According to the American Terrorism Study, 296 terrorism incidents occurred in the United States from 9/11 through 2019.
In domestic terrorism investigations, as in conventional policing, place matters. Although the location of terrorist violence is critical, the places where a terrorist lives and plans violent acts can also represent vital evidence.
Information about place helps law enforcement and intelligence agencies identify individuals or groups engaged in terrorism-related activities and provides opportunities to prevent terrorist attacks and apprehend the people involved. In addition, researchers can use location information to understand and predict how, when, and why a terrorist or terrorist group will act.
Prior spatial research looking at the “where” of terrorism-related activity focused on the site of the terrorist act, with an inference that planning of the activity occurred at or near the location of the terrorist act. However, other research has shown that most terrorists do not live near the places they attack. Rather, the locations where those who commit terrorist acts live and plan are often geographically distinct from where the attack is executed. In addition, incidents related to terrorist activity occur throughout the nation and in diverse communities.
Moving forward, understanding the place-related connections between residence, planning, and execution of attacks can give law enforcement and intelligence agencies sharper insights into patterns of extremist violence. A larger place-based dataset can also lead to more statistically significant research findings and may help expose people who plan acts of terror before they can implement them.
A Two-Tool Approach to Spatial Analysis of Terrorism Risk
Much of the existing research connecting location to the risk of terrorism in particular places has relied on statistical models designed to predict how a single factor can increase or decrease the risk of terrorism in a particular location.
However, the risk of terrorism is based on multiple, interacting factors, rather than on a single variable. With that in mind, a research team from the University of Arkansas and Rutgers University applied two advanced analytical tools for interpreting location data. The tools are:
- Conjunctive Analysis of Case Configurations (conjunctive analysis): A method that identifies the demographic and social characteristics at neighborhood and county levels and develops profiles of communities most at risk of terrorist attacks and attempted attacks, as well as those most likely to be the location where preparatory or pre-incident planning takes place.
- Risk terrain modeling: A method for identifying situational, place-based risk factors most associated with locations where terrorist incidents are likely to be planned or occur. This method looks at specific aspects of the physical landscape, such as locations of buildings or parking lots.
The Arkansas-Rutgers team integrated these tools in a single analytic inquiry designed to provide a more complete picture of how social and environmental elements intersect in unique and patterned ways across communities. The study extended previous research on the place-based risks of terrorism by combining the two methods to discover underlying risk dynamics.
The study objectives were to:
- Identify demographic and social characteristics of communities at risk of terrorism-related pre-incident and incident activities.
- Identify situational, place-based risk factors most associated with where pre-incident and incident activities are more likely to occur.
Through combining conjunctive analysis and risk terrain modeling, the team found that terrorism-related activities in the United States were not evenly distributed geographically. In fact, the top five states in terms of total incidents accounted for 50% of all incidents. This finding can help inform policy. For example, law enforcement agencies can use the data to allocate anti-terrorism resources.
The team used the two tools to analyze risk through several criminology perspectives, including ecological, situational, and environmental criminology. See “Defining Criminology Perspectives.”
The research team used this approach to develop a framework for understanding how broad social conditions and specific interactions operate in a particular physical area to increase or decrease the risk of terrorism-related activities in that area.
The team then examined data linked to terrorism-related incidents in the United States from the time of the 9/11 terror attacks in 2001 through 2019. According to the American Terrorism Study, during that time, 296 terrorism incidents and 617 pre-incident activities occurred. In addition, there were 420 known residences tied to terrorism-related incidents in particular states.
The conjunctive analysis segment of the research examined geographic study areas, such as counties and census tracts, with at least one terrorism-related event. The analysis revealed that those areas with the most prominent risk profiles were all associated with high-density populations.
The risk terrain modeling study segment looked at spaces as small as a single building or parking lot. This analysis indicated that New York City had the highest number of attempted or actual terror incidents with 13 incidents, all primarily involving use of a bomb or other explosive.
The Importance of Place
The place-based analysis approach to terrorism investigation represents a shift from the conventional research emphasis on targeting suspicious persons by their demographic or other traits. This approach investigates the importance of location in explanations of crime and terrorism.
The research team noted that although approaches to place-based terrorism research in the United States are varied, some patterns are emerging from the literature, suggesting certain prominent risk factors, including:
- Urbanization in the study area
- Social diversity
Further, the team reported that economic factors were relatively insignificant for predicting the location of terrorism incidents.
