GIS 306 Introduction to Remote Sensing will introduce the fundamentals of the basic physical principle of remote sensing and demonstrate the current applications of the technology. Students will become familiar with the basic image processing techniques for image pre-processing and data extraction. The course is designed to stimulate the current remote sensing activities in natural resource management.
Prerequisites: Admission into ADGIS/BGIS program
Corequisite: GIS 302
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 | 15 |
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| Total Credits | |
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| Total Hours | 45 |
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Typical hours per week breakdown| Lecture | 1 |
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| Lab (lab, field, computer) | 2 |
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Learning Outcomes
Upon successful completion of this course, the learner will be able to:
- Understand the basic physical principles of remote sensing
- Describe the general procedure (big picture) of remote sensing
- Identify different types of remote sensing data, sensors and platforms and their applications
- Apply radiometric and atmospheric corrections for images
- Successfully apply different image processing techniques (pixel-based and object based image classifications) for data extraction using ENVI and QGIS software
Teaching and Learning Approach
The course will include a mix of theory, discussions, demonstrations, case studies, lab work, and independent
study.Learning Resources
Required:
None required
Recommended:
Lillesand, T.M., Kiefer, R.W. and Chipman, J.W. 2015. Remote Sensing and Image Interpretation. 7th Edition.
John Wiley & Sons.Detailed Course Content, Topics, and Sequence Covered
1. College orientation days
2. The physics of 'Light'. Note: Instructor absent on RFW Field Trip.
3. Introduction to Remote Sensing and Visual Image Interpretation, Sensors and Image Characteristics
4. Electromagnetic Energy and Spectral Signatures
5. Image Preprocessing
6. Image enhancements: Contrast manipulation, Spatial and Spectral feature manipulation
7. Introduction to Photogrammetry
8. Introduction to Sentinel-2 data + Midterm Exam Review
9. Midterm
10. Digital Image Classification
11. Object-Based Image Classification
12. Accuracy Assessment /
13. Remote Sensing for Change Detection / Biophysical Modelling / Quantitative Remote sensing
14. Course Review
15. Final ExamAssessment
| Title | Learning Outcomes | Value |
|---|
| Task 1 Assignments | 1, 2, 3, 4, 5 | 60% |
| Task 2 Midterm Exam | 1, 2, 3, 4 | 20% |
| Task 3 Final Exam | 1, 2, 3, 4, 5 | 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.