GEOG 885
Advanced Analytic Methods in Geospatial Intelligence

Geography 885 Syllabus

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GEOG 885: Advanced Analytic Methods in Geospatial Intelligence

Summer 2023

You can print the entire syllabus by clicking on the "Print" link in the upper right-hand corner of this page. You can also just print the course schedule--there is a link for a printer-friendly version of the schedule there. That being said, it is essential that you read the entire document as well as the material covered in the Orientation. Together these serve the role of our course "contract."


GEOG 885 Prerequisite

There are no prerequisites for this course.


Instructors

The instructor rotates by semester. Review the "Meet the Professor" page in the orientation to learn more about your instructor for the semester. 

  • Leanne Sulewski

    • Email: Please use the course e-mail system - see the Inbox tab in Canvas.
    • Availability: Please call or e-mail me to schedule a time that is convenient for you.
  • Steve Handwerk

    • Mobile: (717) 303-7962 (The country code for the United States is 1)
    • Email: Please use the course e-mail system - see the Inbox tab in Canvas.
    • Availability: Please call or e-mail me to schedule a time that is convenient for you.
  • David Jimenez

    • Mobile: (575) 618-7989 (The country code for the United States is 1)
    • Email: Please use the course e-mail system - see the Inbox tab in Canvas (in an emergency my PSU email is dxj13@psu.edu).
    • Availability: Please call or e-mail me to schedule a time that is convenient for you. Please note I am located in the Mountain Standard Time zone.
  • Greg Thomas

    • Office: (814) 867-1471 (The country code for the United States is 1)
    • Email: Please use the course e-mail system - see the Inbox tab in Canvas (in an emergency my PSU email is gat5@psu.edu).
    • Availability: Please call or e-mail me to schedule a time that is convenient for you. Please note I am located in the Eastern Time zone.


Class Support Services

Penn State Online offers online tutoring to World Campus students in math, writing, and some business classes. Tutoring and guided study groups for residential students are available through Penn State Learning.


Course Overview

GEOG 885 explores the challenges and opportunities created by combining human expertise with computational analysis methods in the field of geospatial intelligence (GEOINT). The course focuses on the science and technology of human-machine collaboration using geospatial artificial intelligence (GeoAI) in GEOINT and the professional and ethical concerns that must be considered as we move forward in this rapidly evolving field. Students completing this course will be able to explain and apply Structured Analytic Techniques (SATs), automation methods, and GeoAI tools in combination to solve geospatial intelligence problems. Students will create analysis workflows that ensure the efficiency, credibility, and accuracy of analytical insights. SATs are evaluated by students to gauge their ability to improve the quality and rigor of analysis. Students will also learn how to apply emerging GeoAI tools to summarize data and perform analytical tasks that have typically required human intelligence. GEOINT plays an increasingly critical role in supporting decision-making across a broad range of industries, from defense and intelligence to environmental monitoring and urban planning. The amount of geospatial data available today is overwhelming, but by leveraging the strengths of both humans and machines, we can gain deeper insights into high-dimensional spatial data and more effectively solve geographic problems. The course does not require any technical background, and it is open to students from all disciplines.

Course Objectives

Students who excel in this course are able to:

  • LO-1: Apply the geospatial intelligence process including problem spatialization, recording, discovering, tracking, comprehending, and communicating analytic results.
  • LO-2: Contrast the strengths and limitations of the human and machine in geospatial analysis.
  • LO-3: Explain the professional and ethical considerations surrounding machine-driven analysis, automation, and GeoAI in geospatial intelligence analysis.
  • LO-4: Elaborate about the application of human cognitive techniques (Structured Analytic Techniques), computational thinking, GeoAI and automation in geospatial analysis.
  • LO-5: Compare the potential impact of human-machine collaboration on decision-making across different applications.
  • LO-6: Apply critical thinking and problem-solving skills to analyze complex geospatial intelligence problems using a human-machine collaborative approach.
  • LO-7: Defend the results of a geospatial analysis to decision-makers while safeguarding trust, credibility, and accuracy of analytic insights.
  • LO-8: Articulate an understanding of emerging trends and future directions in human-machine collaboration for geospatial intelligence analysis.

