Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms

We introduce and test LandTrendr (Landsat-based detection of Trends in Disturbance and Recovery), a new approach to extract spectral trajectories of land surface change from yearly Landsat time-series stacks (LTS). The method brings together two themes in time-series analysis of LTS: capture of shor...

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Bibliographic Details
Published in:	Remote sensing of environment Vol. 114; no. 12; pp. 2897 - 2910
Main Authors:	Kennedy, Robert E., Yang, Zhiqiang, Cohen, Warren B.
Format:	Journal Article
Language:	English
Published:	New York, NY Elsevier Inc 15.12.2010 Elsevier
Subjects:	Animal, plant and microbial ecology Applied geophysics Biological and medical sciences Change detection Earth sciences Earth, ocean, space Exact sciences and technology Forest disturbance Forest growth Fundamental and applied biological sciences. Psychology General aspects. Techniques Internal geophysics Land cover dynamics Landsat Teledetection and vegetation maps Temporal segmentation Time series Oregon United States Washington Change detection Temporal segmentation Landsat Time series Land cover dynamics Forest growth Forest disturbance time series analysis algorithms Extract recovery Earth surface North America Capture duration segmentation landscapes processes Space remote sensing Trend utilization Method Perturbation forests Long term trajectory Landsat satellite Smoothing strategy Recognition
ISSN:	0034-4257, 1879-0704
Online Access:	Get full text
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