Spring 2020 - GEOG 353 D100
Advanced Remote Sensing (4)
Class Number: 3181
Delivery Method: In Person
Course Times + Location:
Mo 10:30 AM – 12:20 PM
RCB 8100, Burnaby
Exam Times + Location:
Apr 24, 2020
8:30 AM – 11:30 AM
TAKE HOME-EXAM, Burnaby
Office: RCB 7134
Advanced remote sensing principles and techniques, including physics-based modeling, advanced classifiers, automated data processing, and integration of ancillary data products. Quantitative.
Welcome to Advanced Remote Sensing. This course expands on the physical principles of remote sensing introduced in GEOG 253, and explores more advanced methods used in contemporary studies of the Earth’s surface. The focus is on extraction of quantitative information and how to derive it with state-of-the-art image processing techniques, including some automation.
On successful completion of this course, students will:
· Have a stronger understanding of the physical basis of satellite-based remote sensing.
· Be aware of the wide range of uses of modern remote sensing.
· Be able to apply a range of advanced image processing techniques to extract information and produce maps from remote sensing data.
· Calculate diverse indices based on mathematical relationships between spectral bands.
· Transform remotely sensed data into physically-meaningful variables.
· Understand hyperspectral remote sensing.
· Manipulate diverse software packages for remote sensing data processing and visualization.
· Have access to a diverse and curated list of remote sensing data sources.
There will be one 2-hour lecture per week. Students will learn about and practice remote sensing techniques through formal lectures, student-oriented discussions, computer labs and individual assignments. 2-hour lab sessions will be conducted most weeks (not the first), based on using sample data sets and software analysis to reinforce the theoretical concepts and methods presented in the class lectures. Specialized software will be used to examine real world data from multiple sources, with a strong emphasis on problem-based and interactive learning. Students will also form groups to complete an independent literature review of a remote sensing field of their interest, presented orally to their classmates.v
- Lab assignments: 25%
- Midterm: 25%
- Literature Review 15%
- Final Exam 35%
Campbell, J.B. and Wynne, R.H. (2011). Introduction to Remote Sensing. 5th Edition. USA: Guilford Press. ISBN: 9781609181765
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