A Geospatial Intelligence Analytics Certificate
Companies and government organizations look for graduates who have excellent geospatial intelligence (GEOINT) knowledge and critical thinking skills. Penn State's online GEOINT Analytics certificate can prepare you to use critical thinking, knowledge of human and physical geography, problem-solving abilities, and geographic information technologies to confront challenges such as disaster response, emergency management, and military operations.
Our online geospatial intelligence analytics graduate certificate program can help you advance your career as a geospatial intelligence analyst — and you can complete the certificate in one year. It is designed to "stand alone" or serve as a "step-up" program into the Master of Geographic Information Systems or Master of Professional Studies in Homeland Security programs.
When you have successfully completed our certificate program in geospatial intelligence, you may apply the credits to either master’s degree, if you are granted admission to enter one of the master’s degree programs.
Geospatial Portfolio Video
Learn more about the World Campus geospatial programs in this video:
Penn State World Campus Provides USGIF-Accredited Education
Penn State's online GEOINT Analytics certificate is fully accredited by the United States Geospatial Intelligence Foundation (USGIF). USGIF's accreditation program was established in 2005 to encourage higher education institutions to develop academic certificates that prepare students to advance the geospatial intelligence field. When you earn a certificate in GEOINT Analytics from Penn State, you will also receive a certificate from the USGIF.
Geospatial Career-Oriented Course Work
All courses are online and instructor led. You'll complete weekly assignments, submit projects online, take quizzes, and receive feedback from faculty. The geospatial course work includes, but is not limited to, geographic foundations of geospatial intelligence, GIS, remote sensing, and additional electives.
Take a Look at Our GEOINT Courses
Familiarize yourself with Penn State's online course work before applying to our program. Visit the Open Educational Resources website to preview GEOINT courses.
Professional Development Courses
If you are a GEOINT professional, you may want to take some of our online courses, such as one of the remote sensing or other electives, to fulfill continuing professional development requirements.
Who Should Apply?
If you are a GEOINT professional working in such fields as national security, disaster response, environmental resource preservation, or business, this certificate program was designed for you.
Career Opportunities for Graduates
Penn State's online certificate in GEOINT Analytics can help start or advance your career as a:
- geospatial intelligence analyst
- midsenior-level geospatial intelligence analyst
- imagery analyst
- intelligence image analyst
- remote sensing scientist or technician
- remote sensing program manager
Information for Military and Veterans
Are you a member of the military, a veteran, or a military spouse? Please visit our military website for additional information regarding financial aid, transfer credits, or application instructions.
Find Out More or Apply Now
For more information on geospatial professional development courses, contact Penn State's College of Earth and Mineral Sciences at [email protected].
Online Education at Penn State
Penn State has a history of 100+ years of distance education and more than a decade of experience in online learning. We create an online learning environment that offers you the same quality education our residential students experience in a face-to-face setting. Learn more about Penn State World Campus.
Explanation of Network Analysis
Network analysis of this type has been ongoing in many sectors for some time. Amazon Inc. has frequently mapped sales of political books to try to present a view of regional political leanings based on sales and “also bought” patterns. Business Week did an article and analysis of this type of data back in the 2012 Presidential election. Although this was sales data of information, it could be tied to a location by its purchase origin and shipping address. One thing to realize here is that there are a couple of biases present – data presented at the state level rather than at some finer degree of granularity and groups of books sold and categorized as either red or blue by Amazon (recall that Amazon makes recommendations to you based on what other people have bought). The article makes this point in its analysis when it attempts to predict the winner based on different levels of such granularity. (Can this be characterized as a reflection of the Modified Areal Unit Problem?)
Books were categorized by political leaning at inherentvice.net and can be presented in Nodes. The take-away here is that one set of sales data can be viewed in two different manners. One is a pure Nodal view and the second one is a more traditional geographic view. Both provide insights that are unique to their view. Recall the heat map in the previous figure. It could not be derived without the link analysis below. Books are grouped by political persuasion as classified by Amazon and then can be mapped, as we saw earlier, by shipping address. The same analysis is often done to detect media biases in the news industry.
Figure 43. Who reads what? There are "Blue" books and there are "Red" books according to the same Amazon sales data. Data about what is read can be analyzed by Nodal Analysis. It has a "geo" component that correlates to "where" it is being shipped. Recall Figure 42?
Credit: Original graphic from inherentvice.net.
|Domain||Questions Given Context|
|Career Planning||How do people network to find jobs?|
|Business Process Re-engineering||Where are the information bottlenecks?|
|Human Resources||Are diversity efforts working?|
|Organizational Design||How should the office be laid out?|
|Knowledge Management||How do innovations spread through an organization? Who are the Subject Matter Experts (SMEs)?|
Figure 44. Areas of interest and examples of context questions amplified via SNA. Look at the resources page on the Navanti website for examples of professional analysis using "Big Data" as a data source.
Original table of questions by M. Thomas.
(The NodeXL plugin has been downloaded and installed as an earlier assignment.)
So how does one decide on hashtags to collect on? An example can be gleaned from the Arab Spring events that toppled President Mubarak in Egypt. There were principal actors (Mubarak), places (Egypt, Tahrir), and even dates (Jan25) when the events were unfolding. So, appropriate tags might be: #Egypt, #Jan25, #tahrir, and #mubarak. The results are all going to be different based on individual insights and choices.
It might be helpful at this point to be getting familiar with the tool NodeXL. There is an excellent exercise I would recommend going through prior to starting your analysis of your own data. There will be two steps to this:
- Download the pdf "NodeXL for Network analysis Hands-on at NICAR 2013, Louisville, Mar 2."
- Download the "US Senate 2007 dataset - the co-voting network of US Senators in 2007."
- Walk through the "Hands On" pdf from Step 1 by importing the dataset into your copy of NodeXL. The goal here is to just get familiar with some of the basic "buttonology" used in a typical analysis. The Tabs after Lesson 7 provide a greater in-depth look at how to import your own data later.
Up until now we have focused on analysis of secondary data sources mostly collected by others. For this project, we will be collecting and analyzing some data on our own using NodeXL and SensePlace2. This will require that we go through a process of evolution that begins with collecting raw data and ends with relevant intelligence. While not part of the assignment, consider the spatial elements in the data throughout the process.
Figure 45. Hierarchy and evolution from data to intelligence.
Image Source. NGA's Open Source Seminar Student Packet.
Do a Google search on a topic of interest to you in GeoPolitics currently trending in the news. Decide on appropriate Hashtags or user accounts, and then collect data that is trending currently. Since the information contained in Twitter is dynamic in nature, the resulting views acquired are going to be very diverse. Using NodeXL, collect data on a set of hashtags, and present your analysis in a short paper with graphics included. The analysis should be 500 words plus or minus 10%. I will not mark down exceeding the target value, but I will mark down for being too short. To use the app on Twitter, a Twitter account is required.
If for a project in real life, the question of credibility of the source has to be in the forefront of any analysts thinking. If you are collecting reports from a number of sources, think about a system for verification. This can be giving the reports you are gathering a good read to make sure they make sense. If your reports need to stand up to the scrutiny of peers, international bodies, or even courts of law, determine a system for verification that is both doable and will stand up to such scrutiny. A good example of a verification process can be found in "The Verification Handbook", a copy of which has been uploaded to the Professional Sources Library in the course material.