Landsat-based detection of Trends in Disturbance and Recovery (Land Trendr)

Target Audience:  

  1. Remote sensing specialist in countries reporting to REDD+
  2. Officials working on understanding the role of forest degradation on carbon emission
  3. Students of remote sensing in forestry applications
  4. Individuals interested in estimation of land cover change using earth observation

Summary and Objectives:  This e-learning course will introduce you to the implementation of Landsat-based detection of Trends in Disturbance and Recovery (LT) Algorithms in Google Earth Engine (LT GEE), and how it can be used to monitor and forecast forest health.

By the end of this course, you will have learned about:

  1. How LandTrendr algorithms distinguish the disturbances and changes in the forest in a different time series.
  2. The methodology and purpose of the LandTrendr algorithms (LT-GEE).
  3. Explore and identify the requirements to run each LT algorithm in GEE.

Course Contact:  Monica Jeada  mjeada@contractor.usgs.gov or Sylvia Wilson snwilson@usgs.gov