Role of Spatial Data in the Protection of Critical Infrastructure and Homeland Defense

Applied Spatial Analysis and Policy

Volumn 5, Issue 1, 2012, Pages 1-23

  Yates, Justin ^a   Casas, Irene ^b  

^a Department of Electrical and Computer Engineering   (United States)

^b LOUISIANA TECH UNIVERSITY   (United States)

Author keywords

GIS; Homeland security; Network interdiction; Optimization

Indexed keywords

CRITICAL ANALYSIS; DECISION MAKING; GIS; INFRASTRUCTURAL DEVELOPMENT; MILITARY APPLICATION; NATIONAL SECURITY; NETWORK DESIGN; OPTIMIZATION; PROBABILITY; RESOURCE ALLOCATION; SPATIAL ANALYSIS;

CALIFORNIA; NORTHRIDGE; UNITED STATES;

EID: 84857627761     PISSN: 1874463X     EISSN: 18744621     Source Type: Journal    
DOI: 10.1007/s12061-010-9057-1     Document Type: Article

References (18)

1. Anselin, L. (1995). Local indicators of spatial association-LISA. Geographical Analysis, 27, 93-115.
2. Bard, J. (1998). Practical bilevel optimization; algorithms and applications. Boston: Kluwer Academic.
3. Bayrak, H., & Baily, M. (2008). Shortest path network interdiction with asymmetric information. Networks, 52(3), 133-140.
4. Bier, V., Haphuriwat, N., Zimmerman, J., Menoyo, R., & Culpen, A. (2008). Optimal resource allocation for defense of targets based on differing measures of attractiveness. Risk Analysis, 28(3), 763-770.
5. Brown, G., Carlyle, M., Salmeron, J., & Wood, K. (2006). Defending critical infrastructure. Interfaces, 36(6), 530-544.
6. Department of Homeland Security. (2008). Homeland security advisory system. http://www. dhs. gov/xinfoshare/programs/Copy_of_press_release_0046. shtm (accessed April 18, 2008).
7. Getis, A., & Ord, J. K. (1996). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206.
8. Grubesic, T. (2010). Sex offender clusters. Applied Geography, 30, 2-18.
9. Israeli, E., & Wood, K. (2002). Shortest-path network interdiction. Networks, 40(2), 97-111.
10. Kies, U., Mrosek, T., & Schulte, A. (2009). Spatial analysis of regional industrial clusters in the German forest sector. International Forestry Review, 11(1), 38-51.
11. Lim, C., & Smith, J. C. (2007). Algorithms for discrete and continuous multicommodity flow network interdiction problems. IIE Transactions, 39, 15-26.
12. List, G., Mirchandani, P., Turnquist, M., & Zografos, K. (1991). Modeling and analysis for hazardous materials transportation: Risk analysis, routing/scheduling and facility location. Transportation Science 25, no. 2.
13. Montgomery, D. (2001). Design and analysis of experiments. New York City: Wiley.
14. Nemhauser, G., & Wolsey, L. (1999). Integer and combinatorial optimization. New York: Wiley-Interscience.
15. U. S. Census Bureau. (2008). TIGER/Line and TIGER-related products. http://www. census. gov/geo/www/tiger/ (accessed August 1, 2008).
16. Willis, H. (2007). Guiding resource allocations based on terrorism risk. Risk Analysis, 27(3), 597-606.
17. Zhang, T., Madhani, S., Berg, E. V. D., & Mohanty, S. (2005). Sensor on patrol (SOP): Using mobile sensors to detect potential airborn nuclear, biological, and chemical attacks. Military Communications Conference 2005, MILCOM 2005. IEEE. 2924-2929.
18. Zhuang, J., & Bier, V. (2007). Balancing terrorism and natural disasters-defensive strategy with endogenous attacker effect. Operations Research, 55(5), 976-991.