Carey L Baxter’s research while affiliated with U.S. Army Engineer Research and Development Center and other places

Background:Military and nonmilitary organizations need the capability to support their expeditionary forces by selecting a temporary base of operations that projects a minimal footprint and reduces logistical burdens. For example, strategically sited temporary bases anticipate impacts on the local context and its population of siting and operating temporary bases. Objective:This paper describes a methodology to assess the practicality of incorporating local construction materials when planning for contingency operations in a given region. While the assessment methodology was originally developed for military planners, the principles and methods are applicable to any organization that is considering building and operating temporary locations in foreign nations. Method:The methodology assesses factors such as population densities, main building types, geographical regions, port locations, railroad locations, road networks, airport locations, flood-risk areas, and construction materials. The methodology optimizes all factors to yield the best material-based solution for site selection. To demonstrate the developed methodology, two hypothetical case studies are described–Dhaka in Bangladesh for its high-population density and Maiduguri in Nigeria for its low-population density and potential for disruption. Results:This methodology provides a contingency site selection process that does not currently exist and will assist in the reduction of materiel demand, minimize footprint, and reduce the risk to personnel. The methodology captures factors such as population densities, main building types, geographical regions, port locations, railroad locations, road networks, airport locations, flood-risk areas, and construction materials and optimizes all factors to yield the best material-based solution for site selection. Conclusion:This methodology provides a contingency site selection process that does not currently exist for mission planners. It is designed to produce a methodology with a goal of developing a GIS-based decision support tool to assist in siting bases of operations.

The potential for social media analysis, both in terms of data availability and software development, continues to expand because of easy to use APIs. Twitter has increasingly been used to study various research topics such as election predictions, disease spread, sentiments on public transportation, and how individuals and groups interact within public spaces. However, social media platforms don’t saturate the entire population in a study area, especially emerging nations, only representing more affluent subpopulations. The US Army Corp of Engineers Engineering Research and Development Center (ERDC), in partnership with the University of Illinois CyberGIS Center, is acknowledging and quantifying the utility of demographic information to inform neighborhood scale social media models. Twitter data from the Philippines will be geotagged via intra-Twitter relationships and weight adjusted to demographic surveys and microdata. This research includes text/sentiment and spatial-temporal analysis to provide higher geo-temporal precision to the mapped products. ERDC’s social media analysis tools incorporate quantifiable uncertainties with specific on-the-ground reporting techniques. The resulting maps will augment more authoritative maps to perform risk assessment for humanitarian aid and disaster relief (HADR).

The ready and Department human to respond assistance of to Defense security and disaster threats stands relief (HA/DR) across the globe. Rapid response relies on forecasting probabilities of needs far in advance to ensure that soldiers and materiel are sufficient and adequately prepositioned, which is challenging in rapidly changing human and natural threats. One of those dimensions involves rapid global megacity growth, which can result in ungoverned urban areas attractive as safe havens and recruiting targets for terrorist groups. Forecasting when and where such areas are likely to develop would allow military planners to better anticipate future challenges. Unfortunately, to date computational capabilities to project future growth were developed for developed countries where historic and current land use/land cover data is readily available. As a result, there is a need for inexpensive methods to project urban growth to support the identification of dynamically changing social challenges, where megacities are the most challenging environments forecasting changing conditions. In this article, we present a novel solution using the regional urban growth (RUG) model, a spatially dynamic, extensible approach for assessing the relative attractiveness within cities for various densities of residential growth within a region. This model estimates the attractiveness of development for every location in a rasterized landscape based on proximity to development attractors, such as existing dense development, roads, highways, forest, and water. The level of attraction can vary with distance of the attractor and can even be negative. RUG can be rapidly installed, parameterized, calibrated, and run for any megacity across the globe. Here we illustrate RUG capabilities by applying it to Dhaka, Bangladesh and its surrounding areas. The principal raw data is digital elevation and 8-band, 2m resolution WorldView-2 satellite imagery. Our findings suggest that the RUG model provides a cost-effective means of predicting where urban growth will occur in megacities based on development attractiveness factors derived from sparse, but ubiquitous, global data. This information will improve Department of Defense (DoD) long-term preparation and planning for security and emergency needs within megacities by providing critical neighborhood scale household density information for constructing sociocultural analysis maps.

