately following a disaster, GIS and other geospatial technologies will be called upon to develop a situational picture and to allocate first responder resources. In Lesson 5, we will delve into a wide variety of challenges that are associated with disaster response.

Reminder - Complete all of the Lesson 4 tasks!

You have reached the end of Lesson 4! Double-check the to-do list on the Lesson 4 Overview page to make sure you have completed all of the activities listed there before you begin Lesson 5.

Questions?

If you have any questions, please post to the Canvas Discussion Forum called "General Questions" or email the instructor via Canvas conversations (if the question is personal in nature).

In this lesson, we will focus on how geospatial perspectives and technology are used in response to emergency situations. Geospatial analysis has tremendous potential for aiding disaster response, but as you will learn, it is not easy to quickly translate geospatial data into actionable information when lives are at stake. Responders need to know where to go and how to get there, and emergency managers need to understand and react to a changing situational picture.

Response

Actions taken immediately before, during and after an event to alleviate suffering and prepare for recovery

• Establish Situational Awareness
• Evacuations and Shelters
• Respond to remaining hazard
• Search and Rescue
• Mass Care
• Logistics response
• Initiate Recovery

What You Will Learn

By the successful completion of this lesson, you should be able to:

• identify the roles that geospatial approaches and technologies can play in disaster response;
• discuss some of the issues that geospatial analysis systems must overcome in response situations with your colleagues;
• understand the implications of real-time mapping and spatial analytics;
• create real-time mapping and spatial analytics dashboards.

What You Will Do

Lesson 5 is one week in length. To finish this lesson, you must complete the activities listed below.

Please refer to the Course Calendar for specific due dates.

Questions? 

If you have questions about the content or lesson activities, please post them to the General Questions and Discussion forum in Canvas. While you are there, feel free to post your own responses if you, too, are able to help a classmate. If your question is of a personal nature, please email me directly through Canvas.

When Disaster Strikes, What's Next?

In the wake of a serious disaster, geospatial analysts along with other emergency managers are expected to provide a wide array of information with short deadlines for a variety of important tasks. First, it is essential for everyone involved to have a clear sense of the current situation (situation awareness) and to receive updates on the situational picture as time progresses. This can be a serious challenge because often a disaster can impact the types of data that are available. Also, consider the extreme case of the EOC for New York on 9/11 which was located at 7 World Trade Center, and its state-of-the-art equipment and data were destroyed as a result of the attacks.

Any geospatial plan for responding to an emergency or crisis should consider several key questions:

• Are there backup sources for equipment and data?
• Is there an alternate site where personnel can gather in the event that the primary EOC is taken out by the disaster?
• What are the basic geospatial-dependent products you must be able to provide to support fundamental response efforts?
• What are the plans for dealing with power and communication (Internet) outages, especially when current and emerging geospatial applications are dependent on these?

Even contemporary web-based geospatial systems present possible challenges in a real crisis situation. While cloud-hosted solutions can help avoid the risks associated with data storage in a single EOC, many disasters make Internet access difficult or impossible. We will consider this issue in more detail later.

Who Needs Help, And Where is the Help?

The most pressing need facing geospatial managers during the immediate aftermath of a disaster is to estimate the impact of the disaster on the local population to determine where first responders should focus their rescue efforts. This problem requires an awareness of the scale and scope of the disaster as well as the ability to know where response resources are located, what their capabilities are, and what routes are available for them to take to those who need their help.

As an example, consider the May 22, 2011 tornado that went through Joplin, Missouri. The map above shows locations of key facilities and estimated building damage levels. Developing an understanding of the scope of damage during and immediately following an event is a key goal for geospatial analysis. Spatial data on the location and functions of key facilities can be developed as part of mitigation and preparedness.

Later in this lesson, we will consider these issues in greater detail when we look at (near) real-time mapping and spatial analytics. The data and tools to support emergency management are changing rapidly and are much more advanced than they were just a few years ago.

On the next page, you'll find your reading assignment for this week, where we'll delve deeper into how GIS and other spatial tools are used during response activities, including a focus on the limitations of GIS systems in response situations.

The readings for this week focus on the fourth component of emergency management, response. You will read an overview chapter from your textbook, review a situation awareness briefing from FEMA during Hurricane Maria, and a book chapter on emergency management communications technology.

1. READ

"GIS for Disaster Management" - Chapter 7 - "Disaster Management and Geographic Information Systems"

Previous readings have focused on how GIS can be used to avoid disasters, mitigate the consequences of events that may happen in the future, and prepare (in those cases where there is warning) for a disastrous event that is likely to happen (e.g., a hurricane that exists and has a predicted track and severity). These chapters focuses on how GIS can help in situations where an emergency/crisis is unfolding and shows how a well-reasoned, timely response can make a difference in the consequences of a disaster. Have a look at the entire chapter but focus on pages 192 - 203 – Geographical Aspects of Situational Awareness.

2. REVIEW

Situation awareness described in FEMA Geospatial Coordination Updates on two days during Hurricane Maria. The PDF's are located in Module 5 of Canvas.

• Wednesday, September 20, 2017
• Sunday, September 24, 2017

These slide decks supported one of the daily coordination briefings that FEMA ran in the days up to and following Hurricane Maria. They provide a nice summary of what different FEMA teams and allied agencies are doing. It is meant to provide an overall summary of the current situation. Contrast these "hard copy" products with newer web based tools in the FEMA Geospatial Resource Center.

3. READ

Norris, C. 2018. Chapter 2 - Computer Networks and Emergency Management from Technology and Emergency Management found in Module 5 of Canvas.

Finally, I’d like you to think a bit more about communication systems during disasters. This book chapter provides some interesting, albeit a bit basic, information on communication systems and then describes some of the ways they are impacted by disasters and how they can be restored during a disaster. It is good background given how much geospatial technologies depend on reliable ICT.

You might also be interested in this late 2017 news article on What Happens to the Internet After a Disaster?

Deliverable

1. Post a comment in the Reading Discussion (L5) forum that addresses the RESPOND prompt above during the first 5 days of the lesson.
2. Then, I'd like you to offer additional insights, critiques, a counter-example, or something else constructive in response to your colleagues on two of the following 5 days.
3. Brownie points for linking to other technology demos, pictures, blog posts, etc., that you've found to enrich your posts.
   NOTE: Respond to this assignment in the Reading Discussion (L5) forum by the date indicated on the course calendar.

Grading Criteria

This discussion will be graded out of 15 points.

Please see the Discussion Expectations and Grading page under the Orientation and Course Resources module for details.

Overview

This week’s emerging theme focuses on the topic of looking at disasters and maintaining situation awareness in (near) real time. To complete this section, you will need to:

• review a short video and reading to get you started;
• use ArcGIS Online to create your own emergency response dashboard;
• identify and add live data feeds to your dashboard;
• conduct analysis to develop situation awareness that can be used to target response resources; and
• write a short report summarizing your work and findings.

Real-Time Mapping and Spatial Analytics

For this exercise, we are going to focus primarily on the Solutions for Emergency Management apps that have been developed by Esri and are based on their suite of ArcGIS technologies, especially cloud and web-based GIS services. Also, see Esri’s Disaster Response Program website for the help the company offers during emergencies. There are other systems out there, some that leverage major industry platforms and some that are developed in-house from open-source software (e.g., recall InaSAFE, PDC, and even Google Crisis Response).

Regardless of the system being used, they have similar goals such as providing:

• base maps and other datasets that can be prepared beforehand and deployed during an event, e.g., road networks, building footprints;
• infrastructure for communicating with a range of stakeholders from local first responders, EOCs, specialists working at a distance, and the general public;
• a means to upload data, including real-time, from the field and other sources;
• rapid analysis and then uploading and sharing derived products, e.g., spatial data analytics, rapid image processing for damage assessment; and
• visualize diverse datasets in an easy to update and understandable format, e.g., multiple map displays on a dashboard with other charts, figures, and video feeds.

Before developing your own situation awareness app, have a look at the two videos and the optional reading below. The first (short) video is an overview of a case study where these approaches are used by the California Office of Emergency Services (Cal OES). The second (longer) video provides more detailed examples about incorporating live data feeds into a situational awareness app and dashboard using Esri tools. These concepts are further discussed in the optional reading from The ArcGIS Book.

ArcGIS Online Case Study: Emergency Management – Cal OES (3:54 minutes)

Leveraging Live Feeds for Situational Awareness (55:39 minutes)

I know this is a long video. If you don't have time to watch the entire video, please have a look at the first 10-15 minutes or so.

The next page will provide you with the details of the Exercise and writing assignment that are due this week.

For the analysis part of this exercise, you will consider the applications of (near) real-time geospatial tools for emergency management in greater detail. You should critically evaluate what is already out there and what is required for an effective decision support system utilizing dynamic and real-time spatial data. Once again, you are assuming the role of a geospatial analyst that is planning for and responding to emergency situations.