Required Course Materials

In order to take this course, you need to have the required course materials and an active Penn State Access Account user ID and password (used to access the online course resources). All (other) materials needed for this course are presented online through Canvas. In order to access the online materials, you need to have an active Penn State Access Account user ID and password (used to access the online course resources). If you have any questions about obtaining or activating your Penn State Access Account, please contact the Outreach Helpdesk.

Obtaining Verification of Enrollment

Special pricing on textbooks and software is available to GEOINT students. Verification of enrollment will be required by several of the vendors.

  1. Before proceeding with textbook or software purchases, please visit the Penn State Office of the University Registrar's website.
  2. Follow the link labeled "Verify Enrollment/Degree Immediately."
  3. Using the form provided, enter either your Social Security number or your Penn State ID to access your enrollment verification. (If you do not know your Penn State ID number, please contact World Campus Student Services at 800-252-3592 or psuwd@psu.edu.)
  4. Save an electronic copy of the resulting enrollment verification.

Required Textbooks

There is no required textbook for this course.

Required Software

A number of software packages will be used for activities throughout the course. Please refer to the "Technology Requirements" page to verify that your computer meets the minimum specifications. Some students have attempted to run course software on an Apple computer using a Windows operating system emulator. Neither the software vendors nor the Dutton e-Education Institute provides technical support for this configuration.

Note:

You need administrative rights on your computer in order to properly install the course software.

Assistance with textbooks

Penn State honors and values the socioeconomic diversity of our students. If you require assistance with the costs of textbooks for this course, please visit the Office of Student Care and Advocacy at 120 Boucke Building or call 814-863-4926. For additional needs, related to socioeconomic status, please visit Project Cahir

Using the Library

Just like on-campus students, as a Penn State student, you have a wealth of library resources available to you!

As a user of Penn State Libraries, you can...

  • search for journal articles (many are even immediately available in full-text)
  • request articles that aren't available in full-text and have them delivered electronically
  • borrow books and other materials and have them delivered to your doorstep
  • access materials that your instructor has put on Electronic Reserve
  • talk to reference librarians in real time using chat, phone, and e-mail
  • ...and much more!

To learn more about their services, see the Library Information for Off-site Users.

Assignments and Grading
Activity Lesson Effort Weight
Mini-Case Study Discussions 1,2,3,4,5,6,7,8,9 Individual 30%
Reflection Papers 2,3 Individual 20%
Capstone Project Individual Contribution 4,5,6,7,8,9 Individual 25%
 Capstone Project Team Progress Notes 4,5,6,7,8,9 Project 5%
Team Presentation 10 Project 20%

Acceptable discussion participation:

  • Offers solid analysis, without prompting, to move the discussion forward
  • Demonstrates deep knowledge of the topic and the question
  • Actively "listening" to other participants
  • Offers clarification and/or follow-up that extends the conversation
  • Remarks often refer back to specific parts of the text

Unacceptable discussion participation:

  • Offers little commentary
  • Is ill-prepared with little understanding of the text and question
  • Offers no commentary to further the discussion
  • Distracts the group by offering off-topic questions and comments
  • Ignores the discussion

Letter grades will be based on the following percentages:

Grading Scale
A 90.0% or above
A- 88.0-89.9%
B+ 85.0-87.9%
B 80.0-84.9%
B- 78.0-79.9%
C+ 75.0-77.9%
C 70.0-74.9%
D 60.0-69.9%
F 59.9% or below

Class participation will be considered in grading for those whose final course grade is close to the next letter grade.

All activity grades in GEOG 885 are posted to Grades in Canvas. To view your grades during the semester, do the following:

  • Log into Canvas.
  • Access the space for this class.
  • Click on the Grades tab.

GEOG 885 Course Schedule

Printable Schedule

Below you will find a summary of the learning activities for this course.

