GEOG 885
Advanced Analytic Methods for the GEOINT Professional

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Welcome!

New to GEOG 885?

Registered students should begin with the Course Orientation. Please complete the orientation by they beginning of Lesson One.

Not registered? Students who register for this Penn State course gain access to assignments and instructor feedback and earn academic credit. Information about registering for this course and about the online Postbaccalaureate Certificate in Geospatial Intelligence Program is available at https://gis.e-education.psu.edu/geointel.

Quick Facts about GEOG 885

Overview

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.

Your Instructors:

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DENNIS BELLAFIORE: Hello. I'm Dennis Bellafiore with the Geospatial Intelligence Program at Penn State. Looking forward to see you in one of our classes. I've been with the program now for about nine years. I really enjoy the program. I come from the field of physics and really enjoyed the intelligence portion, which really looks at the analysis and looks through the cognitive lens as well as the physical lens as well as the human activity lens. And as we speak about lens, I'll be going up to the photo expo. I go there every year for the last 20 years. Photography is one of my hobbies. And a couple of years back, they started to introduce drones. This year, a lot of time is going to be spent on face recognition. All areas of investigation for the intelligence field. Hope to see you in one of our classes.
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STEPHEN HANDWERK: I'm Steve Handwerk. I'm an associate teaching professor of geospatial intelligence here at Penn State. Thanks for stopping by. Let me tell you a little bit about myself. First of all, I love geography. I always have. I loved it since I was a little boy through grade school. I studied geography at Penn State, and I spent 33 years at the National Geospatial-Intelligence Agency before retiring and coming to Penn State. Geography and geospatial intelligence is so important to our lives because, as General Jim Clapper, former director of National Intelligence and director of NGA, once said, everything happens somewhere. Certainly, along with geography, I love my family. Here you'll see my wife and I on vacation in Hawaii, and then you see my son and his family. They live down in Northern Virginia, and two of our six grandchildren live there. Molly and I like to travel, and when we do, we like to collect some indigenous art. This is from a Pueblo tribe down in New Mexic0-- a wedding vase. And over here we have an Aboriginal wombat from Australia. I'm also a lover of trains-- the real ones and the model ones. Here is a model that runs around our Christmas tree every year. It is of the Lehigh Valley Railroad. And I have that in my blood because my great-grandfather spent a whole career working for Lehigh Valley between New York and Buffalo. Wait. Did I mention that I went to Penn State, and I bleed blue and white? We are!

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.