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Welcome to GIS4120/5120 Geospatial Analytics for Fall 2024 at Saint Louis University! This website is your go-to resource for all course-related information, including links to labs, lectures, datasets, and other essential materials. I’m excited to guide you through the world of geospatial analytics as we explore powerful tools and techniques together.

Course Information#

Course Number: GIS4120/5120
Meeting Times: Tuesday and Thursdays 8:00 AM to 9:15 AM
Location: Room 103, Des Peres Hall, 3694 W Pine Mall, St. Louis, MO 63108
Pre-requisites: Introduction to GIS (GIS4050/5050), Introduction to Remote Sensing (GIS4040/5040), Programming for GIS and Remote Sensing (GIS4090/5090)

Course Description#

This course introduces students to the fundamental concepts and frameworks of spatial analysis, emphasizing the role of geospatial technology in addressing grand societal challenges. Students will explore a range of topics, including spatial analysis processes, data exploration, surface and field analysis, and the application of Python and big data in geospatial contexts. At the end of the course, students will be able to tackle a geospatial analytics project including data collection, data processing, analysis and making inference like a geospatial scientist.

Instructor Information#

Instructor: Sourav Bhadra, Ph.D.
Email: sourav.bhadra@slu.edu
Teaching Assistant: Md. Ahasan Habib (mdahasan.habib@slu.edu)
Office Hours: By Appointment

Learning Outcomes#

By the end of the course, students should be able to:

  • Explain and apply fundamental concepts of spatial analysis.

  • Explore and analyze spatial data using statistical methods.

  • Conduct surface and field analyses, including geometry and interpolation.

  • Use Python and geospatial tools for complex analyses.

  • Analyze and interpret multidimensional climate data.

  • Design, execute, and present a geospatial analysis project.

Required Materials#

Textbook#

De Smith, M.J., Goodchild, M.F. and Longley, P. (2007) Geospatial Analysis: A Comprehensive Guide to Principles, Techniques and Software Tools (6th Edition). Troubador Publishing Ltd., Leicester.

Software#

ArcGIS Pro, Anaconda3

Evaluation and Grading#

Grading Weight#

  • Attendance (5%)

  • Lab Assignments (45%)

  • Midterm Exam (25%)

  • Final Project (25%)

Grade Distribution#

Quality of Performance

Letter Grade

Range %

GPA

Excellent - work is of exceptional quality

A

93 - 100

4.00

Excellent

A-

90 - 92.9

3.70

Good - work is above average

B+

87 - 89.9

3.30

Satisfactory

B

83 - 86.9

3.00

Below Average

B-

80 - 82.9

2.70

Poor

C+

77 - 79.9

2.30

Poor

C

70 - 76.9

2.00

Failure

F

< 70>

0.00

Expectations from Students#

  • Attend every class session, as each lecture builds on the previous one. If you anticipate missing a class, please inform me in advance.

  • Arrive on time to ensure you don’t miss any crucial information.

  • You are responsible for catching up on any material or announcements, including changes in assignments, meeting times, or due dates, if you miss a class.

  • Participation isn’t just about speaking; active listening and thoughtful contributions that advance the discussion are equally important.

  • Submit all assignments at the beginning of class on the due date. Late submissions will impact your grade.

  • To maintain a focused learning environment, refrain from non-academic activities on electronic devices during class.

  • If you anticipate any disruptions, such as an emergency phone call or appointment, please notify me ahead of time.

Lab Assignments#

There will be a total of 8 labs (tentatively) in this course. Students are expected to follow the instructions provided in the lab manual and answer all the questions thoroughly. The lab assignments make up 45% of your overall grade, so please ensure you submit them on time to maintain a strong academic standing.

Mid-term Exam#

The mid-term exam is scheduled for October 17 during our regular class time. The exam will primarily consist of open-ended questions based on our lectures. It’s designed not to test your memorization of concepts, but to assess your reasoning skills and your ability to apply geospatial concepts to real-world scenarios. We will go over the exam details together in our upcoming meetings.

Class Projects#

The class project is a significant component of your learning experience, contributing 25% to your final grade. This project is an opportunity for you to apply the geospatial analytics concepts and techniques we’ve explored throughout the course to a real-world problem. You are expected to work individually to develop an original project that showcases your analytical skills, creativity, and understanding of geospatial data.

Major Expectations#

  • Originality: Your project must be original, demonstrating your approach to solving a geospatial problem. It should reflect your ability to think critically and innovatively within the field of geospatial analytics.

  • PowerPoint Presentation: You will present your project to the class in a concise PowerPoint presentation. This presentation should clearly communicate your project’s objectives, methodology, results, and conclusions. More details will follow.

  • Short Report: Along with your presentation, you will submit a short report (3-4 pages) summarizing your project. The report should include an introduction, a detailed explanation of your methods, your findings, and your conclusions. It should be clear, well-organized, and professionally written. More details will follow.

The class project is your chance to demonstrate your mastery of geospatial analytics, so take this opportunity to showcase your skills and insights.