Lesson 0: Orientation
Date: Week 0
Objectives:

At the end of this lesson you will be able to:

  • Demonstrate proficiency in the use of the Canvas learning management system
  • Employ appropriate learning skills in distance education
  • Communicate with other students and the instructor through a Canvas discussion forum
Readings:
  • All Orientation Materials
Assignments: Participate in a personal introduction discussion forum.

Lesson 1: Course Introduction, Ethics and Standards in Intelligence Analysis

Date: Week 1
Objectives:

At the end of this lesson you will be able to:

  • Describe the importance of professional standards and ethical considerations in geospatial intelligence analysis using automation and GeoAI and explain how their use can create unintended consequences and amplify biases in data. (LO-3)
  • Explain key ethical principles that should guide geospatial intelligence analysis. (LO-3)
  • Evaluate a case in geospatial analysis where ethical considerations were or were not considered. (LO-3, LO-6)
  • Compare the potential risks associated with using machines in geospatial intelligence analysis with common human biases. (LO-3, LO-4)

Readings:
  • Online content
  • Designated readings
Assignments:

1.    Case Study Discussion

Lesson 2: Structured Analytic Techniques: Building Understanding and Trust

Date: Week 2
Objectives:

At the end of this lesson you will be able to:

  • Define the concept of Structured Analytic Techniques (SATs) and explain their underlying principles, methods, and applications in geospatial analysis. (LO-4)
  • Analyze the strengths and limitations of SATs in intelligence analysis, and identify key factors that contribute to their effectiveness, such as accuracy, reliability, and efficiency. (LO-4)
  • Analyze a case study using of SATs in geospatial intelligence and identify key factors that contribute to the success. (LO-4, LO-6)
  • Apply SATs to generate hypotheses and evaluate evidence. (LO-4)

Readings:
  • Online content
  • Designated readings
Assignments:
  1. Mini-Case Study Discussion
  2. Refelction paper
Lesson 3: Human-Machine Collaboration: In the Loop, On the Loop, or Out of the Loop
Date: Week 3
Objectives:

At the end of this lesson you will be able to:

  • Define the concept of Structured Analytic Techniques (SATs) and explain their underlying principles, methods, and applications in geospatial analysis. (LO-4)
  • Analyze the strengths and limitations of SATs in intelligence analysis, and identify key factors that contribute to their effectiveness, such as accuracy, reliability, and efficiency. (LO-4)
  • Analyze a case study using of SATs in geospatial intelligence and identify key factors that contribute to the success. (LO-4, LO-6)
  • Apply SATs to generate hypotheses and evaluate evidence. (LO-4)
Readings:
  • Online content
  • Designated readings
Assignments:
  1. Mini-Case Study Discussion
  2. Reflection Paper
Lesson 4: Problem Spatialization
Date: Week 4
Objectives:

At the end of this lesson you will be able to:

  • Explain the role and importance of spatializing the problem in the geospatial intelligence analysis process. (LO-1)
  • Describe the process of spatializing the problem, including the tools and technologies. (LO-1, LO-8)
  • Evaluate the potential benefits and risks of including machines in the problem spatialization process. (LO-1)
  • Analyze a case study of human-machine collaboration where an improper understanding of the spatial qualities of the problem resulted in a poor analytic outcome. (LO-5)
  • Formulate effective strategies that employ SATs to enhance the understanding of the spatial aspects of a problem when working in a human-machine team. (LO-3)
Readings:
  • Online content
  • Designated readings
Assignments:
  1. Mini-Case Study Discussion
  2. Capstone Project Individual Contribution
  3. Capstone Project Team Progress Note
Lesson 5: Recording Spatial Data
Date: Week 5
Objectives:

At the end of this lesson you will be able to:

