GEOG 858
Spatial Data Science for Emergency Management

Reading Assignment


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.


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.


These materials present definitions and roles for GIS in the context of Emergency Management. They also reflect the view from a major software vendor in this field. As you peruse these documents, think about which aspects seem software-specific vs. those that appear to be more general to all geospatial applications in emergency management. How would you define roles differently, or broaden some of their definitions?


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.  


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


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.


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?


Complete the writing assignment - Details on the next page!