Geospatial Technologies and Homeland Security

In the aftermath of the terrorist attacks of September 11, homeland security has not only become a top priority of US government policies at all levels (National Governors’ Association 2006; Homeland Security Council 2007), it also has become an emerging field of study (Bullock et al. 2006). Homeland security presents an enormous opportunity but also poses daunting challenges for higher education (National Research Council 2005). Despite the diverse interpretation of the term ‘homeland security,’ existing literature can be grouped in two categories: either narrowly defined as dealing with intentional, human-induced terrorist attacks, or more broadly defined as dealing with any disasters of technological, natural, and human origin. This book takes the broader view.

Regardless of how homeland security is defined, the tasks it deals with typically follow more or less the same cycles of response in a typical emergency situation: detection, preparedness, prevention, protection, rescue, relief, recovery, and reconstruction (Cutter 2003). Although data needed in each phase of an emergency response may differ in spatial and temporal scales, government agencies and citizens need access to real-time, multiple types of general information, as well as accurate geospatial information in order to accomplish many of the tasks during an emergency response situation (Briggs et al. 2002; National Commission on Terrorist Attacks upon the United States 2004; Patterson and Apostolakis 2007).

The classic buffer state of Afghanistan, created to avoid confrontation in the 19th century, has in the 21st century become a focal point for armed conflict that can only be alleviated by attention to the country’s problems, many of which can be studied or alleviated through geospatial technologies. Instead of the present weakness and ineptitude, a Marshall-Plan style of post-war rebuilding could have led to a robust Islamic democracy instead of re-energization of the Taliban and the creation of other problems hindering the country’s reemergence from its long national nightmare. Winning every battle could still result in losing the overall war for Afghanistan unless stronger redevelopment measures are undertaken promptly.

Large metropolitan regions are vulnerable to terrorist attacks and natural disasters. Ports and downtown business districts could be targets of terrorist attacks and are also prone to substantial losses from natural disasters like earthquakes or hurricanes. It is important for stakeholders and decision makers to be aware of the spatial distribution of these losses and recognize the potential economic losses from various hypothetical terrorist attacks and natural disasters on these crucial facilities and core sites. The Southern California Planning Model (SCPM), a GIS-based regional planning model developed initially for the five-county Los Angeles metropolitan area, is capable of endogenizing freight and passenger flows and allocating impacts spatially via unexpected impedances to trips and shipments through the regional highway network. This chapter presents the SCPM model and describes several applications via three case studies of hypothetical events: (1) A radiological bomb or so-called „dirty bomb“ attack and conventional bomb attacks on the twin ports of Los Angeles and Long Beach; (2) A radiological bomb attack on a large office building in Downtown Los Angeles Financial District; and (3) A hurricane striking the Houston-Galveston-Brazoria (HGB) region. The results show that the model can allocate the losses to various types of impact analysis zones or political jurisdictions. The methods used in this study are adaptable to almost any kind of terrorist and natural disaster attacks and also transferable to other large metropolitan areas.

This chapter presents a review and interpretation of the use of small area neighborhood profiles (geodemographics) in community policing and, by extension, in homeland security applications. We discuss the merits of a local focus in policing, and the data and analytical frameworks that are necessary to support this activity. Next we use case study examples to illustrate how priorities for neighborhood policing may be developed, and suggest that available public sector data may be used to drive improved bespoke classifications of neighborhoods. It is argued that better measures of local social capital and community cohesion may be used to tailor interventions to local circumstances, and to maintain and enhance community stability. We conclude with an overview of some ethical impediments to development of such approaches in homeland security applications.

Commonly known as the ‘Troubles,’ the disputes between Irish republicans (mostly Catholics) and British unionists (mostly Protestants) in Northern Ireland have lasted for decades and since the late 1960s have claimed around 3,600 lives. Military intervention by the British Army eventually undermined the activities of the main paramilitary groups (Irish Republican Army that sought the unification of Ireland and the Ulster Volunteer Force and Ulster Freedom Fighters who wished to maintain Northern Ireland’s constitutional position within the United Kingdom). Northern Ireland is now slowly transforming out of conflict, but as it does so, more debates become concerned with interpreting the past and the nature and meaning of victimhood.

This chapter maps the spatial distributions of conflict-related deaths in Belfast (Northern Ireland’s principal city) in an attempt to unravel the complex social, political, and ethno-religious underpinnings of the Troubles. Religious segregation is claimed by many analysts to be a major contributory variable to explaining the pattern of conflict-related deaths, and as such we explore a modification of the spatial segregation index to examine the distribution of Catholic and Protestant neighborhoods in Belfast. After analyzing the extensive database of deaths and their spatial occurrence, the chapter ends with a series of lessons. Most notably, politically motivated attacks can be unpredictable but also seem to cluster within highly segregated and low social class neighborhoods located within close proximity to interfaces between Catholic and Protestant communities. In addition, paramilitary attacks are difficult to profile demographically, and the vast majority involve civilian casualties.