Steps to Follow

1. Start by evaluating some near-real time systems used by different emergency management agencies. We have looked at some examples already, but you should have a search of applications on the web. I can provide some pointers if you are having trouble finding suitable examples.
2. From this, and the other material in this week’s lesson, you should come up with a needs assessment/system design for a hazard and location of your choosing e.g., wildfires in California, inland flooding in Queensland. In other words, what functionality should the tool have and what data is required.
3. Finally, build a simple prototype with ArcGIS Online tools. You should be able to find some data feeds, but there may or may not be much traffic on them if there isn’t a current emergency. That’s OK the idea is to have a simple prototype that has the essential static and dynamic data elements needed when an emergency occurs. You don’t have to find data for everything or address everything from Step 2. 

Deliverables

1. Report your findings by writing a short 400 word essay on your critique of existing systems and your design advice. Please include a minimum of two figures (screen-grabs with captions will be OK) illustrating the points you raise.
2. Create a simple app/dashboard with ArcGIS Online and share with me (and the class). Please include a link to your app at the TOP of the document. 

Submission Instructions

• Submit a link to your app and your written assignment to the Deliverable: Real-time Mapping and Spatial Analytics Exercise Dropbox (L5).
• Post a link to your app with a 2-3 sentence description of what you focused on to the Deliverable: Real-time Mapping App Discussion so that your classmates can see what you have done.
• Review and provide constructive encouragement and feedback on your peer's apps.
• See the Course Calendar for specific due dates.

Grading Criteria

This assignment is worth 50 points toward the exercise portion of your course grade.

This assignment will be grading using the following rubric.

Make Progress On Your First Draft

This week, you should be making significant progress on the first draft of your term project. Your goal should be to make the first draft as high quality as possible, with the idea that doing so will mean you have less work ahead of you to complete your second (and final) draft.

I have designed the timing of this assignment so that I have time to read your full drafts, offer feedback and editing suggestions, and return them to you with enough time left in the course so you can revise your work before submitting a final version.

Expectations

Here are my expectations for your first draft:

• It should be clear who you are writing for and the role you are playing in preparing this report.
• Your draft should be complete, and the topics from your abstract and outline should be covered.
• I understand you may still be working on some of the data analysis and visualization, so I will put a greater emphasis on the rest of the draft. That said, the logic of your analysis should be clear and there should be good progress towards completing your analysis.
• It should be well written using correct grammar and spelling.
• Your draft should not exceed the 3000-word limit (citations and figure captions do not count toward the word limit). A more detailed version of your methodology can be provided in an appendix, and this doesn't count towards your word limit.
• The format of your document should be consistent and elegant.
• You should use a common citation format and apply it consistently. If you don't know which one to use, Chicago Author-Date style is a good default. Refer to the Writing Resources Page for more detials and advice. 

Rubric

This week, you should complete at least the first half of your term project draft. You will have all of this week and next week to complete your first draft, and since you have other assignments in this course, I recommend you manage your time accordingly.

If you're like me and you have trouble getting started on writing assignments, consider this piece of advice I heard from a colleague about completing a Ph.D. dissertation:

"Every day, set aside a writing task for yourself that is so small that you cannot possibly fail to complete it."

When I was writing my dissertation, I set little goals for myself every day that mirrored this advice. For me, it worked best to set a specific word count that I had to achieve every day. For you, there may be better ways to motivate yourself, so your mileage may vary.

Questions?

Remember, if you have any questions while you are working on your first draft, just send me an email or leave a post on the Questions and Comments Discussion in Canvas.

Summary

Effective response to a disaster depends on quickly synthesizing actionable information and disseminating that information to responders in the field. Geospatial data systems and analyses are frequently used to assemble the "big picture" in a disaster. Among other things, it is essential for geospatial systems to help decision makers understand where first responder resources are located and where help is needed.

This week, we also focused attention on another challenge for geospatial systems in response situations. Quite often, a significant disaster will destroy the infrastructure that had been designed to support emergency management. For example, we learned about how an ad hoc system was developed in New York after 9/11. One way of avoiding this kind of problem is to distribute the emergency management geospatial system through a local network or via the Internet where it can be accessed from multiple entry points. This type of approach makes it less important that all emergency management personnel are in the same place.

Up to this point, we have covered mitigation, preparedness, and response topics for emergency management GIS. In the next lesson, we will move on to the final stage of emergency management and explore how geospatial data and analysis is used in longer-term recovery efforts to rebuild disaster areas.

Reminder - Complete all of the Lesson 5 tasks!

You have reached the end of Lesson 5! Double-check the to-do list on the Lesson 5 Overview page to make sure you have completed all of the activities listed there before you begin Lesson 6.

Snapshot of a map made by USA Today shortly after the event to reveal the long-term efforts necessary for New Jersey to recover from Superstorm Sandy in 2012.

Credit: N.J. Department of Insurance, Census Bureau, USA TODAY research

Overview

This week, we will focus on how geospatial approaches and technologies can support the final phase of emergency management - recovery. After response efforts have ended, recovery efforts can begin in earnest. GIS and related geospatial tools can be used to plan near-term infrastructure repairs and to identify candidate organizations and communities to receive long-term aid and assistance through grants and infrastructure projects. Recovery projects frequently involve close interaction with disaster victims who want to rebuild and return to 'life as usual." This poses challenges and opportunities for geospatial practitioners and those who consume information from geospatial analyses. We will discuss these topics and others throughout this lesson.

Credit: © Penn State University is licensed under >CC BY-NC-SA 4.0

Recovery

The rebuilding or improvement of disaster-affected areas

• Debris Management
• Return essential services
• Food and water
• Temporary housing
• Economic assistance
• Insurance claims and rebuilding
• Business aid

What You Will Learn

By the successful completion of this lesson, you should be able to:

• explain and compare multiple ways in which geospatial analysis can be applied to disaster recovery efforts;
• identify strengths and weaknesses in current geospatial approaches to disaster recovery;
• evaluate, describe, and discuss trends and advances in cloud and mobile computing and how they are impacting geospatial systems for emergency management;
• develop a solid first draft of your term project.

What You Will Do

Lesson 6 is one week in length. To finish this lesson, you must complete the activities listed below.

Please refer to the Course Calendar for specific due dates.

Questions?

If you have questions about the content or lesson activities, please post them to the General Questions and Discussion forum in Canvas. While you are there, feel free to post your own responses if you, too, are able to help a classmate. If your question is of a personal nature, please email me directly through Canvas.

Stages of Disaster Recovery

Recovery is a difficult process and involves the coordination of a range of actors with different levels of decision-making power and resources. This is illustrated by the US Federal Emergency Management Agency’s National Disaster Recovery Framework (NDRF) which seeks to address and find a way to operate given this complexity:

The National Disaster Recovery Framework is a guide that enables effective recovery support to disaster-impacted States, Tribes, Territorial and local jurisdictions. It provides a flexible structure that enables disaster recovery managers to operate in a unified and collaborative manner. It also focuses on how best to restore, redevelop and revitalize the health, social, economic, natural and environmental fabric of the community and build a more resilient Nation.

The framework document includes some nice visualizations of disaster recovery as a process that plays out over time (and space!). Take a moment to consider this diagram and the listed examples of activities in the short, intermediate, and long term. Who are some of the actors responsible for undertaking these activities? Where do spatial data and analysis come in?

Stages of Disaster Recovery described in the FEMA National Disaster Recovery Framework (NDRF)

Click here to see a text description.

Stages of Disaster Recovery described in the FEMA

This image shows that Preparedness happens before the disaster. Once the disaster hits, short-term recovery commences, followed by intermediate and long-term recovery. This is not a strictly linear progression as one phase begins before the previous one's end. See the lists below for examples.

Preparedness (Pre-disaster Preparedness) is ongoing. Some examples include:

• Pre-disaster recovery planning
• Mitigation planning and implementation
• Community capacity and resilience building
• Conducting disaster preparedness exercises
• Partnership building
• Articulating protocols in disaster plans for services to meet the emotional and health care needs of adults and children

Short-Term Recovery (days after the disaster)

• Mass Care/Sheltering: Provide accessible interim housing solutions
• Debris: Clear primary transportation routes
• Business
  • Establish temporary or interim infrastructure to support business re-openings
  • Reestablish cash flow
• Emotional/Psychological: Identify adults and children who benefit from counseling or behavioral health services and begin treatment
• Public Health and Health Care: Provide emergency and temporary medical care and establish appropriate surveillance protocols
• Mitigation Activities: Assess and understand risks and vulnerabilities

Intermediate Recovery (weeks to months after the disaster)

• Housing: Provide accessible interim housing solutions
• Debris/Infrastructure
  • Initiate debris removal
  • Plan immediate infrastructure repair and restoration
• Business
  • Support reestablishment of businesses where appropriate
  • Support the establishment of business recovery one-stop centers.
• Emotional/Psychological: Engage support networks for ongoing care
• Public Health and Health Care: Ensure continuity of care through temporary facilities
• Mitigation Activities: Inform community members of opportunities to build back stronger

Long-Term Recovery (months to years after the disaster)

• Housing: Develop permanent housing solutions
• Infrastructure: Rebuild infrastructure to meet future community needs
• Business
  • Implement economic revitalization strategies
  • Facilitate funding to business rebuilding
• Emotional/Psychological: Follow-up for ongoing counseling, behavioral health, and case management services
• Public Health Care and Health Care: Reestablishment of disrupted health care facilities
• Mitigation Activities: Implement mitigation strategies

Credit: FEMA

The next image, again from FEMA, seeks to illustrate how recovery efforts are related to one another but also play out differently in different contexts. For example, recovery in Puerto Rico from Hurricane Maria has, in many ways, been a slower process than what has happened over the last year in Texas and Florida. Resources can be stretched thin when so many events occur around the same time (Note that in addition to the hurricanes, there were also major wildfires in the Western USA occurring around the same time in 2017). Moreover, some places never fully recover as they are repeatedly subject to disaster events. We will explore the recovery process in the next section on Hurricane Sandy, and you will also consider a few case studies in later lessons on events in Nepal and Indonesia.

