A terrain risk assessment method for military surveillance applications for mobile assets |
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| Affiliation: | 1. Missouri State University, Glass Hall 200, Springfield, MO 65897, United States;2. Womply/Oto Analytics, 188 King Street, San Francisco, CA 94107, United States;1. University of Duisburg-Essen and Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), Schaumburg-Lippe-Strasse 5-9, D-53113 Bonn, Germany;2. Narodowy Bank Polski and Warsaw School of Economics, al. Niepodległości 162, 02-554 Warsaw, Poland;3. Centre for European Policy Studies, 1 Place du Congres, 1000 Brussels, Belgium;1. School of Statistics, Zhejiang Gongshang University, Hangzhou, PR China;2. Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong, PR China;1. Director, Oral Design Center of Los Angeles, Herman Ostrow School of Dentistry, University of Southern California, Los Angeles, Calif;2. Former resident, Division of Advanced Prosthodontics, Herman Ostrow School of Dentistry, University of Southern California, Los Angeles, Calif;3. Professor and Program Director, Advanced Prosthodontics, Herman Ostrow School of Dentistry, University of Southern California, Los Angeles, Calif;4. Assistant Professor, Division of Advanced Prosthodontics, UCLA School of Dentistry, University of California, Los Angeles, Calif;1. Helmholtz-Zentrum Geesthacht, Max-Planck Straße 1, 21502 Geestacht, Germany;2. Fakultät Physik/DELTA, 44221 Dortmund, Germany;3. Fakultät Chemie, Physikalische Chemie II, Otto-Hahn-Straße 6, 44227 Dortmund, Germany;4. Deutsches Elektronen-Synchrotron, Notkestraße 85, 22607 Hamburg, Germany |
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| Abstract: | This study proposes an analytical and flexible terrain risk assessment method for military surveillance applications for mobile assets. Considering the risk as the degree of possibility of insurgent presence, the assessment method offers an efficient evaluation of risk in the surrounding terrain for military combat operating posts or observation posts. The method is designed for unmanned aerial vehicles as the surveillance assets of choice to improve the effectiveness of their use. Starting with the area map and geographical data, the target terrain is first digitized for space representation. Then the data of nine geographical parameters are used to formulate five contributing risk factors. These factors are incorporated in an analytical framework to generate a composite map with risk scores that reveal the potential high-risk spots in the terrain. The proposed method is also applied to a real-life case study of COP Kahler in Afghanistan, which was a target for insurgent attacks in 2008. The results confirm that when evaluated with the developed method, the region that the insurgents used to approach COP Kahler has high concentration of high-risk cells. |
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| Keywords: | Unmanned aerial vehicles Military surveillance Terrain assessment Risk Terrain Modeling |
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