Courses : Syllabi : 683/683L
Geography 683 Advanced Concepts in GIS
Instructor
Course Description
This graduate level course is aimed at students who already have a foundation in GIS concepts, techniques, and applications, and are interested in expending their knowledge of application development with GIS components. The course focuses on geoprocessing and scripting techniques as foundational tools for automating geoprocessing tasks and developing customized geoprocessing tools and workflow. The course material is organized into three modules: (1) learning Python scripting, (2) geoprocessing with Python scripting, and (3) Bayesian Theorem in spatial modeling.
Students are expected to actively participate in class, read assigned articles and develop a project of their own choice. The course lab exercises accompanying and elaborating the material presented during lectures will be introduced in the lab. They provide the stepping-stones to master geoprocessing concepts and scripting techniques discussed during lectures. Hence the lab is the integral part of the course. The final grade for the course will be based on the quality of final project, due at the end of the course.
Prerequisites
Geography 484 and Computer Science 108
Grading
Your grade in the 683 course will be based on the following elements:
- Originality of project: 25%
- Demonstrated mastery of geoprocessing/scripting techniques: 50%
- Project paper or poster: 15%
- Project presentation: 10%
Lab completion is for credit/noncredit only. To earn the lab credit students must achieve the total lab score of 70% or better. Students will submit a proof of completing each lab assignment. There will be three wrap-up labs concluding each course module:
- Introduction to Python for spatial-analysis and modeling
- Geoprocessing with Python
- Bayesian modeling
Books and Materials
Lecture PowerPoint files and lab notes available on Blackboard.
Weekly Topics
| Week | Topic |
|---|---|
| Week One | Python 1: Basic Concepts |
| Week Two | Python 2: Sequences, Modules and Files in Python |
| Week Three | Python 3: Object-oriented Programming in Python |
| Week Four | Python 4: Numeric Python |
| Week Five | Geoprocessing 1: Model Builder |
| Week Six | Geoprocessing 2: Introduction to Geoprocessor Object |
| Week Seven | Geoprocessing 3: The Geoprocessor Programming Model and its Objects |
| Week Eight | Geoprocessing 4: Debugging and Error Handling |
| Week Nine | Geoprocessing 5: Developing Geoprocessing Applications |
| Week Ten | Introduction to Bayes' Theorem |
| Week Eleven | Bayes' Theorem in Spatial Modeling |
| Week Twelve | Student Project Consultations |
| Week Thirteen | Student Project Presentations |
| Week Fourteen | Student Project Presentations |