Disaster Recovery for Select Events in the United States during 2017. Overlapping disasters create unique challenges for recovery efforts.

Credit: FEMA presentation to Indiana Geographic Information Council in 2018

Black Summer in Australia

The 2019-20 Bushfire season was catastrophic for much of Australia and National Bushfire Recovery Agency was created to coordinate the recovery effort. Take some time to look at this site and think about the range of activities underway and who they are targeted for.

As we have seen, the boundary between response and recovery is a fuzzy one as is that between recovery and mitigation. As we have talked about earlier, it is useful to think of the stages of emergency/crisis management as a circle with each stage blending into the next. The roles of geospatial approaches and technologies can be conceptualized as occupying (often overlapping) positions along this circle.

This overlap in functions was never more apparent than with the 2012 Sandy Hurricane disaster hitting the eastern seaboard. In the midst of efforts to rescue people stranded by floodwaters, politicians and others began discussing how or whether to rebuild--opening what will probably be a long dialogue about the potential to rebuild in a way that is more resistant to similar events in the future and comparing the economic and other costs of this option with suggestions to not rebuild at all or to relocate parts of the city. Similarly, while repairs and rescue efforts continued, work began in some parts of the city to start on recovery – with spatial tasks ranging from figuring out where displaced individuals were, to assessing damage in regions of the city to determine whose insurance claims of disaster relief requests to process first, to re-establishing utilities, fixing roads, and other efforts to establish the infrastructure required to carry out whatever recovery efforts were decided upon.

Background on What Happened During Hurricane Sandy: Optional, but recommended!

This video, Inside the Megastorm (54:38 minutes), produced by PBS NOVA does a nice job of describing the storm and why it was so damaging. It also helps illustrate the many ways that spatial data analysis was used to aid in the response and immediate recovery. Note how different groups used geospatial data and analysis e.g, first responders, search and rescue, utilities, transportation. I know this is a long video, but it is worth a look, especially if you are not very familiar with what happened.

To get a sense for just how complex and challenging recovery can be, have a look at this report from the Guardian, Hurricane Sandy, five years later: 'No one was ready for what happened after' and contrast it with some of the materials on the FEMA site, Sandy Five Years Later. Do you notice a difference in tone and emphasis of these two sources? Unfortunately, there are pretty much always winners and losers during recovery efforts.

Critical Perspectives on Recovery

Finally, here are two critical perspectives on recovery I’d like you to pay close attention to. This essay, A Tale of Two Recoveries: 5 Lessons from Hurricanes Katrina and Sandy, is written by geographers Susan Cutter and Christophe Emrich of the Hazards and Vulnerability Research Institute at the University of South Carolina. Susan Cutter is an influential scholar working in this space, and you are likely to come across her research center’s work (in fact, consider having a quick search in Google Scholar and/or visit the HVRI website). The second article, As Storms Keep Coming - FEMA Spends Billions in ‘Cycle’ of Damage and Repair, also focuses on some important and difficult issues around recovery, in particular, the back-and-forth between disasters and recovery effort. This echoes some of the messages in the Cutter article, and I’d like you to think about how the 5 Lessons relate to this analysis of FEMA spending. Although the article focuses on FEMA, the story is much the same for other countries trying to manage the complexity of recovery efforts, and we will see this later in the Sulawesi earthquake and tsunami case study.

As we've seen, disasters have a highly variable impact spatially and temporally. There are also strong spatial differences in social, economic, and environmental characteristics that shape both impact and recovery. The map below illustrates this issue by mapping housing damage against median income for part of Long Island in the wake of Hurricane Sandy. This is probably not too surprising given what you learned in Lesson 3 about hazards and social vulnerability. You can really see this play out during a big event like Sandy. This map comes from a piece in The Conversation, Storms hit poorer people harder, from Superstorm Sandy to Hurricane Maria, by Professor Chris Sellers at Stony Brook University.

Superstorm Sandy caused more damage in lower-income parts of Long Island, which are more vulnerable to storms. See the full Conversation article.

Credit: Stony Brook University’s Center for the Study of Inequality, Social Justice and Policy, CC BY

For Further Consideration: Optional

The optional Business of Disaster video (54:47) continues to explore many of the themes around the complexities of disaster recovery. The video was produced by PBS FRONTLINE and NPR in 2017 and focuses specifically on the (ongoing) recovery from Hurricane Sandy.

Click on the image above to open the video in a new window.
Click here for a transcript of the Business of Disaster video as posted on the PBS/Frontline website.

Credit: PBS Frontline

What did you lose during Super Storm Sandy?

Credit: NPR

As you read the course materials and other resources this week, think about strategies that are needed to develop geospatial data and analysis as general capability through which governments and other organizations can address the full range of emergency management challenges. Consider, in particular, what strategies are needed to make the process of using GIS and related technologies to support each stage of emergency management seamless - so that it is practical for emergency management teams to move quickly from the planning to the recovery stage as an event happens and to move among response, recovery, and planning-mitigation tasks as needed.

Also consider one common constraint - quite often the provisioning given to GIS systems to support emergency management is focused on preparedness and response phases. It's a lot harder to convince people to invest in new systems to support long-term recovery efforts. As we continue to face many and nearly simultaneous disasters, investing in recovery this way may become more and more urgent.

Finally, much of what we have considered has focused on events impacting the USA in particular. Moving forward we will explore these issues in other places, including Nepal and Sulawesi, Indonesia. These are places with perhaps more limited resources and geospatial infrastructure and often involve the international community and organizations playing a much stronger role. So think critically about the role of geospatial analysis and what is essential versus what is in development and may roll out eventually. In terms of recovery, how does it play out in these different countries and who is leading recovery efforts?

The readings for this week focus on the final component of emergency management, recovery. You will read a chapter in your text and two papers that address different approaches for using spatial analysis to understand patterns of recovery after major disasters. They all touch on the challenges of using geospatial analysis to help communities and organizations cope with events having geographically distributed impacts. Such events can range from relatively localized chemical spills affecting a small drainage basin, through major events impacting hundreds of thousands of people and with substantial financial impacts (such as 9/11, the 2011 Japan Earthquake, or Hurricane Florence).

1. READ

Chapter 8 – Geographic Information Systems and Disaster Recovery from Geographic Information Systems (GIS) for Disaster Management

This chapter from your textbook provides another overview of how GIS is used in disaster recovery. Note how it contrasts how different types of events require different types of geospatial tools. It also provides some good descriptions of where GIS response could be improved and ways that a long-term recovery infrastructure could be promoted.

2. READ

Schumann et al. 2020. Wildfire recovery as a “hot moment” for creating fire-adapted communities. Internaional Journal of Disaster Risk Reduction 42:101354. (Available on next page in Canvas)

This paper pulls together many of the topics we have consdiered so far. The authors suggest that "the period following a destructive wildfire may provide a “hot moment” for community adaptation. Drawing from literature on natural hazard vulnerability, disaster recovery, and wildfire ecology, this paper proposes a linked social-ecological model of community recovery and adaptation after disaster".

Deliverable

• This week, you will be participating in a "live discussion" with some of your classmates and me! So, no written posts are required! The meeting will last one hour.
• We will focus on the journal articles, so come to the discussion with any points or questions you would like to raise.
• I will send out a Doodle poll so we can fined some times that will work for everyone. We will meet in small(ish) groups so everyone can participate.
• Note: You will also do a short writing assignment that will critique this article as well. This will give you a chance to reflect on what comes out of the live discussion.

Grading Criteria

This discussion will be graded out of 15 points - pretty easy this week! Just show up and share your thoughts.

This week’s emerging theme is focused on an age-old problem, how to get things from point A to point B. The importance of logistics and supply chains in emergency management cannot be overstated. It is a topic that intersects all phases of emergency management but is perhaps most important in the preparation stage. In this section, I’ll provide a bit of background, then you will look at a few videos, agency presentations, and short readings. We’ll end with a consideration of cutting-edge trends in the field that are having or have the potential for big impacts. Finally, you will take what you've learned into a discussion forum and bounce ideas off your classmates. I have also provided some links to optional reading if you want to learn more about this topic.

