GIS 303 GIS Analysis and Automation will build upon the fundamentals of GIS theory by examining geodata models, data management and metadata, advanced analysis (raster and vector), 3D models, batching and scripting. The lab portion of this course will focus on the use of ArcGIS and its extensions for vector and raster analysis, Model Builder for analysis workflow control, and Python scripting for automation.
Prerequisites: GIS 302 with a minimum of 60% or equivalent
Accessibility Services Notice
Students who would like an academic accommodation and who have a documented disability should contact Accessibility Services, if they have not already done so.Course Details| Total number of weeks | 7.5 |
|---|
| Total Credits | |
|---|
| Total Hours | 45 |
|---|
Typical hours per week breakdown| Lecture | 6 |
|---|
Learning Outcomes
Upon successful completion of this course, the learner will be able to:
- Use Model Builder and Python scripts to automate a variety of vector and raster analysis workflows
- Employ a wide range of vector analysis methods, including proximity (buffer), extraction (clip) and overlay techniques to answer spatial questions
- Use the ArcGIS Spatial Analyst and 3D Analyst extensions to create, and visualize raster models and digital elevation models
- Apply model builder and python scripting to automate raster analysis workflow using a habitat suitability model as an example. Compare the effectiveness of these processes
- Apply Raster processing tools (local, focal, global and zonal functions) to answer spatial questions
- Automate raster processing using efficient python scripts including complex loops
- Perform watershed, cost distance and/or network analysis using spatial analyst and network analyst extensions and automate these analyses using python scripts including user inputs
Teaching and Learning Approach
Traditional lectures will be combined with exercises in a computer lab. The concepts will then be applied to a
range of natural resource and planning examples and exercises taken from the real world. Case studies and
projects from the Kootenay Region and BC will be emphasized. Students will be tested using both theory and
practical exams.Learning Resources
Recommended:
Introductory Geographic Information Systems' by Jensen and Jensen, Pearson Series in Geographic Information
Science (2013)
Introduction to Geographic Information Systems' (ninth edition 2019 or later) by K. Chang. McGraw Hill
Education.Detailed Course Content, Topics, and Sequence Covered
1. Vector Analysis Techniques
2. Use model builder to automate vector geoprocessing.
3. Raster Geoprocessing with model builder
4. Reading Week
5. Geoprocessing with Python Scripts: an introduction
6. ArcGIS Pro Tool boxes
7. Midterm
8. Cell-Based Raster Techniques - Local Functions
9. Cell-based Raster Functions: Focal Functions
10. Cell-based Raster Functions: Zonal and Global Functions
11. Global Functions and Hydrological Analysis
12. Network Analysis
13. Review
14. Final ExamAssessment
| Title | Learning Outcomes | Value |
|---|
| Lab Assignments (exercises, models, python scripts) | 1,2,3,4,5,6,7 | 65% |
| Midterm | 1, 2,3,4 | 15% |
| Final Exam | 1, 3, 4, 5, 6,7 | 20% |
| Total | 100% |
Grading Table
Standard Academic and Career Programs Grading Table
| Percentage | Letter Grade | GPA |
| 90-100 | A+ | 4.33 |
| 85-89 | A | 4.00 |
| 80-84 | A- | 3.67 |
| 76-79 | B+ | 3.33 |
| 72-75 | B | 3.00 |
| 68-71 | B- | 2.67 |
| 64-67 | C+ | 2.33 |
| 60-63 | C | 2.00 |
| 55-59 | C- | 1.67 |
| 50-54 | P | 1.00 |
| 0-49 | F | 0.00 |
| | DNW | 0.00 |
See the Academic Calendar for General Information including how to withdraw from course(s) and other regulations.
Disclaimer
Information contained in this course outline is correct at the time of publication. Content of the course is revised on an ongoing basis to ensure relevance to changing educational, employment and market needs. The instructor will endeavor to provide notice of changes to students as soon as possible. The instructor reserves the right to add or delete material from courses.