  • Explain the role and importance of recording in the geospatial intelligence analysis process. (LO-1)
  • Describe the process of recording, including the tools and technologies. (LO-1, LO-8)
  • Evaluate the potential benefits and risks of including machines in the recording process. (LO-1)
  • Analyze a case study of human-machine collaboration where an improper understanding of recording resulted in a poor analytic outcome. (LO-5)
  • Formulate effective strategies that employ SATs to enhance the understanding of the spatial aspects of a problem when working in a human-machine team. (LO-3)
Readings:
  • Online content
  • Designated readings
Assignments:
  1. Mini-Case Study Discussion
  2. Capstone Project Individual Contribution
  3. Capstone Project Team Progress Note
Lesson 6: Spatial Discovery
Date: Week 6
Objectives:

At the end of lesson 6 you will be able to:

  • Explain the role and importance of discovery in the geospatial intelligence analysis process. (LO-1)
  • Describe the discovery process, including the tools and technologies. (LO-1, LO-8)
  • Evaluate the potential benefits and risks of including machines in discovery. (LO-1)
  • Analyze a case study of human-machine collaboration where poor discovery resulted in a poor analytic outcome. (LO-5)
  • Formulate effective strategies that employ SATs to enhance discovery when working in a human-machine team. (LO-3)
Readings:
  • Online content
  • Designated readings
Assignments:
  1. Mini-Case Study Discussion
  2. Capstone Project Individual Contribution
  3. Capstone Project Team Progress Note
Lesson 7: Tracking in Space and Time
Date: Week 7
Objectives:

At the end of lesson 7 you will be able to:

  • Explain the role and importance of tracking in the geospatial intelligence analysis process. (LO-1)
  • Describe the tracking process, including the tools and technologies. (LO-1, LO-8)
  • Evaluate the potential benefits and risks of including machines of tracking. (LO-1)
  • Analyze a case study of human-machine collaboration where poor tracking resulted in a poor analytic outcome. (LO-5)
  • Formulate effective strategies that employ SATs to enhance tracking when working in a human-machine team. (LO-3)
Readings:
  • Online content
  • Designated readings
Assignments:
  1. Mini-Case Study Discussion
  2. Capstone Project Individual Contribution
  3. Capstone Project Team Progress Note
Lesson 8: Comprehending Results
Date: Week 8
Objectives:

By the end of this lesson you will have:

  • Explain the role and importance of comprehension in the geospatial intelligence analysis process. (LO-1)
  • Describe the comprehension process, including the tools and technologies. (LO-1, LO-8)
  • Evaluate the potential benefits and risks of including machines in comprehension. (LO-1)
  • Analyze a case study of human-machine collaboration where poor comprehension resulted in a poor analytic outcome. (LO-5)
  • Formulate effective strategies that employ SATs to enhance comprehension when working in a human-machine team. (LO-3)
Readings:
  • Online content
  • Designated readings
Assignments:
  1. Mini-Case Study Discussion
  2. Capstone Project Individual Contribution
  3. Capstone Project Team Progress Note
Lesson 9: Communicating Insights
Date: Week 9
Objectives:

At the end of this lesson you will be able to:

  • Explain the role and importance of communicating insights in the geospatial intelligence analysis process. (LO-1)
  • Describe the spatial communication process, including the tools and technologies. (LO-1, LO-8)
  • Evaluate the potential benefits and risks of including machines in communications. (LO-1)
  • Analyze a case study of human-machine collaboration where poor communication of insights resulted in a poor analytic outcome. (LO-5)
  • Formulate effective strategies that employ SATs to enhance communicating insights when working in a human-machine team. (LO-3)
Readings:
  • Online content
  • Designated readings
Assignments:
  1. Mini-Case Study Discussion
  2. Capstone Project Individual Contribution
  3. Capstone Project Team Progress Note
Lesson 10: Capstone Report and Presentation
Date: Week 10
Objectives:

At the end of this lesson you will be able to:

  • Apply human-machine collaboration techniques to analyze and interpret geospatial data in a real-world scenario. (LO-6, LO-7)
  • Evaluate the effectiveness of different human-machine collaboration techniques in improving the quality and rigor of geospatial analysis. (LO-6, LO-7)
  • Develop a comprehensive analysis report that effectively communicates insights and recommendations based on the results of the human-machine collaboration. (LO-6, LO-7)
  • Evaluate the ethical implications of using advanced machine learning algorithms in geospatial intelligence analysis and propose strategies to address these ethical considerations. (LO-6, LO-7)
  • Demonstrate proficiency in using structured analytic techniques and artificial intelligence tools to analyze and interpret geospatial data in a collaborative environment. (LO-6, LO-7)
Readings:
  • No reading assignment
Assignments:
  1. Capstone presentation

Course Policies

Technical Requirements

For this course, we recommend the minimum technical requirements outlined on the World Campus Technical Requirements page, including the requirements listed for same-time, synchronous communications. If you need technical assistance at any point during the course, please contact the HelpDesk (for World Campus students) or the IT Service Desk (for students at all other campus locations).

Internet Connection

Access to a reliable Internet connection is required for this course. A problem with your Internet access may not be used as an excuse for late, missing, or incomplete coursework. If you experience problems with your Internet connection while working on this course, it is your responsibility to find an alternative Internet access point, such as a public library or Wi-Fi ® hotspot.

Mixed Content

This site is considered a secure web site which means that your connection is encrypted. We do however link to content that isn't necessarily encrypted. This is called mixed content. By default, mixed content is blocked in Internet Explorer, Firefox, and Chrome. This may result in a blank page or a message saying that only secure content is displayed. Follow the directions on our Technical Requirements page to view the mixed content.

Penn State E-mail Accounts

All official communications from Penn State are sent to students' Penn State e-mail accounts. Be sure to check your Penn State account regularly, or forward your Penn State e-mail to your preferred e-mail account, so you don't miss any important information.

Academic Integrity

This course follows the procedures for academic integrity of Penn State's College of Earth and Mineral Sciences. Penn State defines academic integrity as "the pursuit of scholarly activity in an open, honest and responsible manner." Academic integrity includes "a commitment not to engage in or tolerate acts of falsification, misrepresentation, or deception." In particular, the University defines plagiarism as "the fabrication of information and citations; submitting others' work from professional journals, books, articles, and papers; submission of other students' papers, lab results or project reports and representing the work as one's own." Penalties for violations of academic integrity may include course failure. To learn more, see Penn State's Academic Integrity Training for Students

Course Copyright

All course materials students receive or to which students have online access are protected by copyright laws. Students may use course materials and make copies for their own use as needed, but unauthorized distribution and/or uploading of materials without the instructor’s express permission is strictly prohibited. University Policy AD 40, the University Policy Recording of Classroom Activities and Note Taking Services addresses this issue. Students who engage in the unauthorized distribution of copyrighted materials may be held in violation of the University’s Code of Conduct, and/or liable under Federal and State laws.

For example, uploading completed labs, homework, or other assignments to any study site constitutes a violation of this policy.

Accommodations for Students with Disabilities

Penn State welcomes students with disabilities into the University's educational programs. Every Penn State campus has an office for students with disabilities. The Office for Student Disability Resources website provides contact information for Campus Disability Coordinators at every Penn State campus. For further information, please visit the Office for Student Disability Resources website.

In order to receive consideration for reasonable accommodations, you must contact the appropriate disability services office at the campus where you are officially enrolled. You will participate in an intake interview and provide documentation. See documentation guidelines at Applying for Services from Student Disability Resources. If the documentation supports your request for reasonable accommodations, your campus’s disability services office will provide you with an accommodation letter. Please share this letter with your instructors and discuss the accommodations with them as early in your courses as possible. You must follow this process for every semester that you request accommodations.

Change in Normal Campus Operations

In case of weather-related delays or other emergency campus disruptions or closures at the University, this online course will proceed as planned. Your instructor will inform you if there are any extenuating circumstances regarding content or activity due dates in the course due to these delays or closures. If you are affected by a weather-related emergency, please contact your instructor at the earliest possible time to make special arrangements.