Background on Logistics and Supply Chains

We will begin with some quick background information about disaster and humanitarian logistics. The first video provides an overview description of what humanitarian logistics is all about. Then there are two videos that show what this looks like on the ground during some recent disasters. Finally, a news article explores what can go wrong if one part of the supply chain is disrupted - blue tarps!

Watch: The Logistics Cluster in 2:30 Minutes

For further reading (optional):

• Logistics Cluster Website
• Emergency Supply Chain Training Slides by World Food Programme. You can find the slides in Lesson 4 of Canvas.

Private Sector Response in Puerto Rico

Watch: Crowley and FEMA Accelerate Relief Aid to Puerto Rico (1:18 minutes)

Defense Logistics Agency Response to Maria and Sandy

Watch: Logistics On Location: Supporting Hurricane Maria (2:56 minutes)

When supply chains break down: Where are the blue tarps?

Read: Puerto Rico: urgently needed tarps delayed by failed $30m FEMA Contract from The Guardian

Geospatial Approaches

Next, let's consider some of the ways geospatial approaches are used in humanitarian logistics and supply chains. Start by reviewing what Esri is doing by watching the following short video, visiting and reviewing the Logistics Planning Website and trying out the Logistics Planning App. After you finish looking at these resources, contrast this work with what Google is doing in this space by looking at their Google Maps Platform: Transportation Website.

Esri Logistics Planning Tools

Watch: Watch this 3:33 minute demonstration video and then explore the live app on the Esri website

What's next with logistics?

We’ll end with a consideration of some of the cutting-edge trends in logistics R&D and practice that are having or have the potential for big impacts on humanitarian and disaster operations.

DHL is one of the major world logistics companies and they produce an annual tech trend assessment for their industry. I'd like you to consider how they characterize the current state of the art and how that is changing rapidly due to developments in technology and operational models. Start with the video and then move on to the report linked below.

Watch: DHL Data Analytics video (1:27 minutes)

This short video and industry report were developed by the commercial logistics company DHL. It provides some useful insights into where the industry is heading and how new technologies are shaking things up. When you watch this, think about what you read and watched previously and consider how these ideas may or may not match up, particularly in the emergency management context.

Review: Logistics Trend Radar Industry Report (also found in Lesson 4 of Canvas)

Deliverable

1. Post a comment in the Emerging Theme Discussion (L4) forum that addresses the following prompts:
   • Comment on a significant way you think commercial and disaster/humanitarian logistics differ.
   • How might one of the emerging trends in logistics benefit disaster/humanitarian logistics, e.g., Uberisation of logistics?
2. The initial post should be completed during the first 5 days of the lesson.
3. Then, I'd like you to offer additional insights, critiques, a counter-example, or something else constructive in response to your colleagues on three of the following 5 days.
4. Brownie points for linking to other technology demos, pictures, blog posts, etc., that you've found to enrich your posts.
   NOTE: Respond to this assignment in the Emerging Theme Discussion (L4) forum by the date indicated on the course calendar.

Grading Criteria

This discussion will be graded out of 15 points.

Please see the Discussion Expectations and Grading page under the Orientation and Course Resources module for details.

This week, you need to finish the first draft of your term project. Your goal should be to make the first draft as high quality as possible, with the idea that doing so will mean you have less work to complete the second (and final) draft.

I have designed the timing of this assignment so that I have time to read your full drafts, offer feedback and editing suggestions, and return them to you with enough time left in the course to revise your work before submitting a final version.

Here are my expectations for your first draft:

• It should be clear who you are writing for and the role you are playing in preparing this report.
• Your draft should be complete, and the topics from your abstract and outline should be covered.
• I understand you may still be working on some of the data analysis and visualization, so I will put a greater emphasis on the rest of the draft. That said, the logic of your analysis should be clear and there should be good progress towards completing your analysis.
• It should be well written using correct grammar and spelling.
• Your draft should not exceed the 3000-word limit (citations and figure captions do not count toward the word limit). A more detailed version of your methodology can be provided in an appendix, and this doesn't count towards your word limit.
• The format of your document should be consistent and elegant.
• You should use a common citation format and apply it consistently. If you don't know which one to use, Chicago Author-Date style is a good default.

Submission and Grading Criteria

Submit your assignment to the Lesson 6 Term Project First Draft dropbox. See the Course Calendar for specific due dates.

Rubric

The first draft of your term project is worth 10% of your final course grade and is graded out of 100 points. For this assignment, I will assign grades with the following rubric:

Summary

This week, we moved to the final phase of emergency management - recovery. Recovery from a disaster can take a very long time (many would argue that we are still working on the aftermath of Sandy, for example), and there are a wide range of roles that geospatial perspectives and technologies can play in the recovery process. For example, GIS and mapping may be called upon to identify areas for redevelopment projects or to recalibrate vulnerability models to help predict future disaster impacts.

Talk of recovery plans may begin quite early following a disaster. We learned that during Sandy there were efforts to begin talking about the rebuilding process during the response phase of the disaster. A key challenge that geospatial systems for emergency management must face will be rapidly changing priorities.

Now that we have identified and discussed all four stages of the emergency management process, we will shift focus in the next lesson toward the use of scenarios to plan geospatial systems for emergency management. You've had a bit of experience with these already in your vulnerability assessment work in Lesson 3. Scenarios can be incredibly useful tools to help predict what technology and capabilities a GIS system will need to have to handle all phases of emergency management.

Reminder - Complete all of the Lesson 6 tasks!

You have reached the end of Lesson 6! Double-check the to-do list on the Lesson 6 Overview page to make sure you have completed all of the activities listed there before you begin Lesson 7.

Members of the Logistics Cluster, World Food Programme GIS, and World Food Programme Emergency Preparedness conduct a preparedness and response tabletop exercise.

Credit: Logistics Cluster

In this lesson, we will rely on our new knowledge of geospatial perspectives and technology as it is used in the four stages of emergency management to develop scenarios that can be used to inform the design of new geospatial systems for emergency management. Scenarios are a key creative mechanism for evaluating system designs against the likely impacts and outcomes from a hypothetical disaster situation. You will learn about scenarios and then develop your own.

What You Will Learn

By the successful completion of this lesson, you should be able to:

• describe the key components of scenario design
• produce compelling scenarios that focus on the use of geospatial applications and technology during a hypothetical emergency event.
• explain and discuss why mapping social media is relevant to geospatial systems for emergency management

What You Will Do

Lesson 7 is one week in length. To finish this lesson, you must complete the activities listed below. 

Please refer to the Course Calendar for specific due dates.

Questions?

If you have questions about the content or lesson activities, please post them to the General Questions and Discussion forum in Canvas. While you are there, feel free to post your own responses if you, too, are able to help a classmate. If your question is of a personal nature, please email me directly through Canvas.

Besides researching previous disasters and geospatially-enabled emergency management technology, an excellent way to forecast what is needed in a future geospatial system is to develop scenarios. You've already had some experience with this in Lesson 3 where you explored potential disasters for Texas using the InaSAFE plugin for QGIS.

In a disaster management setting, scenarios are realistic stories that describe what would happen to people, infrastructure, and the natural environment with a given set of disaster conditions. Often, scenarios are developed as part of a hazard assessment process where they can be used to predict the possible effects on a place, given different types of hazard situations. Scenarios are also used to create training simulations to test preparedness measures and response plans. This latter purpose is particularly relevant for this class; we need to use scenarios to evaluate the extent to which our geospatial infrastructure and analytical capabilities will actually hold up during a disaster situation.

Note that in geospatial system design activities, scenarios can end up being quite formal in terms of their structure. For further reading on the essence of scenario-based design, check out Chapter 48 of The Human-Computer Interaction Handbook – NOTE: you don’t have to read all of this! Just have a quick look.

Disaster Scenario Examples

A great way to understand scenarios is to read a few yourself. The US Department of Homeland Security and FEMA have prepared many different scenarios and training materials that you can review. Please click on the "Emergency Planning Exercises For Your Organization" link on Emergency Planning Exercises page to see some examples. In particular, I would like to explore a few of these exercises. Please pay particular attention to the roles that participants play, the rules to follow, the scenario itself, and the prompts used to keep things moving. What are participants expected to do and get out of this? Focus on these (but feel free to explore others):

Critical Power Failure

“Developed by the Office of External Affairs and the FEMA's National Exercise Division, this exercise is based on a combination of U.S. communities experiencing critical power failure during a severe weather event. Designed to help the private sector identify ways to prepare for, respond to, and recover from such a disaster.”

Hurricane

“Prepare to respond to and recover from a Category 5 hurricane. Based on the National Planning Scenario for a major hurricane, this exercise was developed by the Office of External Affairs together with FEMA's National Exercise Division to prepare the private sector for catastrophic damage caused by major flooding, tornado, and other natural disasters.”

Chemical Accident

“Based on the National Planning Scenario for a chlorine tank explosion, this exercise is designed to help the private sector improve Organizational Continuity, Preparedness, and Resiliency in the event of an emergency, to respond to, recover and restore operations.”