For undergraduate students who registered for GIS4120: for the class project, you can choose any lab assignment, use a different dataset to complete the tasks as mentioned in the lab and present. You are NOT required to submit a report. I will make sure you have the right sets of goals specified for the class project.

Academic Integrity#

Academic integrity is the commitment to and demonstration of honest and moral behavior in an academic setting. Since the mission of the University is “the pursuit of truth for the greater glory of God and for the service of humanity,” acts of integrity are essential to its very reason for existence. Thus, the University regards academic integrity as a matter of serious importance. Academic integrity is the foundation of the academic assessment process, which in turn sustains the ability of the University to certify to the outside world the skills and attainments of its graduates. Adhering to the standards of academic integrity allows all members of the University to contribute to a just and equitable learning environment that cultivates moral character and self-respect. The full University-level Academic Integrity Policy can be found on the Provost’s Office website at: https://www.slu.edu/provost/policies/academic-and-course/academic-integrity-policy.pdf.

Disability Accommodations#

Students with a documented disability who wish to request academic accommodations must formally register their disability with the University. Once successfully registered, students also must notify their course instructor that they wish to use their approved accommodations in the course.

Please contact the Center for Accessibility and Disability Resources (CADR) to schedule an appointment to discuss accommodation requests and eligibility requirements. Most students on the St. Louis campus will contact CADR, located in the Student Success Center and available by email at accessibility_disability@slu.edu or by phone at 314.977.3484. Once approved, information about a student’s eligibility for academic accommodations will be shared with course instructors by email from CADR and within the instructor’s official course roster. Students who do not have a documented disability but who think they may have one also are encouraged to contact to CADR. Confidentiality will be observed in all inquiries.

Note: due to accreditation requirements, regulatory differences, and/or location-specific resources, the School of Law, the School of Medicine, and SLU Madrid have their own standard language for syllabus statements related to disability accommodations. Faculty in those units should seek guidance for syllabus requirements from their dean’s office.

Title IX#

Saint Louis University and its faculty are committed to supporting our students and seeking an environment that is free of bias, discrimination, and harassment. If you have encountered any form of discrimination on the basis of sex, including sexual harassment, sexual assault, stalking, domestic or dating violence, we encourage you to report this to the University. Discrimination on the basis of sex includes discrimination on the basis of assigned sex at birth, sex characteristics, pregnancy and pregnancy related conditions, sexual orientation and gender identity. If you speak with a faculty member about an incident that involves a Title IX matter, that faculty member must notify SLU’s Title IX Coordinator that you shared an experience relating to Title IX. This is true even if you ask the faculty member not to disclose the incident. The Title IX Coordinator will then be available to assist you in understanding all of your options and in connecting you with all possible resources on and off campus.

If you are pregnant or experiencing a pregnancy related condition, the Title IX Coordinator can assist you in understanding your rights and options as well as provide supportive measures.

Anna Kratky is the Title IX Coordinator at Saint Louis University (DuBourg Hall, room 36; anna.kratky@slu.edu; 314-977-3886). If you wish to speak with a confidential source, you may contact the counselors at the University Counseling Center at 314-977-TALK or make an anonymous report through SLU’s Integrity Hotline by calling 1-877-525-5669 or online at http://www.lighthouse-services.com/slu. To view SLU’s policies, and for resources, please visit the following web addresses: https://www.slu.edu/about/safety/sexual-assault-resources/index.php.

Note: due to accreditation requirements, regulatory differences, and/or location-specific resources, the School of Law, the School of Medicine, and SLU Madrid have their own standard language for syllabus statements related to Title IX. Faculty in those units should seek guidance for syllabus requirements from their dean’s office.

Use of Generative AI#

You are allowed to use generative AI in a limited capacity in this course. Tools such as [ChatGPT, Microsoft Copilot, Gemini, Midjourney, DALL-E or GitHub Copilot] can be used for specific assignments as directed in the assignment. You CANNOT use Generative AI to directly generate open-ended question answers in the assignments but you can use it to understand Python codes (if available). Please note the assignments for which generative AI is allowed come after you have been introduced to foundational skills and concepts geospatial analytics. Tools that perform readability analysis, detect tone and provide editing suggestions as well as those that paraphrase, summarize and outline are allowed for general use on any assignment.

Using a generative AI tool may assist your learning by simplifying texts, helping you brainstorm, providing choices of theses when writing, assisting you with forming arguments, providing grammar checks or feedback for structure, debugging code or creating works of art. However, becoming dependent on generative AI could undermine your learning by eroding your ability to ideate independently, participate fully and intentionally in the writing process, or critically problem solve by debugging your code. The use of generative AI can strip a writer of her/his voice diminishing a creative work. Generative AI still produces inaccurate information and hallucinations are still common which if left unchecked can harm your grade on the assignment. Any work generated with AI should be fact checked to ensure accuracy. You are responsible for the content of your work.

Teams Channel for Communication#

Join the course’s Teams channel here: Teams Channel

If you have questions or need help with lab assignments or lectures, I encourage you to post your inquiries in Teams. This way, everyone can benefit from the discussion and learn together.

GitHub#

The lab materials will be shared through the course’s GitHub repository.

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