Among the many internal national security issues facing society today, significant focus has been placed on means to protect our nation’s children from sexual predators. A number of laws have been passed, typically named after the tragic child victims of sexual attacks. Individually, these laws mandate creation and maintenance of registries for convicted offenders, establish safety zones from which known offenders are restricted, and require notification to neighbors of the presence of registered offenders in neighborhoods.

Almost all of these laws have spatial impacts. Registries identify sex offenders’ home addresses. Safety zones are formed by buffers of varying distances around places where children typically gather. Notification laws require that neighbors within specific distances of an offender’s home must be notified of their presence. All of these laws specifically apply to offenders who are known, convicted, and registered.

In each case, these laws impose economic and societal costs for implementation and enforcement. Considering their inherent spatial nature, little is understood regarding spatial justification for implementing these laws or impact from their enforcement. This chapter describes the use of spatial analysis to examine the effectiveness of sex offender laws in Brazos County, Texas.

For natural or anthropogenic disasters, rapid assessment is critical for an appropriate and effective emergency response. Remote sensing has served—and will continue to serve—a vital function in disaster damage-assessment activities. This includes disaster-mapping of natural and agricultural ecosystems and human settlements, which may involve assessments of structural damage, contamination, and affected populations. Single- and multi-date (change detection) analyses can be employed, and a need to exploit both spectral and spatial information in order to delineate damage regions from remote sensor imagery is identified. This chapter provides a brief overview of some of the remote-sensing damage-assessment applications that are of utility in the realm of homeland security. Specific attention is given to remote sensing-based detection of vegetation damage and soil contamination, including a discussion of the remote-sensing implications of artificial radionuclide contamination, as well as damage to urbanized areas and other human settlements.

Floods continue to pose the greatest threat to the property and safety of human communities among all natural hazards in the United States. While the link between urbanization and flooding is established, the degree to which specific characteristics of the built environment affect the level of damage sustained by a community has never been thoroughly investigated at the regional scale. Our study addresses this lack of research by examining the relationship between the built environment and flood impacts in Texas, which consistently sustains the most damage from flooding more than any other state in the country. Specifically, we calculate property damage resulting from 423 flood events over a five year period between 1997 and 2001 at the county level. We identify the impact of several built environment measures, including wetland alteration, impervious surface, and dams on reported property damage while controlling for biophysical and socioeconomic characteristics. Statistical results suggest that naturally occurring wetlands play a particularly important role in mitigating flood damage. These findings provide guidance to homeland security experts and flood managers on how to most effectively mitigate the costly impacts of floods at the community level.

In evacuation planning, it is advantageous for community leaders to have a thorough understanding of the human and geophysical characteristics of a community, be able to anticipate possible outcomes of different response and evacuation strategies under different situations, inform the general public, and develop a set of evacuation plans accordingly. In order to achieve this goal, evacuation managers in a community can use computer modeling techniques to simulate different ‘what-if’ scenarios, use the results from these simulations to inform the public, and generate different evacuation plans under different circumstances. The complexity associated with evacuation planning in an urban environment requires a computer modeling framework that can incorporate a number of factors into the modeling process. These factors include the nature of the disaster in question, the anticipated human behavioral patterns in the evacuation process, the unique geography and transportation infrastructure in a given area, the population distribution in the area, the population dynamics over different time periods, and the special needs of different population groups, to name a few. Agent-Based Modeling (ABM) provides a general approach that can be used to account for these factors in the modeling and simulation process. In this chapter, the authors provide an overview of agent-based modeling and simulation, illustrate how agent-based modeling and simulation were used in estimating the evacuation time for the Florida Keys, and report some preliminary results in planning a hypothetical route for evacuating the elderly from a nursing home on Galveston Island, Texas, based on network dynamics during an evacuation.

This chapter begins with an assessment of the reasons for the current surge in interest in developing building evacuation analysis using models that focus explicitly upon the human individual’s locus of behavior. We then present an extended overview of available software for modelling and simulating pedestrian evacuation from enclosed spaces, and use this to develop guidelines for evaluating the wide range of pedestrian evacuation software that is currently available. We then develop a sequential conceptual framework of software and model specific considerations to take into account when contemplating application development. This conceptual framework is then applied to a hypothetical building evacuation setting. Our conclusions address not only the efficiency and effectiveness of the software solutions that are currently available, but also the degree of confidence (broadly defined) that underpins their application.

The coastline is a long, narrow hazard zone vulnerable to storm surge or tsunami as well as to the much slower rise in relative sea level associated with climate change and crustal subsidence. Effective planning for coastal hazards depends upon reliable climatological and tidal data, monitoring networks able to detect large rotating storms or distant undersea earthquakes, and refinement of computer simulation models like SLOSH (Sea, Lake, and Overland Surges from Hurricanes), developed in the 1970s and used for three decades by the National Weather Service to identify areas requiring evacuation. SLOSH, which accommodated 1970s computers with a coarse systematic grid unable to capture the effects of irregular shorelines and small features that can accelerate or attenuate sudden inundation by wind-driven seas, epitomizes the need for better models and more refined elevation data. Reliable modeling is important because the time-consuming evacuation of large coastal populations is thwarted by the unnecessary clearing of areas not at risk. Improved planning for severe coastal storms is possible with more computationally efficient models based on high-resolution, unstructured grids and able to account for wave action as well as topographic irregularities. Although these advanced models require refined elevation data—as do credible projections of sea level rise—for many parts of the United States coast the best current elevation data are derived from obsolete topographic maps with a five- or ten-foot contour interval. Topographic lidar, which can provide a half-foot vertical resolution, is a promising solution to the pressing need for better coastal elevation data. Integration with bathymetric lidar, which can image the sea floor in water as deep as 20 to 30 meters, yields a seamless topographic/bathymetric dataset useful for the high-resolution modeling of storm surge.