Tabletop Exercises

You’ll also note that scenarios often go hand-in-hand with Tabletop exercises. Tabletop exercises are simulated response activities. Usually, these are held in an extremely generic hotel ballroom with stakeholders of all types hunkered down on their laptops. An exercise begins with a scenario description, and then a moderator provides additional information during the response activities to throw things into further chaos and test the limits of what people are prepared for. Some of the FEMA materials include videos to simulate news reporting, although they need to be about forty times more hyperbolic to match the 24/7 news channel intensity these days.

The 2:06 minute video below provides an interesting example of a tabletop exercise conducted by the local government in Waco, Texas in 2017. Pretty low-tech, but you get the idea of what can be accomplished. More focused exercises can subsequently be run with specific stakeholders, e.g., geospatial teams.

Introduction

This week we will do something a little different for our writing assignment. I would like you to work in groups (see the Lesson 7 announcement for group assignments) to develop one of three different scenarios that focus on leverage points for the use of geospatial applications and technology. You will have the opportunity to imagine a realistic situation and propose different roles for geospatial approaches during the disaster. Each group will use Esri Story Maps to present the content and analysis you have developed.

For this exercise, you will work in the following groups

• Group 1 - TBD
• Group 2 - TBD
• Group 3 - TBD
• Group 4 - TBD

You will be assigned one of three topics.

1. Develop a scenario about a cyber attack that impacts the power grid in the Southeast US. Split your scenario into five 6-hour long time periods, starting with the time period 6 hours prior to the attack.
2. Develop a scenario about a major indiustrial accident (e.g.,chemical spill but you can choose something else) in an industrial site within a major urban area. Split your scenario into five 6-hour long time periods, starting with the time period 6 hours prior to the accident.

Criteria

You will notice that I have not provided detailed specifics on certain aspects of each disaster, such as how fast the wildfires are spreading, or how effective the cyber-attack was at interrupting the power supply. I encourage you to fill in those gaps in your writing and to imagine plausible answers to those sorts of questions.

• For each time period, write two short paragraphs describing what would happen to people, infrastructure, and the natural environment considering the local geography.
• For each time period, identify at least one example of how GIS could be used to prepare, mitigate, respond to, or recover from a specific aspect of the disaster.
• Embed pictures, maps, or other graphics to help tell your story. If you have ideas for geospatial workflows, include them in graphical form.
• Your scenario should be compelling and realistic in a way that would make it easy for an organization to use it as a starting point for developing a disaster preparation plan.

I know group work can be challenging if everyone doesn't do their part. As part of the assessment you will be asked to provide confidential feedback to me about how things went with your team mates. If you are having problems during the week, please let me know as well.

Instructions

For this group exercise, you will be organizing your content into an Esri Story Map. For those of you not familiar with Story Maps, they are a great way of presenting a narrative that includes a mix of text, maps, and other multimedia. They can be a powerful way of conveying a lot of complex material in a “guided tour” format. You can view many examples on the Story Maps homepage. The Story Map related to Hurricane Harvey is particularly nice and you saw one on the 2018 Camp Fire in Lesson 2.

There are a number of ways to get started. You can collaboratively edit in your Story Map directly or you can create a “Storyboard” in a program like PowerPoint or Word and then migrate content. I recommend you develop a storyboard. This will help you organize your content and make sure you have what you need to make the story map. As mentioned in earlier lessons, you can manage your collaboration in the course OneDrive folder.

Here are some resources to get you started.

• ArcGIS Online
• How to make a story map
• What Kind of Story Do You Want to Tell?
• There are also many videos on the Esri site and YouTube for further advice and inspiration.

Before you get started, I recommend that you decide on a division of labor for this work. For example, one person might want to be responsible for developing the overall narrative in consultation with the group, another person might want to take on the analysis/mapping task and another may want to focus on migrating everything into the Story Map.

Collaborating

Since you are working in small groups, collaboration should be fairly straightforward, I suggest the following -

• Get organized - Review the assignment requirements and decide on what you are going to do. Come up with a division of labour e.g., someone might collect content, someone might develop the maps and someone might assemble the Story Map. Make a plan and stick with it, and keep in mind you don't have a lot of time.
• OneDrive and Office 365 Apps - Create a folder in OneDrive and share it with your group. Collect any images or other resources needed for your Story Map. Consider using PowerPoint to create a 'storyboard' to layout your content before moving it to ArcGIS Online.
• ArcGIS Online and Story Maps - Create a group and invite your classmates. You should be able to enable simultaneous editing of the StoryMap. Note that web maps / apps you create can be embedded in Story Maps along with a wide range of other content.
• Ask for help - Get in touch with the instructor if you are having any problems.

Deliverables

For this week's exercise, please submit the following items to the Lesson 7 Group Scenario Exercise Dropbox in Canvas. See our Course Calendar in Canvas for specific due dates.

• Link to the Esri Story Map. Please include the topic number in the naming convention.

Grading Criteria

I'll assign grades by group. This project is worth 4% of your total course grade and will be graded out of 20 points using the following rubric.

Informal Use of Social Media During Crisis

We have already talked a lot about volunteered geographic information (VGI) and other types of citizen involvement in emergency management, but here we will consider how social media data, like Twitter, Instagram, and Facebook, are being used informally and more formally through big (spatial) data analytics. These are potentially rich data sources but are still a bit difficult to use and have some specific problems around getting accurate and meaningful location information.

To get this section started, have a look at this NBC Nightly News Story (2:01 minutes) about how search-and-rescue used social media to help locate people needing rescue.

Mapping Social Media in Crises

In the recent past, there have been significant advances in automated tools for extracting place information from news articles and other text media. This led to a wave of map mashups that allowed for news stories to be browsed using a map. Since those earlier efforts, social media data sources have become ubiquitous, and while similar methods can be used to extract and represent places mentioned in social media reports like Tweets, there are also a lot of challenges we have yet to overcome to make these datasets truly useful in a crisis situation. Moreover, as we saw in Lesson 5, the rise of real-time geospatial systems means we need to be able to locate and understand the content of social media in near real-time, and this is still challenging!

The use of social media in disaster response really took off in the mid-2000s with the efforts of digital humanitarians like Patrick Meier, the author of your textbooks (also see Chapter 3 – Crowd Computing Social Media in Digital Humanitarians for more). In the following short video (1:31 minutes), Patrick explains how this works, particularly how we can teach machines to understand and classify tweets into actionable information.

A few of the challenges associated with mapping information from social media are:

• disambiguating where a tweet is reported from versus what places it talks about;
• figuring out which locations to use when the place names found could refer to multiple places (Indiana, PA vs. Indiana the state);
• symbolizing massive collections of social media reports on a map (simple overlay just causes a lot of clutter - so what else can we do?).

Here at Penn State, we've been engaged in research to develop new tools for foraging through and visualizing geographic information coming from social media reports.

The SensePlace2 project harvests tweets that include disaster-related keywords. From these tweets, we then extract place names and geocode them (along with other named entities, such as people, organizations, and resources). Please have a look at the following 3 minute video, SensePlace2: Visual Analytics and Big Data for Spatiotemporal Sensemaking.

If you want to learn more, check out this 2017 journal article on the project: SensePlace3: a geovisual framework to analyze place–time–attribute information in social media, Cartography and Geographic Information Science

Because so many social media sources now feature API access to their data feeds, new map mashups are now possible that can integrate multiple forms of social media with other geospatial data. Keep in mind that the quality of these vary considerably. For example, some tools just use the location feature that some (very few, it turns out) enable on their devices when they use Twitter.

OPTIONAL

You may be interested in this study that was published just this year (2022!) on using tweets and retweets to understand information diffusion during disasters. This is just FYI, but it is worth a skim now.

Jinwen Xu & Yi Qiang (2022) Analysing Information Diffusion in Natural Hazards using Retweets - a Case Study of 2018 Winter Storm Diego, Annals of GIS, 28:2, 213-227, DOI: 10.1080/19475683.2021.1954086

Deliverable

1. Post a comment in the Emerging Theme Discussion (L7) forum that describes how you imagine integrating social media mapping into a successful geospatial system for emergency management. How would you deal with the various aspects of uncertainty that these data sources entail? What emergency management phase do you think social media data is most useful for?
2. In addition, provide a link and short description to a social media application to emergency management or public safety ‘in the news’ or that you have otherwise come across.
3. The initial post should be completed during the first 5 days of the lesson.
4. Then, I'd like you to offer additional insights, critiques, a counter-example, or something else constructive in response to your colleagues on two of the following 5 days.
5. Brownie points for linking to other technology demos, pictures, blog posts, etc., that you've found to enrich your posts.
   NOTE: Respond to this assignment in the Emerging Theme Discussion (L7) forum by the date indicated on the course calendar.

Grading Criteria

This discussion will be graded out of 15 points.

Please see the Discussion Expectations and Grading page under the Orientation and Course Resources module for details.

Take a mental vacation to a place like this on the Andaman Coast in Thailand.

Credit: © M. Beaty, Penn State used with permission

This week, I'll be reading each of your term project drafts and providing my feedback. So, for now, you can relax a little about your project and focus on the rest of this lesson.