This paper presents a methodology of mapping population-centric social, infrastructural, and environmental metrics at neighborhood scale. This methodology extends traditional survey analysis methods to create cartographic products useful in agent-based modeling and geographic information analysis. It utilizes and synthesizes survey microdata, sub-upazila attributes, land use information, and ground truth locations of attributes to create neighborhood scale multi-attribute maps. Monte Carlo methods are employed to combine any number of survey responses to stochastically weight survey cases and to simulate survey cases’ locations in a study area. Through such Monte Carlo methods, known errors from each of the input sources can be retained. By keeping individual survey cases as the atomic unit of data representation, this methodology ensures that important covariates are retained and that ecological inference fallacy is eliminated. These techniques are demonstrated with a case study from the Chittagong Division in Bangladesh. The case study illustrates the application of the methodology and the resulting output. The resulting products provide a population-centric understanding of many social, infrastructural, and environmental metrics desired in humanitarian aid and disaster relief planning and operations wherever long term familiarity is lacking. Of critical importance is that the resulting products have easy to use explicit representation of the errors and uncertainties of each of the input sources via the automatically generated summary statistics created at the application’s geographic scale. This set of techniques also aids in identifying locations where more survey sampling is necessary to improve the quality of the products.

Combatant commands (CCMD) develop theater campaign plans (TCP) to organize and align operations, actions, and activities that achieve strategic effect. However, structured data is sparse and planners often rely on the qualitative analysis of subject matter experts (SMEs) when developing theater security cooperation programs. A lack of comprehensive information applied across a broad range of disciplines limits both the options identified and the efficacy of TCP. The U.S. Pacific Command (USPACOM) developed several analytic frameworks to connect theater campaign objectives with the data necessary to support strategic planning. One of these, USPACOM’s humanitarian crisis (HC) framework, defines dozens of social, infrastructural, and environmental indicators aligned to USPACOM needs. Many of the indicators are critical to understanding megacities and other dense urban environments in USPACOM’s area of responsibility. In addition to the challenge of obtaining sufficient information to populate the indicators, it is critical to understand the quality, or uncertainty, of the information. While commanders are accustomed to operating with uncertainty, the ability to methodically characterize uncertainty offers the opportunity to better connect available data to operational decision making. In this article, the authors describe a systematic analysis method and tools designed to help determine whether the available data provides enough credible information for decision making in the context of humanitarian assistance and disaster relief (HA/DR) planning.

The U.S. military may be required to operate in dense urban and megacity environments, which may pose significant challenges for contingency basing. This work reviews and analyzes the potential disconnect between existing doctrine, standard operating procedures, and the human geographic reality of dense urban environments and megacities as concerns contingency basing. The work: (1) characterizes 41 projected megacities using the Army Chief of Staff’s Strategic Study Group’s megacity typology, (2) performs crosswalk analysis between this characterization and existing contingency basing doctrine, (3) details doctrinal gaps, specifically those pertaining to site selection, logistics, and security, and (4) recommends future research to alleviate those gaps.

Socio-Cultural Analysis (SCA) has evolved rapidly over the past decade as conflicts in Afghanistan and Iraq have forced the DOD to reappraise the techniques used to collect information about the populations in conflict zones. As these two major conflicts wind down, the DOD must recognize that SCA must evolve again due the changing responsibilities of phase zero operations while preparing for future conflicts. Given the challenges of declining DOD budgets while improving our SCA capabilities, the chapters in this white volume describe many of the issues facing the DOD for phase zero operations and collecting the socio-cultural information necessary should conflicts escalate. Most of the chapters’ discussions were heavily influenced by LTG Flynn et al.’s “Left of bang: The value of socio-cultural analysis in today’s environment” PRISM article. “Left of bang…” was also revised and included in the SMA/ERDC organized White Volume “National Security Challenges: Insights from Social, Neurobiological, and Complexity Sciences,” available at http://www.nsiteam.com/publications.html. The target audiences are planners, operators, and policy makers. With them in mind, the articles are intentionally kept short and written to stand alone. All the contributors have done their best to make their articles easily accessible.

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