A More Complete Picture
The integration of macro-level (socio-demographic, from Conjunctive Analysis) and micro-level (terrain feature, from risk terrain modeling) perspectives in a single study provides a more complete picture of how social and environmental elements intersect in unique and patterned ways across communities.
One benefit of this more robust place-based data set relates to the rarity of terrorism-related incidents in the United States since 9/11. The statistical significance of research findings depends on the quantity of data analyzed.
The main data sources for the study were:
- The American Terrorism Study, a source of data on pre-incident terrorism-related activities and incident activities.
- Community and environmental data derived from an open-access data portal, Info-Group, and the U.S. Census Bureau.
Learning How Demographic and Social Characteristics of Communities Influence Behavior Using Conjunctive Analysis
Conjunctive analysis differs from conventional quantitative research approaches in that it allows for all possible combinations of variables in what are known as “fully saturated models.” The study focused on counties with at least one terrorist-related event, but it aggregated all combinations of data to determine risk profiles. It generated findings at the county, tract (or neighborhood), and event levels.
The most prominent terrorism risk profiles identified through conjunctive analysis, combining all three levels of analysis, included:
- High population density
- Low white population
- Less-than-high-school education
- Moderate unemployment
- Low percentage of families below the poverty line
- Moderate percentage of families living in the same residence as one year prior (stability measure)
- Low percentage of vacant houses
- High percentage of foreign born
Learning How Environment Influences Behaviors Using Risk Terrain Modeling
The study represented the first application of risk terrain modeling to U.S. domestic terrorism.
Risk terrain modeling diagnoses how the environment influences behaviors. It is used to predict risk at the micro level, with the expectation that some locations are riskier than others. It considers two variables, proximity and density, in determining the spatial influence of risk factors in a given physical environment. For example, in considering risk posed by the presence of a bar in a local area, risk terrain modeling considers whether close proximity to a bar creates a risk of crime and whether the density of bars in a small area influences risk of crime.
The risk terrain modeling segment of the study found that after New York City, the second-highest incident counts occurred in the Oakland, California area. Of nine total incidents, eight related to environmental extremism, and one was Islamist extremism. The report also presented neighborhood profiles of three Washington, D.C., neighborhoods where a total of five terrorism-related incidents occurred during the study period. A notable feature of those tracts was numerous government buildings.
Criminology research has long recognized the significance of crime “hot spots” as potential predictors of criminal behavior and as opportunities to develop interventions to prevent crime. Risk terrain modeling extends beyond a focus on specific hot spots in one time period to one that examines conditions over time, uncovering contexts conducive to terrorism events and their precursors.
Limitations of this Study
Given the rarity of terrorism incidents, the researchers combined data categories to achieve statistical significance. Although they acknowledged that the merger of categories is a study limitation, at the same time they said, “given the heightened level of offense type, we believe this is an important contribution.” The three combined categories were pre-incident/preparatory; target location; and residence. When combined, the three reflect a broader terrorism activity with known locations.
The study was also limited by the fact that full street addresses were not available for all locations informing the risk terrain modeling micro-level analysis.
Combining the analytical power of conjunctive analysis and risk terrain modeling offers promise for enhancing the ability to predict where future terror-related activity is more likely to occur.
The relatively small number of terrorist attacks in the United States makes it difficult to collect enough data to assess the risk of terrorism-related events. The researchers noted that, in a typical day, there are more murders in the United States than all the domestic terrorism incidents since 9/11. By combining data from multiple categories, the study aimed to generate findings of greater significance to law enforcement and intelligence agencies, as well as the research community.
A significant implication of the research is that this approach can be used to alert community members, as well as law enforcement, about possible locations of terrorist acts.
That said, assessing the predictive power of the researchers’ models will have to await future events.
Sidebar: Defining Criminology Perspectives
In this study, researchers analyzed risk from three criminology perspectives. Following are definitions of each, including ecological, situational, and environmental criminology.
- Ecological — Focused on how different environments, such as area- and place-based social organization and activities, influence criminal development and action.
- Situational — Focused on how aspects of an individual’s situation influence the individual’s choices to engage in or refrain from criminal conduct; for example, in a prison environment, aspects include prison features, staffing, and resident access to communication devices.
- Environmental — Focused on exploring how actual criminal events involve interactions between motivated individuals and social, economic, legal, and physical surroundings.
About This Article
The research described in this article was funded by NIJ award 2017-ZA-CX-0004, awarded to the University of Arkansas. This article is based on the grantee report “Innovative Methodologies for Assessing Radicalization Risk: risk terrain modeling and Conjunctive Analysis,” by Jeff Gruenewald, principal investigator.