This week, we have explored how scenarios can be used to predict and plan for how GIS can be used for emergency management situations. Scenarios are stories developed around a hypothetical disaster situation, and they are used quite commonly in planning activities as a way to predict what will happen in a real situation.

You have worked with your classmates in this lesson to develop your own scenarios to see for yourself how scenario-based planning works. I hope you found it valuable to attempt this task with your colleagues. Most people who are charged with the task of planning a GIS for emergency management will not be working on that task alone, so the challenges posed by group work in this situation are quite relevant.

Scenarios are not easy to pin down. There are no universal rules as to what they should or should not include, and there are no automated tools available yet that can generate them. Scenario writing requires the synthesis of multiple types of knowledge, and, ultimately, it demands a fair bit of creativity on behalf of the author(s).

Next, we will apply what we have learned so far about the dimensions of emergency management and ways to plan GIS systems to support emergency management tasks. In the next lesson, we will work together on a case study research project to understand how GIS was used in the mitigation, preparation, response, and recovery from a recent disaster.

Reminder - Complete all of the Lesson 7 tasks!

You have reached the end of Lesson 7! Double-check the to-do list on the Lesson 7 Overview page to make sure you have completed all of the activities listed there before you begin Lesson 8.

MapAction started work immediately after the earthquake to develop geospatial products to aid in response and recovery efforts. See the 2012 Haiti Earthquake StoryMap for details.

Credit: MapAction

Case Study Collaborative Project

This week, we will tackle our second collaborative project. This collaborative assignment is designed to pull together what you have learned so far in this class and apply it toward researching and critiquing the use of geospatial approaches and technology in a recent disaster. You will work in teams to gather and condense information to explain and critique how GIS was used in a real crisis situation - the 2021 Haiti Earthquake.

What You Will Learn

By the successful completion of this lesson, you should be able to:

• research and discuss how geospatial approaches can be applied in a real crisis;
• create a Story Map that summarizes what happened and what can be learned from a real crisis;
• critique the use of geospatial approaches and technologies in a crisis situation;
• identify leverage points for the use of geospatial for similar situations in the future;
• describe and discuss the use of geospatial artificial intelligence (geoAI) and its potential impact on geospatial systems for emergency management.

What You Will Do

Lesson 8 is one week in length. To finish this lesson, you must complete the activities listed below.

Please refer to the Course Calendar for specific due dates.

Questions?

If you have questions about the content or lesson activities, please post them to the General Questions and Discussion forum in Canvas. While you are there, feel free to post your own responses if you, too, are able to help a classmate. If your question is of a personal nature, please email me directly through Canvas.

This week, I would like you to work together to research key phases of emergency management, and the use of geospatial analysis to support them for the 2021 Haiti Earthquake. Each group will be assigned to evaluate one or two phases of Emergency Management:

• Group 1 - TBD - Topic: Preparedness following the 2010 Earthquake (focus on period from 2016 to 2021)
• Group 2 - TBD - Topic: Response / Relief in the immediate aftermath of 2021 Earthquake 

Topics not covered this term:

• Group # - TBD - Topic: Recovery between 2010 and 2021 Earthquakes
• Group # - TBD - Topic: Mitigation/Preparedness for next major earthquake

Assignment Guidelines and Criteria

You will be researching the 2021 Haiti Earthquake, which caused massive loss of life and property. Each group should create a Story Map using ArcGIS Online for their phase of emergency management according to the following criteria:

• One Section describing generally what happened to people and infrastructure.
• One Section identifying the key stakeholders and their needs.
• 2-3 Sections about how geospatial was used during this phase. At a minimum, answer the following questions. !hat worked and what did not work? Did geospatially-oriented social media play a role? If so, how?
• Include at least three pictures and/or videos (more = better) and link when appropriate to external sources that back up what you are reporting.
• Together, I'd like you to create at least one analytical product using one or more of the datasets I've linked to here (or others you find on your own).
  • Haiti Earthquake Data Portal
  • Humanitarian Data Exchange
  • Maxxar Open Data Program

This analytical product should include a map and supporting graphics/text such that it can stand on its own if it were distributed widely. It's up to your group what you would like to highlight - there are dozens of datasets out there now and a wide range of possible stories you might try to tell using them. Creativity is encouraged!

Collaborating

Since you are working in small groups, collaboration should be fairly straightforward, I suggest the following -

• Get organized - Review the assignment requirements and decide on what you are going to do. Come up with a division of labour e.g., someone might collect content, someone might develop the maps and someone might assemble the Story Map. Make a plan and stick with it, and keep in mind you don't have a lot of time.
• OneDrive and Office 365 Apps - Create a folder in OneDrive and share it with your group. Collect any images or other resources needed for your Story Map. Consider using PowerPoint to create a 'storyboard' to layout your content before moving it to ArcGIS Online.
• ArcGIS Online and Story Maps - Create a group and invite your classmates. You should be able to enable simultaneous editing of the StoryMap. Note that web maps / apps you create can be embedded in Story Maps along with a wide range of other content.
• Ask for help - Get in touch with the instructor if you are having any problems.

Deliverables

For this week's exercise, please submit the following items to the Lesson 8 Group Haiti Earthquake Analysis Dropbox in Canvas. See our Course Calendar in Canvas for specific due dates.

• Link to the Esri Story Map. Please include the topic number in the naming convention.

Grading Criteria

I'll assign grades by group. It is worth 4% of your total course grade and will be graded out of 20 points using the following rubric.

This week, I would like you to work together to research key phases of emergency management, and the use of geospatial analysis to support them for the 2021 Haiti Earthquake. Each group will be assigned to evaluate one or two phases of Emergency Management:

• Group 1 - TBD - Topic: Preparedness following the 2010 Earthquake (focus on period from 2016 to 2021)
• Group 2 - TBD - Topic: Response / Relief in the immediate aftermath of 2021 Earthquake 

Topics not covered this term:

• Group # - TBD - Topic: Recovery between 2010 and 2021 Earthquakes
• Group # - TBD - Topic: Mitigation/Preparedness for next major earthquake

Assignment Guidelines and Criteria

You will be researching the 2021 Haiti Earthquake, which caused massive loss of life and property. Each group should create a Story Map using ArcGIS Online for their phase of emergency management according to the following criteria:

• One Section describing generally what happened to people and infrastructure.
• One Section identifying the key stakeholders and their needs.
• 2-3 Sections about how geospatial was used during this phase. At a minimum, answer the following questions. !hat worked and what did not work? Did geospatially-oriented social media play a role? If so, how?
• Include at least three pictures and/or videos (more = better) and link when appropriate to external sources that back up what you are reporting.
• Together, I'd like you to create at least one analytical product using one or more of the datasets I've linked to here (or others you find on your own).
  • Haiti Earthquake Data Portal
  • Humanitarian Data Exchange
  • Maxxar Open Data Program

This analytical product should include a map and supporting graphics/text such that it can stand on its own if it were distributed widely. It's up to your group what you would like to highlight - there are dozens of datasets out there now and a wide range of possible stories you might try to tell using them. Creativity is encouraged!

Collaborating

Since you are working in small groups, collaboration should be fairly straightforward, I suggest the following -

• Get organized - Review the assignment requirements and decide on what you are going to do. Come up with a division of labour e.g., someone might collect content, someone might develop the maps and someone might assemble the Story Map. Make a plan and stick with it, and keep in mind you don't have a lot of time.
• OneDrive and Office 365 Apps - Create a folder in OneDrive and share it with your group. Collect any images or other resources needed for your Story Map. Consider using PowerPoint to create a 'storyboard' to layout your content before moving it to ArcGIS Online.
• ArcGIS Online and Story Maps - Create a group and invite your classmates. You should be able to enable simultaneous editing of the StoryMap. Note that web maps / apps you create can be embedded in Story Maps along with a wide range of other content.
• Ask for help - Get in touch with the instructor if you are having any problems.

Deliverables

For this week's exercise, please submit the following items to the Lesson 8 Group Haiti Earthquake Analysis Dropbox in Canvas. See our Course Calendar in Canvas for specific due dates.

• Link to the Esri Story Map. Please include the topic number in the naming convention.

Grading Criteria

I'll assign grades by group. It is worth 4% of your total course grade and will be graded out of 20 points using the following rubric.

We hear a lot about artificial intelligence (AI) these days, and indeed AI is a rapidly expanding field finding applications in many aspects of our lives. Emergency management and geospatial applications are no exception. So, what is AI and GeoAI and how are they being applied to the phases of emergency management?

Artificial intelligence refers to a range of approaches and applications whereby computers are trained to simulate intelligent human behavior and act in autonomous or semi-autonomous ways. AI systems are also able to process and learn from vast amounts of data that are difficult if not impossible for humans to readily understand.

What about geospatial artificial intelligence (geoAI)? I’d like you to have a look at two videos that illustrate some of the current characteristics of geoAI and where it is heading. The first video is a presentation on machine learning and the prediction of road accidents from a recent Esri conference (8:50 minutes). It provides a good overview of geoAI and an interesting application to illustrate what’s currently possible with one of the main GIS software systems.

