Graduate Programs in Geospatial Intelligence

The program is offered through the Department of Geographical Sciences in the College of Behavioral and Social Sciences. Geospatial Intelligence provides workforce-focused technical training that gives graduates the skills and expertise to lead new initiatives in the rapidly shifting landscape of GEOINT applications, data collection systems, analytic methods, and mission support. 

Mentoring and advising are an essential part of the program. Students meet with faculty and the academic program director to ensure that educational goals and career learning and development goals are met. Students should contact Professor Ruibo Han, via email: ruibo@umd.edu. 

Overview

The Master of Science in Geospatial Intelligence has a 30-credit, 10-course curriculum that provides workforce-focused training to respond to a rapidly shifting landscape of applied problem-sets, analysis schemes, big and growing data-sets, and software platforms that characterize today’s geospatial intelligence. 

• Offered in person (major code GEIN) or online (major code GINO). The curriculum is identical in each delivery format.
• State-of-the-art training in the geospatial technologies (e.g., web mapping, mobile applications, geospatial programming), geographical knowledge (e.g., geostatistics, geospatial networks, spatial reasoning), and scientific methods to address issues of public administration and policy analysis; public safety; criminology; military intelligence; emergency response and preparedness; project and workflow management; environmental applications; urban studies and regional sciences; and transportation geography.
• Students acquire the knowledge and practical skills in geographic information science & technology (GIS&T), remote sensing, mapping and geo-visualization, computer programming to tackle geospatial intelligence problems such as pattern recognition and feature extraction, big geospatial computing, developing source-to-screen workflows, and communicating uncertainty to decision-makers.
• Skills range from project design, data collection and interoperation, software development, algorithm implementation, data-mining, analytic processing and management, visualizing results and reporting. Technical skills are closely intertwined with substantive topics in a range of applied geospatial intelligence contexts, from defense and homeland security to humanitarian response and emergency management.
• Can be completed in fifteen months of continuous full-time enrollment. See Designation of Full-time/Part-time Status.

Program Features

Curriculum offers fundamental and advanced courses in three main areas:

• Fundamentals of geospatial intelligence science and technology;
• Geospatial data handling processes using advanced algorithms, models, and commercial and open-source platforms; and
• Support systems for applying geospatial intelligence in behavioral and social science, emergency and security management, and computational science.

GEOG697: Capstone Project (core course):

• An independent research project that demonstrates competence in geospatial intelligence technologies. 
• This project can originate from an internship, from relevant work at a current or past employer, or can be developed in conjunction with CGIS faculty. 
• The student prepares a project report and presentation which contains an executive summary, background information including a literature review and establishment of requirements, a detailed technical description of the project data and methods, a discussion of results obtained, and final conclusions and recommendations. 
• The final project submission includes all data, computer code and/or workflow documentation required to replicate the project results. 
• In completing this project, students develop a concrete example of how GEOINT technologies can be applied to solve real-world problems, and begin developing a portfolio that can be presented to potential employers.

Plan of study includes five 3-credit core courses (15 credits) and five 3-credit electives (15 credits). 

Registration Overview

• See the sample plan of study, below. Students should use this as a guide to develop a plan with the academic program director.  
• Actual course offerings are determined by the program and may vary semester to semester. Students should note if a course has a pre-requisite or co-requisite. 
• Specific class meeting information (days and time) is posted on UMD’s interactive web service services, Testudo. Once on that site, select “Schedule of Classes,” then the term/year. Courses are listed by academic unit.   
• Due to visa requirements, international students admitted into the in-person learning option (major code GEIN) are required to register for on-campus sections and attend lectures in-person.
• The program uses specific section codes for registration, which are listed on the sample plan of study.

Sample Plan, Fall Admission

Sample Plan, Spring Admission

Courses

For a listing of program courses, see the Graduate School Catalog program requirements for GEIN and GINO. For course descriptions that includes pre-requisites or co-requisites, see GEOG.

Overall

• Program offers two learning options: in person (major code GEIN) or online (major code GINO). The curriculum is identical in each delivery format.
• Uses the term academic calendar with classes held each 12-week term: I (fall), II (winter), III (spring), IV (summer).
• Classes are held weekday evenings (e.g., after 5:00 p.m.) to accommodate the working professional’s schedule.
• Instruction provided by University of Maryland faculty and professionals in the field. 

In-Person Learning 

• Classes meet in UMD College Park campus classrooms, offering a focused, distraction-free learning environment. 
• Instructors present dynamic and interactive seminar-style instruction.
• Lectures are video archived. Students who are unable to attend a class session can review the session at their convenience.
• Students enrolled in a program that features in-person instruction are required to submit the University’s Immunization Record Form prior to the first day of their first semester/term. See Health Requirements. 

Online Learning

• Using advanced audio and video technology, UMD’s online learning environment delivers dynamic and interactive content. 
• Featuring convenience and flexibility, online instruction permits asynchronous or synchronous participation.
• Lectures are video archived. Students who are unable to attend in real time can review the session through asynchronous participation.

Upon successful completion, graduates will have mastered the following competencies:

• A well‐rounded understanding of the fundamental nature of geospatial intelligence and analysis, including the core theory, methods, and protocols for gathering and management of geospatial intelligence data, analyses and visualization of those data, use of the resulting products in operational settings for applied geospatial intelligence, and the ethical treatment of data and analysis throughout those procedures.
• Advanced expertise in either or both of the challenges and opportunities for geospatial intelligence in human, security, and engineering domains; and technologies for future geospatial intelligence and analysis in computing, machinery, and software.
• Practical, hands‐on project and lab‐style training with data collection procedures, data analysis, algorithm development, using commercial and open source modeling and analysis software and platforms.
• The ability to design and implement strategies to solve real‐world intelligence problems as they present across a variety of domains, including intelligence activities, security and defense, hazards and emergency response and management, and transportation and urban applications.
• Training in analytic thinking and real‐world problem solving for future success in the workforce. Skills include but are not limited to interpersonal communications and teamwork, creative and critical thinking, occupational planning and organizing, problem‐solving, and decision making.