LandTrendr
Landsat-based detection of trends in disturbance and recovery algorithm
LandTrendr is set of spectral-temporal segmentation algorithms that are useful for change detection in a time series of moderate resolution satellite imagery (primarily Landsat) and for generating trajectory-based spectral time series data largely absent of inter-annual signal noise. The LandTrendr algorithm has been used for analysis of change in Landsat spectral time series data. Here, we review LandTrendr for the Google Earth Engine (GEE) platform.
Google Earth Engine Scripts:
Collection Parameters:
Start Year: 1984| End Year: 2019| Start Day: 01-01 | End Day: 05-31 | Index: NBR| Mask: cloud, shadow, snow, water
GEE-visualization
var viz = {min: 1984, max: 2019, palette: ['#9400D3', '#4B0082', '#0000FF', '#00FF00', '#FFFF00', '#FF7F00', '#FF0000']};
LandTrendr - related papers:
Contacts
Robert Kennedy
robert.kennedy@oregonstate.edu
Emil Cherrington
emil.cherrington@nasa.gov
Christine Evans
cae0004@uah.edu