The second video is an interview with Nigel Clifford the CEO Ordinance Survey, the UK’s national geospatial agency where he talks about the future of AI and geoAI in particular (4:35 minutes).

Finally, I’d like you to consider a few examples of AI and geoAI applied to recent emergency management problems. The first is a presentation from Robert Munro, CTO Figure Eight, at the recent CogX AI conference (18:47 minutes). While not specifically focused on geoAI, geospatial problems figure through most of his presentation. Contrast this perspective with what we saw from Esri in the earlier video. The second video is a quick recap of the surf rescue video you saw in the UAV exercise in Lesson 2.

Artificial Intelligence Processing at the Edge: The Little Ripper Lifesaver UAV (2:05 minutes)

---> Breaking news: Here is an update on Little Ripper and its cousin CrocSpotter.

By now, you should have received my feedback on the first draft you submitted in Lesson 6. You now have until the end of Lesson 10 to submit your final draft. Please dedicate some time this week toward incorporating some of the suggestions I've provided. If you are unclear about any of my comments or suggestions, get in touch so I can clarify things for you.

This week, you took on the task of developing a case study analysis of the 2021 Haiti earthquake, focusing specifically on the role of geospatial analysis during emergency management phases. This was presented via a Story Map that can be shared with others in an interesting and accessible format. We also discussed the AI and how it is being developed in the geospatial realm as geoAI. I like that this class juxtaposes a consideration of the practical needs of emergency management now with cutting edge trends that are changing things very quickly. I didn't ask about this earlier, but can you envisage ways geoAI (or other emerging themes) could be brought to bear if the Nepal event were to happen now? As we have seen, what seemed to be impossible or cutting edge a few years ago are mainstays today.

Next week, you will consider another case study about an event that occurred late in 2018, the Sulawesi earthquake and tsunami. This event has so many interesting dimensions, many of which we have been studying and discussing in this class, including logistics, social vulnerability, multiple hazards, national and international responses, and even civil unrest! For the final Emerging Theme, we will revisit some of the real-time GIS advances covered in Lesson 5 in greater detail by discussing the Internet of Things (IoT).

Reminder - Complete all of the Lesson 8 tasks!

You have reached the end of Lesson 8! Double-check the to-do list on the Lesson 8 Overview page to make sure you have completed all of the activities listed there before you begin Lesson 9.

Drawing on data from the USGS, The New York Times worked quickly to develop informative maps and web content showing key observations from the Earthquake and Tsunami impacting Sulawesi, Indonesia.

Credit: New York Times

This week, we will learn about how geospatial approaches and technologies were used to respond and recover from the 9.28.2018 Sulawesi Earthquake and Tsunami in Indonesia. This disaster required a large-scale response from many entities including response organizations around the world. The geography of the affected area made it very difficult to reach victims and assess the damage - posing a variety of challenges to geospatial analysts that we will explore this week.

What You Will Learn

By the successful completion of this lesson, you should be able to:

• identify and critique the ways in which GIS was used to respond and recover from the 9.28.18 Sulawesi, Indonesia Earthquake and Tsunami;
• explain the complexity associated with very large disasters that international cooperation;
• revise the final draft of your term project;
• describe and discuss the Internet of Things (IoT) in emergency management situations.

What You Will Do

Lesson 9 is one week in length. To finish this lesson, you must complete the activities listed below. 

Please refer to the Course Calendar for specific due dates.

Questions?

If you have questions about the content or lesson activities, please post them to the General Questions and Discussion forum in Canvas. While you are there, feel free to post your own responses if you, too, are able to help a classmate. If your question is of a personal nature, please email me directly through Canvas.

Sulawesi, Indonesia Earthquake and Tsunami

On September 28, 2018, at 6:02 PM local time, a 7.5 magnitude earthquake struck in central Sulawesi, Indonesia. The quake triggered a tsunami with a maximum height of 4-7 meters (13-23 feet) causing massive destruction. There was also widespread destruction due to soil liquefaction, landslides, flooding, and aftershocks (see below). There have been over 2,100 confirmed dead, 10,679 injured, and over 5000 still missing. There was mass disruption to transportation links which delayed response and recovery efforts.

Map of the epicenter and aftershocks of the 2018 Sulawesi Earthquake.

Credit: Indonesian Institute of Sciences

The earthquake occurred in a part of Indonesia that is diverse both in terms of human settlement patterns and environmental factors. It contains relatively large settlements such as Palu (population 335,297 in 2010) as well as small and remote rural settlements. The triple impact of the earthquake, tsunami and land movement made it extremely difficult to locate people in need and deliver food and medical assistance. The recovery effort has also been challenging.

Search and Rescue in Palu, Sulawesi

Credit: BNBP

Putting Yourself There

To get a sense for what this all looked like on the ground, please consider the following:

• Review: Catastrophe in Sulawesi – The Straits Times (Oct 2, 2018)
• Visit: BNPB Geospatial (Use Google Translate)

• Listen to the 3:51 minute audio report from NPR or read the transcript

Now that we have a better understanding of what happened in Sulawesi during and right after the earthquake and tsunami, I'd like you to read about three topics related to Indonesia’s disaster vulnerability and preparedness. These touch on themes we've considered earlier, e.g., social vulnerability, planning and preparedness, and emergency communications.

1. READ

Social vulnerability to natural hazards in Indonesia: driving factors and policy implications (2014) in the Journal of Natural Hazards. You can find this article on the following page in Canvas.

The first reading is a journal article about measuring and mapping social vulnerability in Indonesia and how this can be used to inform policy (you first encountered way back in Lesson 3), As you read this, think about how it fits or contrasts with what you learned about who was impacted the most by the 2018 event.

2. READ

Chapter 9: Spatial Planning, Disaster Risk Reduction, and Climate Change Adaptation Integration in Indonesia: Progress, Challenges, and Approach (2017) in the recent book Disaster Risk Reduction in Indonesia. You can find this book in the Penn State Library and/or on the following page in Canvas.

The second reading focuses on the role of spatial planning in Disaster Risk Reduction (DRR) efforts in the context of current vulnerabilities and changing vulnerability with climate change. There are two key points I'd like you to take from this reading. The first is the concept of Disaster Risk Reduction, and the second is the idea that the current hazard and risk profile of a given area is not fixed and may be exacerbated by factors such as climate change or rapid urbanization.

3. READ

Finally, have a look at the following online resources about tsunami warning systems.

• What is a tsunami and how are they monitored?
• What Went Wrong With Indonesia’s Tsunami Early Warning System
• Would the U.S. Tsunami Warning System Have Averted Indonesia’s Disaster?

The final readings take a different direction and discuss tsunami warning systems, how they are meant to work and what happen during the 2018 Sulawesi event.

This week’s emerging theme topic, digital twin, brings together most of the emerging themes (and other content) you have learned about over the last few weeks.

The basic idea behind a digital twin is to build a virtual version of a real world system by integrating a wide range of datasets and models. The twin allows you to examine the way the system works and to see the effects of potential changes. They may also incorporate machine learning are are able to learn and change over time as new information is added.

For example, a digital twin of an aircraft engine allows engineers to understand maintenance needs and performance issues under real world and modelled conditions. For example, Rolls-Royce feeds inflight sensor and instrument data via satellite link its digital twin.

Rolls-Royce UltraFan TurboFan

Credit: Rolls-Royce

Read this short article on Rolls-Royce’s IntellgentEngine program: How Digital Twin technology can enhance Aviation

You may hear digital twin talked about in the context of the “multiverse”. This language is a bit trendy, but the basic point is that a digital twin provides a way of creating / testing out new ideas or looking at problems in different (endless??) ways. A basic example might be modelling the potential impact of different road intersection options on pedestrian safety. On a much broader scale, and in an emergency management context, a digital twin may be used to understand the cascading impacts of major flooding in an urban area. Impacts that may not be obvious using traditional GIS or statistical analysis.

Video: What is a Digital Twin? How does it work? (1:56)

Video: Digital Twin Sydney (4:24)

TAKE A QUICK LOOK / KEEP FOR REFERENCE

Have a quick look at these two websites that provide some detailed information about Digital Twin from the point of view of two software developers in this space.

• Digital Twins Explained: A Guide for the Built Environment from the New Zealand Company, 12d Synergy. This guide is also available for download.
• Next look at ESRIs (more flashy!) Digital Twin website and go ahead and download a copy of their eBook for future reference.

Take note of how familiar geospatial and data science methods and technologies are used in the context of a Digital Twin.

Digital Twin – Examples

Now, look at this short video and have a play with the New South Wales Digital Twin.

Video: New South Wales Digital Twin (2:07)

Now spend a few minutes exploring the data sets and tools on the New South Wales Digital Twin web portal

End your exploration with this short article about how the NSW Digital Twin to inform emergency planning this bushfire season.