Reporting Educational Equity Concerns

Penn State takes great pride to foster a diverse and inclusive environment for students, faculty, and staff. Acts of intolerance, discrimination, or harassment due to age, ancestry, color, disability, gender, gender identity, national origin, race, religious belief, sexual orientation, or veteran status are not tolerated (Policy AD29 Statement on Intolerance) and can be reported through Educational Equity via Report Bias.

Counseling and Psychological Services

Many students at Penn State face personal challenges or have psychological needs that may interfere with their academic progress, social development, or emotional well-being.  The university offers a variety of confidential services to help you through difficult times, including individual and group counseling, crisis intervention, consultations, online chats, and mental health screenings.  These services are provided by staff who welcome all students and embrace a philosophy respectful of clients’ cultural and religious backgrounds, and sensitive to differences in race, ability, gender identity, and sexual orientation.  Services include the following:

Counseling and Psychological Services at University Park  (CAPS): 814-863-0395
Counseling Services at Commonwealth Campuses
Penn State Crisis Line (24 hours/7 days/week): 877-229-6400
Crisis Text Line (24 hours/7 days/week): Text LIONS to 741741

Military Personnel

Veterans and currently serving military personnel and/or spouses with unique circumstances (e.g., upcoming deployments, drill/duty requirements, disabilities, VA appointments, etc.) are welcome and encouraged to communicate these, in advance if possible, to the instructor in the case that special arrangements need to be made.

Connect Online with Caution

Penn State is committed to educational access for all. Our students come from all walks of life and have diverse life experiences. As with any other online community, the lack of physical interaction in an online classroom can create a false sense of anonymity and security. While one can make new friends online, digital relationships can also be misleading. Good judgment and decision-making are critical when choosing to disclose personal information to others whom you do not know.

Deferred Grades

If you are prevented from completing this course within the prescribed amount of time for reasons that are beyond your control, it is possible to have the grade deferred with the concurrence of the instructor, following Penn State Deferred Grade Policy 48-40. To seek a deferred grade, you must submit a written request (by e-mail or U.S. post) to the instructor describing the reason(s) for the request. Non-emergency permission for filing a deferred grade must be requested before the beginning of the final examination period.  It is up to the instructor to determine whether or not you will be permitted to receive a deferred grade. If permission is granted, you will work with the instructor to establish a communication plan and a clear schedule for completion within policy.  If for any reason, the coursework for the deferred grade is not complete by the assigned time, a grade of "F" will be automatically entered on your transcript.

Attendance

This course will be conducted entirely online. There will be no set class meeting times, but you will be required to complete weekly assignments with specific due dates. Many of the assignments are open for multiple days, so it is your responsibility to complete the work early if you plan to travel or participate in national holidays, religious observances or University approved activities.

If you need to request an exception due to a personal or medical emergency, contact the instructor directly as soon as you are able. Such requests will be considered on a case-by-case basis.

Diversity, Inclusion, and Respect

Penn State is “committed to creating an educational environment which is free from intolerance directed toward individuals or groups and strives to create and maintain an environment that fosters respect for others” as stated in Policy AD29 Statement on Intolerance. All members of this class are expected to contribute to a respectful, welcoming, and inclusive environment and to interact with civility.

For additional information, see:

Mandated Reporting Statement

Penn State’s policies require me, as a faculty member, to share information about incidents of sex-based discrimination and harassment (discrimination, harassment, sexual harassment, sexual misconduct, dating violence, domestic violence, stalking, and retaliation) with Penn State’s Title IX coordinator or deputy coordinators, regardless of whether the incidents are stated to me in person or shared by students as part of their coursework. For more information regarding the University's policies and procedures for responding to reports of sexual or gender-based harassment or misconduct, please visit Penn State's Office of Sexual Misconduct Prevention & Response website.

Additionally, I am required to make a report on any reasonable suspicion of child abuse in accordance with the Pennsylvania Child Protective Services Law.


Disclaimer

Please note that the specifics of this Course Syllabus can be changed at any time, and you will be responsible for abiding by any such changes. All changes will be communicated with you via e-mail, course announcement and/or course discussion forum.