Jon T. McCloskey

Spatial Analyst

Jon McCloskey is a Spatial Analyst with a background in Ecology and Environmental Scientist. He has extensive experience with Bayesian networks (BN), spatial analysis, and remote sensing. Dr. McCloskey has several years of research and management experience involving land use decisions and natural resource management. Dr. McCloskey has facilitated several workshops that use BN to link data and expert knowledge as way of addressing uncertainty for complex decision making. During his Postdoctoral work, his research team developed a low cost, rapid assessment method that uses expert and stakeholder knowledge to deal with uncertainty of the influential and causal relationships between spatial data and various land use decisions. The process uses participatory modeling strategies to identify important GIS and remotely sensed data, build BN models, identify causal relationships, run different scenarios, and interpret the results. The process can be used to mitigate potential conflict among competing land use values and to help target, prioritize, and choose among different spatial alternatives. These methods have practical applications for several government communities including intelligence, defense, homeland security, drug enforcement, transportation, health, and natural resources. 

Dr. McCloskey teaches part of IDI’s Introductory BN course on using Netica/Geo-Netica to link expert knowledge and spatial data. He is also working on IDI’s team to further develop their Calibrated Baseline Model Project for the U.S. Navy’s Operational Logistics Energy Conservation office. The team has developed statistical models of vessel energy consumption to produce high quality forecasts of energy conservation initiative effectiveness and assess efficacy of installed initiatives. Dr. McCloskey also works with IDI’s STARLite team facilitating workshops to elicit expert knowledge used to create decision support tools for the U.S. Army CECOM. Dr. McCloskey’s work uses remote sensing, GIS, and Bayesian network software.


Education

University of Maine. Ph.D. in Ecology & Environmental Sciences with minor in Remote Sensing.
Texas A&M University-Kingsville. M.S. in Range & Wildlife Sciences with minor in tatistics.
University of Montana.  B.S. in Wildlife Biology.


Selected Publications and Presentations

Acheson, J. M. and J. T. McCloskey. 2010. The causes of deforestation: the Maine case. In: D. Bates and J. Tucker (eds.), Human Ecology: Contemporary Research and Practice. Springer, New York, N.Y., pp. 331- 348.

McCloskey, J.T., R. Llieholm, R. Boone, R. Reid, S. Sader, D. Nkedianye, M. Said, and J. Worden. 2011. Using Bayesian Belief Networks to Integrate Spatial Data and Expert Knowledge for Sustainable Development. In: C.A. Brebbia and E. Tiezzi (eds.), Ecosystems and Sustainable Development VIII. WIT Press, United Kingdom.

McCloskey, J.T., R. Llieholm, and C. Cronan. 2011. Using Bayesian Belief Networks to Identify Potential Compatibilities and Conflicts between Development and Landscape Conservation. Landscape and Urban Planning 101:190-203.


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