GEOG-G 436 ADVANCED REMOTE SENSING (3 CR.)
Advanced remote sensing theory and digital image processing techniques with an emphasis on environmental applications. Hands-on computer exercises provide significant experience in introductory digital image processing for extraction of qualitative and quantitative information about the Earth's terrestrial environments.
1 classes found
Spring 2024
Component | Credits | Class | Status | Time | Day | Facility | Instructor |
---|---|---|---|---|---|---|---|
LEC | 3 | 30115 | Open | 9:45 a.m.–11:00 a.m. | MW | SB 221 | Hwang T |
Regular Academic Session / In Person
LEC 30115: Total Seats: 25 / Available: 10 / Waitlisted: 0
Lecture (LEC)
- COLL (CASE) N&M Breadth of Inq
- Above class meets with GEOG-G536
- COLL (CASE) N&M Breadth of Inquiry credit
In this class, we will learn about the application of terrestrial remote sensing (both passive and active), mostly focused on forested ecosystems. We will use multi-sensor remote sensing data, such as MODIS, Landsat, and LiDAR etc. In addition, we will talk about how these remotely sensed datasets can be used in monitoring of vegetation phenology, deforestation, land use and land cover (LULC) changes, vegetation productivity and structure across different scales. This class will also introduce JavaScript programming in conjunction with the Google Earth Engine for geospatial analysis. This class will also provide a hands-on programming experience to independently solve problems in RS analysis including machine learning too.