Climate Resilience Demonstrator

The following video and interactive app were created as part of The Digital Twin (DT) Hub by the Centre for Digital Britain at the University of Cambridge. It will probably make you think about the scenario development group project you completed a couple of weeks ago. Start by watching the video and then move on to the interactive app.

Video: Tomorrow Today - a CReDo film, and Interactive App (6:21)

Now, work through the interactive app.

TAKE A QUICK LOOK / KEEP FOR REFERENCE

If you are interested in taking a deeper dive into the topic of Digital Twin, you may want to look at the follow recent journal papers. They provide nice reviews of the history of DT and their applications in disaster and emergency managment. No need to read these carefully - Just skim / have a look at tables and figures. Note PDF versions are on the following page in Canvas.

Disaster City Digital Twin: A vision for integrating artificial and human intelligence for disaster management

Digital twin-driven intelligence disaster prevention and mitigation for infrastructure: advances, challenges, and opportunities

RESPOND

• What stands out to you about the Digital Twin approach?
• Do these examples meet the your expectations or definitions of DT from the previous readings?
• Do you think we can achieve spatial Digital Twins as robust as the Rolls-Royce IntellgentEngine? Does GeoAI help?
• What stages of EM can DT be used to help with? How do DT let you plan for the future? New normals?
• Can DT help us understand/model multi-hazard, compounding, cascading events?

I'd like you to conducted a quick analysis and write a short report synthesising what you have learned about the Sulawesi Earthquake and Tsunami. 

To begin with, you will work with satellite image pairs taken before and immediately following the 2018 Sulawesi event. The imagery is from Palu and the surrounding area. Imagine you are helping assess the damage on critical infrastructure (rather than population issues or housing) for the purposes of early recovery/clean-up.

I would like you to identify three areas demonstrating three different types of disaster impacts, e.g., landslide area. Present these as side by side image pairs. You can identify these areas manually through visual examination, refer to crowdsourcing maps where damage has already been identified, or even conduct your own image classification and change detection analysis.

After you assess the satellite images and have your image pairs, look online for an on-the-ground photo showing what these areas might look like up close, and then provide short captions for each image.

There will be a lot of obvious damage to things like buildings, so, brownie points for having one of your three image deal with more unusual (but significant) impacts.

You will need to:

1. Download the image pairs from the course OneDrive folder.
2. Unzip and then open the images in ArcGIS Pro.
3. It might be useful to use ArcGIS base maps or other data such as OSM or other data sources that you are aware of. For example, OSM might help you identify damage to roads.
4. Conduct your before and after assessment. Provide short descriptions (1-2 sentences) for each image pair.
5. Save your image pairs, either through ArcGIS Pro or as a simple screenshot.

Finally, draw upon your findings and the reading you have done to answer the following questions in a 300-400 report:

• Do you think the types of damage observed in the repeat imagery could have been avoided?
• How do you think emerging technologies, especially geospatial, can accelerate the process of DRR?
• BONUS - What are some of the issues associated with providing early warning to everyone versus just to first responders and emergency managers?

Deliverables

Grading Criteria

This assignment is worth 5% of your total grade and will be graded out of 10 points. 

At this point, you should be well on your way toward finishing your final term project paper. If you have already finished, consider having a colleague at work (or someone else you know who understands geospatial approaches and technology) read your final draft and offer feedback. This is a great way to check for spelling and grammatical errors, and it's also a great way to find out how well you are at communicating your ideas.

As always, if you run into trouble and need some help, please email me.

If I were you, I'd also have a look ahead at the video presentation component of the final project, which you may want to begin preparing now. It's due during Lesson 10.

This week, we have explored the 9.28.2018 Sulawesi Earthquake and Tsunami and the many ways in which geospatial approaches were used to respond and recover from this disaster. The magnitude of the disaster means that for the next several years, GIS and related technologies will continue to have a role in the long-term recovery of the region, and we can already see in subsequent disasters (like the many USA storms in 2018) that the expectations for GIS outputs continue to evolve at a rapid pace.

Next, we will begin the final lesson for this course. We will devote our attention to the term projects you have been working on throughout the semester. You will submit your final term project assignment materials and participate in a mini-conference to share your findings with your classmates.

Reminder - Complete all of the Lesson 9 tasks!

You have reached the end of Lesson 9! Double-check the to-do list on the Lesson 9 Overview page to make sure you have completed all of the activities listed there before you begin Lesson 10.

Along the Great Ocean Road - Victoria, Australia 

Credit: Matt Beaty

What You Will Learn

At the successful completion of Lesson 10, you should be able to:

• deliver a completed final term project report;
• create a 5-7 minute narrated presentation that describes your term project;
• participate in a mini-conference with your classmates by sharing your presentations.

What You Will Do

Lesson 10 is one week in length. To finish this lesson, you must complete the activities listed below. 

Please refer to the Calendar in Canvas for specific timeframes and due dates.

Questions?

If you have questions about the content or lesson activities, please post them to the General Questions and Discussion forum in Canvas. While you are there, feel free to post your own responses if you, too, are able to help a classmate. If your question is of a personal nature, please email me directly through Canvas.

This week provides you with your last opportunity to finish revising your term project. Make sure you have addressed the issues I pointed out in your first draft. If you have questions about your edits, reach out to me quickly so I have time to get back to you before the due date.

Once you have made it through the edits, consider the following ideas for enhancing your final project:

• Include images, links to multimedia, and other content that will help the reader / decision-maker understand the context of your report.
• Include citations to the relevant scientific literature to bolster your arguments and substantiate any claims you have made.
• Make sure that the formatting of your report is consistent and elegant - make it look professional.
• Ask a classmate, colleague at work, or someone else who would be reasonably familiar with the content to read your report and provide feedback.

Grading Criteria

Your term project should meet the following guidelines:

• It should be clear who you are writing for and the role you are playing in preparing this report
• The final text is no longer than 3000 words (not including references or an appendix where you can outline your methodology in greater detail)
• Includes images and graphics where relevant
• Cites sources using a consistent citation format
• Applies consistent formatting across the sections of your paper (hint: use MS word styles)
• Presents clear and organized arguments to support your project goals
• Matches the spirit and goals associated with the project option you have chosen

Grading Rubric

Your final term project is worth 15% of your final course grade and will be graded out of 100 points using the following rubric.

The ability to synthesize technical information into a concise package that is appropriate for a broad audience is a skill that is hard to hone and yet highly sought after in the workplace. This assignment provides you an opportunity to do just that. I would like you to create a short (5 - 7 minute) recorded presentation about your term project. The presentation will be shared with your classmates.

Guidelines for your video

• Must be no longer than 5-7 minutes (no exceptions!).
• Outline the topic you chose, brief background, and key contributions of your work.
• Create a slide presentation that includes key points, graphics, photos, etc. to explain the project.
  • Avoid lots of text (and reading your slides) if you can make the same points with a graphic. You want the audience to focus on what you are saying and not on reading the slide!
  • Do not go into extreme detail in five minutes - the idea here is to provide a quick teaser of your work that will entice someone to read your final report.
  • Be creative!

Make your video.

1. You may choose your own screen recording software, or record your screen-cast from within Canvas. Here is a link to instructions on how to use Kaltura Capture to record within Canvas. Note: Kaltura Capture is accessed in Canvas by clicking on My Media in the Canvas menu and "Add new". If you do not use Kaltura Capture, you will need to upload your own video file to My Media using these instructions.
2. Record your screen while you give your five to seven-minute slideshow (make sure the slides are visible and the audio is clear - using a headset microphone is normally the best way to ensure decent audio quality).
3. Need more help? Contact the World Campus Helpdesk for assistance.

Directions for creating, submitting, and sharing your presentation can be found with the dropbox. 

Review your peers' presentations

Go to the Media Gallery in Canvas and view your peers' presentations. Please provide comments and feedback to your peers in the "Lesson 10 Term Project Presentation Discussion" forum in Canvas. I will leave the course open for several weeks so you are able to view your classmate's work. 

Grading Criteria

The Term Project Presentation is worth 5% of your total course grade and will be graded out of 50 points using the following rubric.

This week, you have finished work on your term project and shared your findings with your classmates. I hope you have found this experience to be intellectually stimulating. Throughout the course, I have tried to balance multiple learning objectives, and I appreciate your patience with me as I have refined things a little as we progressed through the material. Every class I teach is different from the last instance, as I like to keep things as fresh as possible.

I think it's clear that geospatial approaches and technologies can be shaped in a wide range of ways to fit various types of emergency management tasks. Emerging technology trends like volunteered geographic information and geoAI will allow future GIS systems for emergency management to be flexible and responsive to dynamic and complicated crisis situations. Now that you have completed this course, you should have the ability to plan new GIS systems that take into account the real-world constraints of a disaster scenario and blend together off-the-shelf GIS tools with creative solutions that leverage new technologies and data sources. I wish you the best of luck in your future work! Please stay in touch and let me know how you're doing.

I will work to quickly evaluate your final project materials and post your grades. In the meantime, please complete the course evaluation that you are sent automatically and provide honest, constructive feedback for the material as well as my performance. Your feedback makes it possible for future students in this course to benefit from your experiences.