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The Structured Geospatial Analytic Method (SGAM) is both as an analytic method and pedagogy for the Geospatial Intelligence professional.〔Bacastow, T.S. and Bellafiore, D.J. (2008-2010). The Learner's Guide to Geospatial Analysis. Penn State University. https://www.e-education.psu.edu/sgam/〕 This model was derived from and incorporates aspects of both Pirolli and Card’s sensemaking process〔Pirolli, P. and Card, S. K. (2005). The sensemaking cycle and leverage points for analyst technology as identified through cognitive task analysis. In Proc. Int'l Conf. on Intelligence Analysis'05, 2-4.〕〔Klein, G., Moon, B., and Hoffman, R. (2006). Making sense of sensemaking 1: Alternative perspectives. Vol. 21 (4). IEEE Intelligent Systems.70-73.〕 〔Perry, J., Janneck, C.D., Umoja, C., and Pottenger, W.M. (2009). Supporting Cognitive Models of Sensemaking in Analytic Systems. DIMACS Technical Report 2009-12. http://dimacs.rutgers.edu/TechnicalReports/TechReports/2009/2009-12.pdf〕〔Russell, D. M., Stefik, M. J., Pirolli, P., & Card, S. K. (1993). The cost structure of sensemaking. Paper presented at the INTERCHI '93 Conference on Human Factors in Computing Systems, Amsterdam.〕〔Sieck, W., Klein, G., Peluso, D.A., Smith, J.L. and Harris-Thompson, D. (2007). FOCUS: A Model of Sensemaking. United States Army Research Institute for the Behavioral and Social Sciences.〕〔Zhang, P., Soergel, D., Klavans, J.L., & Oard, D.W. (2008). Extending Sense-Making Model with Ideas from Cognition and Learning Theories. In proceedings of the ASIS&T 08 Annual Conference. (Oct 2008, Columbus, Ohio). http://terpconnect.umd.edu/~pengyi/files/zhang-08-asist-sense-making-final.pdf〕 and Richards Heuer’s Analysis of Competing Hypotheses model.〔Heuer, R.J. (1999). Psychology of Intelligence Analysis. Center for the Study of Intelligence, Washington, D.C.〕〔Wheaton, K. J. and Chido, D.E. (2006) Structured analysis of competing hypotheses: Improving a tested intelligence methodology. Competitive Intelligence Magazine; vol. 9 (6). 12-15.〕 This is a simplified view of the geospatial analytic process within the larger intelligence cycle. The SGAM is intended to advance the Geospatial Intelligence tradecraft by providing an approach not only to teach the analyst how forage and repackage data, but also how to analyze the data in a meaningful way. It has been long known that without specific prompting, people may be unaware of spatial patterns of an environment 〔Golledge, R.G. (1992). Do people understand spatial concepts: The case of first-order primitives. University of California at Santa Barbara. Presented at the International GIS Conference, Pisa, Italy. pp. 1-22.〕 and, similar to other areas of intelligence analysis, the geospatial analyst has the human tendency to:〔Heuer, R.J. (1999). Psychology of Intelligence Analysis. Center for the Study of Intelligence, Washington, D.C.〕 * unconsciously discount much of the relevant information * mentally simplify the task and likely oversimplify the results * make judgments that are subject to unconscious biases, blind spots, and limitations of working memory. Spatial thinking that goes beyond a simple identification of locations is key to applying the SGAM. This thinking involves comparing locations, considering the influence of nearby features, grouping regions and hierarchies, and identifying distant places that have similar conditions. It is also the consideration of change, movement, and diffusion through time and place.〔Gershmehl, P.J. and Gershmehl, C.A. (2006). Wanted: A concise list of neurologically defensible and assessable spatial-thinking skills. Research in Geographic Education, 8, 5-38.〕 Spatial thinking then proceeds to examine the places and compare places in the context of space and time. The method is organized into two major loops: *A foraging loop aimed at seeking information foraging, searching, and filtering it, and reading and extracting information. *a Sensemaking loop that involves iterative development of a mental model from the schema that best fits the evidence. The foraging loop recognizes that analysts tend to search for data by beginning with a broad set of data and then proceeding to narrow that set down into successfully smaller, higher-precision sets of data, before analyzing the information. The three foraging actions including exploring for new information; narrowing the set of items that has been collected; and exploiting items in the narrow set; trade off against one another under deadline or data overload constraints. It is important to note that much geospatial intelligence work may never depart from the foraging loop and can simply consist of extracting information and repackaging it without much actual analysis since the production of maps is oft the role that the analyst fulfills. Sensemaking is the ability to create situational awareness and understanding in situations of high complexity or uncertainty in order to make decisions. It is “a motivated, continuous effort to understand connections (which can be among people, places, and events) in order to anticipate their trajectories and act effectively”.〔Klein, G., Moon, B., and Hoffman, R. (2006). Making sense of sensemaking 1: Alternative perspectives. IEEE Intelligent Systems, 21 (4), 70-73.〕 Pirolli discusses the importance of using a cooperative approach to sensemaking as it yields a greater diversity of knowledge and reduces the risk of missing relevant information.〔Pirolli, P. (2009). An elementary social information foraging model. 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