Landsat-based Detection of Trends in Disturbance and Recovery algorimth modified to accept LandsatLinkr-processed imagery.
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README.md

README.md

LLR-LandTrendr

LandTrendr (Landsat-based Detection of Trends in Disturbance and Recovery) algorimth modified to accept LandsatLinkr-processed imagery.

The Landsat satellites have witnessed decades of change on the Earth’s surface. Algorithms in LandTrendr (Landsat-based Detection of Trends in Disturbance and Recovery) attempt to capture, label, and map that change for use in science, natural resource management, and education.

LandTrendr is maintained by Robert Kennedy in the Geography group in the College of Earth, Ocean, and Atmospheric Sciences at Oregon State University, with recent contributions by David Miller, Jamie Perkins, Tara Larrue, Sam Pecoraro, and Bahareh Sanaie (Department of Earth and Environment, Boston University), and foundational contributions from Zhiqiang Yang and Justin Braaten in the Laboratory for Applications of Remote Sensing in Ecology located at Oregon State University and the USDA Forest Service’s Pacific Northwest Research Station.

This set of code allows images produced by the LandsatLinkr image processing system to easily be used as inputs. The Landtrendr algorimths remain the same, the alterations only deal with getting the LLR outputs hitched up as LT inputs.

Any use of this alorithm should give due credit:

Kennedy, Robert E., Yang, Zhiqiang, & Cohen, Warren B. (2010). Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr - Temporal segmentation algorithms. Remote Sensing of Environment, 114, 2897-2910

If it's critical to work you'll submit as a paper, please consider engaging Robert Kennedy as a co-author. If you make money from it, you need to develop an agreement with Oregon State University and Boston University. Contact kennedyr@bu.edu for more on any of this."

For more information and instructions on running the batchfiles, please visit the wiki page.