Richard Medina

Spatial and Temporal Analyses of Terrorist Incidents in Iraq, 2004-2006

Terrorist incidents are not random in space or time. Understanding the current spatial and temporal patterns of terrorist incidents, as well as predicting future trends, is vital for effective counterterrorist efforts. This article focuses on terrorist incidents in Iraq, which are defined here as attacks, both successful and unsuccessful, in order to detect patterns in the establishment of terrorist activity spaces. Using Geographic Information Science (GISc), this project carries out a series of spatial and temporal cluster identification analyses on recent terrorist incidents in Iraq.

Visualizing diurnal population change in urban areas for emergency management.

There is an increasing need for a quick, simple method to represent diurnal population change in metropolitan areas for effective emergency management and risk analysis. Many geographic studies rely on decennial U.S. Census data that assume that urban populations are static in space and time. This has obvious limitations in the context of dynamic geographic problems. The U.S. Department of Transportation publishes population data at the transportation analysis zone level in fifteen-minute increments. This level of spatial and temporal detail allows for improved dynamic population modeling. This article presents a methodology for visualizing and analyzing diurnal population change for metropolitan areas based on this readily available data. Areal interpolation within a geographic information system is used to create twenty-four (one per hour) population surfaces for the larger metropolitan area of Salt Lake County, Utah. The resulting surfaces represent diurnal population change for an average workday and are easily combined to produce an animation that illustrates population dynamics throughout the day. A case study of using the method to visualize population distributions in an emergency management context is provided using two scenarios: a chemical release and a dirty bomb in Salt Lake County. This methodology can be used to address a wide variety of problems in emergency management.

A Geographic Information Systems (GIS) Analysis of Spatiotemporal Patterns of Terrorist Incidents in Iraq 2004–2009

As terrorism on all scales continues, it is necessary to improve understanding of terrorist and insurgent activities. This article takes a Geographic Information Systems (GIS) approach to advance the understanding of spatial, social, political, and cultural triggers that influence terrorism incidents. Spatial, temporal, and spatiotemporal patterns of terrorist attacks are examined to improve knowledge about terrorist systems of training, planning, and actions. The results of this study aim to provide a foundation for understanding attack patterns and tactics in emerging havens as well as inform the creation and implementation of various counterterrorism measures.

Advancing the Understanding of Sociospatial Dependencies in Terrorist Networks

Terrorist networks operate in hybrid space where activities in social and geographic spaces are necessary for logistics and security. The Islamist terrorist network is analyzed as a sociospatial system using social network analysis, Geographic Information Science (GISc), and novel techniques designed for hybrid space analyses. This research focuses on identifying distance and sociospatial dependencies within the terrorist network. A methodology for analyzing sociospatial systems is developed and results lead to a greater understanding of terrorist network structures and activities. Distance and sociospatial dependencies are shown to exist for the Islamist terrorist network structure. These findings are discordant with recent literature that focuses on terrorist network tendencies toward decentralization in the information age. In this research, the Islamist terrorist network is theorized to use multiple structures of hierarchical and decentralized organization for effectiveness, efficiency, and resilience. Implications for counterterrorism policy and strategies are given.

Geospatial Analysis of Dynamic Terrorist Networks

The emergence of global terrorism has given a new relevance to the study of social networks within global geographic space. Terrorists and their organizations, as nonstate actors, are a great threat to the existing order, structures and people. However, as organizations, terrorist networks share an evolving correspondence to other organizational entities both in terms of their social network relationships, and the manifestation of these relationships across geographic space. This evolving correspondence is a fertile ground for description and investigation. While our knowledge of structure and operations of terrorist networks is presently limited, gaining this knowledge is a matter of global security and peace. Generally, a network is visualized as a collection of vertices or nodes and the connections between them termed edges or links. In the study of terrorist networks in social space, nodes, or actors in the network can be individual terrorists, terrorist cells, or clusters, where the links are the relationships between those nodes. Various types of nodes and links can coexist. For example, nodes can represent different sex, nationality, location, etc., while links can vary by strength of relationships, geographic or social class proximity, etc. Nodes and links in a network can also be represented with varying degrees of importance or influence by different weights.1 For example, if the nodes in question are individual people, Osama bin-Laden of al Qaeda will be a larger influence on the network than an actor of lesser status. Nodes within a network typically vary in their connectivity. They can be classified based on their relative connectivity as hubs or non-hubs. Network hubs dominate connectivity, and are responsible for connecting nodes with fewer connections. An ideal example of a hub in a network is the wheel that contains a node at the center, and nodes at the outside end of each spoke. The hub in the center has optimal connectivity, as it is connected to each of the nodes through the spokes, while the outer nodes have the minimal connections; they connect only to the hub. It is easy

From Anthropology to Human Geography: Human Terrain and the Evolution of Operational Sociocultural Understanding

Human terrain is a complicated term. It has been plagued with controversy in recent years stemming from US Army implementations in the Middle East. This paper reviews the history of human terrain in three forms: as a human behavioral concept, a conflict based application, and a multidisciplinary area of research. It investigates the history of the term and its evolution from anthropological foundations to human geography and geospatial intelligence. Recommendations are given and practices are suggested to gain knowledge and understanding of people that can assist in helping in hazardous situations and avoiding conflict.

A review of security and privacy concerns in digital intelligence collection

Abstract In recent years, government leaks have brought many alleged potential privacy violating intelligence collection programs to the public arena. Intelligence collection can affect the privacy rights of citizens from any country. While the concept of privacy is a complicated one, United States citizen privacy is protected by various policies and laws. This paper reviews these alleged intelligence collection programs, as well as specific laws set in place to protect privacy. Also presented are discussions on public opinion and whether or not digital intelligence collection are providing a safer environment for Americans.

Geographies of Organized Hate in America: A Regional Analysis

Hate in the United States today is narrowly understood but widely used as a politically charged term. Recently, political blame-placing on outsiders such as immigrants has bred a climate of hate and provided fuel for organizations that promote hostility toward others based on marginal group identification. This study investigates patterns of hate groups across space and their drivers with respect to socioeconomic and ideological variables for counties in the United States. Linear and spatial filtering with eigenvector (SFE) models are used to infer relationships between socioeconomic and ideological variables and the number of hate groups within U.S. counties. Additionally, geographically weighted regression (GWR) is used to identify spatial patterns of those relationships. We find that distinct regions of hate can be delineated with variations of hate group activity according to the independent and control variables employed.

Characterizing and predicting traffic accidents in extreme weather environments

Motorists are vulnerable to extreme weather events, which are likely to be exacerbated by climate change throughout the world. Traffic accidents are conceptualized in this article as the result of a systemic failure that includes human, vehicular, and environmental factors. The snowstorm and concurrent accidents that occurred in the Northeastern United States on 26 January 2011 are used as a case study. Traffic accident data for Fairfax County, Virginia, are supplemented with Doppler radar and additional weather data to characterize the spatiotemporal patterns of the accidents resulting from this major snowstorm event. A kernel density smoothing method is implemented to identify and predict patterns of accident locations within this urban area over time. The predictive capability of this model increases over time with increasing accidents. Models such as these can be used by emergency responders to identify, plan for, and mitigate areas that are more susceptible to increased risk resulting from extreme weather events.