GST 105 – Introduction to Remote Sensing

Course Description: 
​This course is an introduction to remote sensing of the Earth. Topics include the physical principles on which remote sensing is based, history and future trends, sensors and their characteristics, image data sources, and image classification, interpretation and analysis techniques.

Student Learning Outcomes (SLOs):

  1. Describe basic physics concepts on which remote sensing is based (i.e. Electromagnetic Spectrum, etc.)
  2. Describe the fundamentals of Photogrammetry
  3. Select appropriate data set for remote sensing application based on spectral, temporal, radiometric and spatial resolution.
  4. Describe characteristics of passive and active remote sensing systems (such as multispectral, LiDAR and Radar).
  5. Perform basic remote sensing workflows to solve problems (such as acquiring data, feature extraction, change detection, pre- and post-processing, create composite images and image classification).
  6. Describe future trends in remote sensing.
  7. Apply basic concepts, methods and uses of accuracy assessment and ground truthing to the results of remote sensing workflows.
  8. Interpret, analyze and summarize results of a remote sensing workflow.