GEOG 885
Advanced Analytic Methods in Geospatial Intelligence

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Meet Your Instructor:

Meet David Jimenez, instructor of GEOG 885 (0:51 minutes).

Click here for a transcript of the meet the instructor video.

Hello everyone. I'm David Jimenez, an adjunct instructor with the geospatial program here at Penn State and located in the southwest town of El Paso. A little bit about me. I'm retired from the United States Air Force, having served 24 years as an intelligence analyst. I then had another career in intelligence for 22 years with federal law enforcement, and then finally in my third career with a counter-drug program called the High Intensity Drug Trafficking Area. I have a passion for all things intelligence with the nexus to analysis and structured methods in the courses that I instruct. I'm an amateur photographer who hasn't quite figured out all the bells and whistles of a nice camera that I have, but I'm working on it. Looking forward to seeing you in class!

Credit: David Jimenez © Penn State is licensed under CC BY-NC-SA 4.0


The traditional approach to geospatial analysis is the intuitive technique. In order to improve analysis, relatively uncomplicated methods exist to help intelligence analysts structure their analysis. These structured methods, which can be applied to a broad range of problems, provide a scientific-like and demonstrable approach to analysis that can enhance the intelligence analyst objectivity. Structured methodologies do not replace the subjective insight of the intelligence analyst. Instead, the intent is to use a logical framework to illustrate and capitalize on intuition, experience, and judgment. A structured methodology provides a traceable and repeatable means to reach a conclusion. Significant for us, structured methods have significant value in that they can be taught. Structured methodologies are severely neglected in the geospatial realm. This course teaches the theory and practice behind a structured analytic method designed for geospatial intelligence, with particular emphasis given to selecting and applying appropriate analysis techniques to create and test hypotheses. Students will assess the various connotative biases and spatial fallacies that interfere with sound spatial thinking. Students also appraise basic analysis techniques including imagination, diagnostic, and challenging & reframing.

Learning Environment

This Web site provides the primary instructional materials for the course. The Resources menu links to important supporting materials, while the Lessons menu links to the course lessons. In addition, Canvas, Penn State's course management system, is used to support the delivery of this course, as well as to provide the primary communications, calendaring, and submission tools for the course.