GEOG 885
Advanced Analytic Methods for the GEOINT Professional

DC Sniper Case Study: Geospatial Thinking Exercise


Case Studies in General

Case study-based learning encourages problem-solving skills; it affords a systematic way of looking at events, collecting data, analyzing information, and reporting the results. It is perhaps the ideal methodology for learning about geospatial analytics. Rather than following a rigid protocol, a scenario involves an in-depth, longitudinal examination. When done properly, a case study can create those moments that pull everything you learned into focus. When theory, practice, and experience all come to a decision that shapes a definitive course of action, it is no longer a question of what can be done, but of what should be done. Unfortunately, there are very few specific geospatial case studies available in the public domain.

DC Sniper Case Study

This course will use the DC Sniper scenario as a case study examining the application of an analytic method to geographic problems. You will work independently with the DC Sniper case study in a step-by-step manner to learn how to use structured methods in geospatial analysis.This step-by-step learning will occur in parallel with another analysis project you will be working on as a team.

In October 2002, local, state, and federal authorities from the Washington, DC area joined in an unprecedented cooperative effort to capture the individuals charged with a series of shootings that paralyzed the National Capital Region. John Allen Muhammad and John Lee Malvo were apprehended following a 3-week shooting spree that brought together uniformed and investigative law enforcement personnel and communications resources from across the region. The extensive response and investigative effort required intelligence that was shared among hundreds of law enforcement officers from a variety of jurisdictions and levels of government.

Read and study the case study. Complete the Exercise below.


Submissions Instructions: Complete the DC Sniper Geospatial Thinking Exercise. Post your analysis to the Lesson 1 Discussion Forum.

To participate in the discussion, please go to the Lesson 1 Graded Discussion forum in Canvas. (That forum can be accessed at any time in Canvas by clicking on the Modules tab. The Lesson 1 Graded Discussion forum is listed under the Orientation Section.)

Purpose: To identify the full range of spatial and geospatial forces, factors, and trends could have indirectly shaped the DC Sniper case.

General. We are using this technique to identify the critical geospatial factors that could have influenced the DC Sniper Case. Often analysts realize only too late that some additional information categories will be needed and then must go back and review all previous files and recode the data. With a modest amount of effort, “Outside-in Thinking” can reduce the risk of missing important variables early in the analytic process.

Most analysts spend their time concentrating on familiar factors and overlook many important geospatial aspects of a problem. That is, they think from the “inside”—namely, what they control—out to the broader world. Conversely, “thinking from the outside-in” begins by considering the external changes that might, over time, profoundly affect the analysts’ own field or issue. This technique encourages analysts to get away from their immediate analytic tasks (the so-called “inbox”) and think about their issues in a wider conceptual and contextual framework. By recasting the problem in much broader and fundamental terms, analysts are more likely to uncover additional factors, an important dynamic, or a relevant alternative hypothesis.

What to do

Using the provided DC Sniper Case Study:

  1. List all the key geospatial characteristics that could have had an impact on the activities of the DC Sniper, but over which one can exert little influence (e.g., locations where people live, traffic networks, etc.). General geospatial characteristics include:
    • Location (magnitude, location, and time)
    • Spatial distributions (pattern, density, and spatial variance)
    • Regions (space in which either single or multiple features occur)
    • Hierarchies (nested levels of phenomena)
    • Networks (connectivity, centrality, diameter, density)
    • Spatial associations (autocorrelation, distance decay, and contiguities)
    • Surfaces (densities of occurrence, flows over space and through time)
  2. Focus next on the key factors over which an actor (the DC Sniper or the police) can exert some influence. For example, dispersing police patrols, establishing checkpoints, not shooting near their "home location," etc.
  3. Assess how each of these geospatial characteristics could affect the analytic problem.
  4. Determine whether these geospatial characteristics actually had an impact on the DC Sniper based on the available evidence.