Area-wide pest management essentially represents coordinated adoption of integrated pest management to conduct preventive suppression of a pest species throughout its geographic distribution. Scientists and researchers in area-wide pest management programs have been developing, integrating, and evaluating multiple strategies and technologies into a systems approach for management of field and crop insect pests. Remote sensing, Global Positioning Systems, geographic information systems, and variable rate technology are additional tools that scientists can implement to help farmers maximize the economic and environmental benefits of area-wide pest management through precision agriculture.

Precision area-wide pest management systems were originally developed to reduce the country’s daily risk of natural pest introductions. Now the systems are being developed to reduce the daily risk the country faces of pest introductions, both natural and intentional. Aerial application under precision area-wide pest management strategy is one of the most feasible methods to quickly limit the threat of area-wide pest infestations, which increased after the terrorist attacks of September 11, 2001.

Modern epidemiology is founded on a tradition of spatial analysis. The genesis of this discipline can be traced to the classic work of John Snow and the Broad Street pump. During the 1850s, cholera outbreaks were an important cause of morbidity and mortality amongst the inhabitants of London. Using simple dot maps and visualization, Snow provided compelling evidence that cases were clustered and that fecal-contaminated drinking water might be the cause of some cholera outbreaks. During the intervening 150 years, spatial epidemiology (alternatively called landscape epidemiology and more broadly, medical geography) has developed into a field within its own right. During the past two decades, advances in geographic information systems and statistical methods for analyzing spatially-referenced health data has allowed epidemiologists to routinely perform spatial analyses. Some of the most beneficial advances in spatial epidemiology have been in the areas of data visualization, detection of disease clusters, identification of spatial risk factors, application of predictive models, and the routine incorporation of GIS into disease surveillance programs. In this chapter, approaches used in spatial epidemiology will be described. Some specific techniques that are currently popular in the discipline will be presented. Several case studies will be used to highlight the application of these techniques within the field of spatial epidemiology and to illustrate the potential value of this discipline to public health and homeland security. The chapter will conclude by considering some of the major obstacles that remain to the consolidation of spatial analysis as a foundation of modern epidemiology, including the availability and quality of spatial disease data, information on the distributions of the populations at-risk, and integration of methods seamlessly into epidemiologic software packages.

This chapter examines the role of geographic information technologies (GIT) in the production of the politics of fear. While technologies such as mapping and GIS appear to offer a fix or solution to problems of terrorism, crime, or disaster, they can contribute to the use of fear for political exploitation. What sustains this politics of fear? This chapter suggests that if GIT continue to produce knowledge of populations in terms of risk, then a politics of fear can be exploited to justify mass geosurveillance. In this light, two case studies are examined; nineteenth century mapping and contemporary crime mapping.

We live in uncertain times. Although we cannot eliminate uncertainty and its effects, it is important to minimize the disruption and loss that result from it. Mitigating the negative effects of uncertainty, especially by applying geospatial technologies, requires spatial thinking skills. We argue that teaching students how to use geospatial technologies will not enable them to deal with uncertainty unless they also learn to think spatially. Spatial thinking can be learned and should be taught. Results from classroom-based research provide guidance in developing effective ways to teach spatial thinking and geospatial technologies.

The future stacks up to be a very dangerous place. To meet homeland security challenges, integrated solutions that cross discipline boundaries and incorporate new technologies like Geographic Information Systems (GIS) are required. Constructing an integrated homeland security curriculum in our classrooms today can help to shape a safer future. Developing such a curriculum that successfully incorporates the full potential of geospatial solutions including Geographic Information Systems (GIS) requires efforts on the part of GIS experts. These professionals must learn the challenges and the components of the solutions, and find ways to incorporate their expertise into those solutions and then convince experts in other disciplines who remain skeptical of unproven programs and unfamiliar technologies, of the potential benefits of integrating GIS into homeland security education.

The acronym GIS can be decoded in three distinct ways: GISystems, GIScience, and GIStudies. This framework is used to provide an overarching synthesis, and to ask whether the chapters of the book provide a complete picture of geospatial issues and applications to homeland security. Three characteristics distinguish homeland security applications from other domains: the need for speed; the difficult environments in which technology must operate; and the impossibility of anticipating many relevant kinds of events in either space or time. One of the strongest factors impeding the effective use of geospatial technologies is lack of collaboration between institutions and the cultures of emergency response and GIS. The final section identifies four themes that are largely missing from this book, but nevertheless represent opportunities and challenges for the future.