How similar are forest disturbance maps derived from different Landsat time series algorithms?

Warren B. Cohen; Sean P. Healey; Zhiqiang Yang; Stephen V. Stehman; C. Kenneth Brewer; Evan B. Brooks; Noel Gorelick; Chengquan Huang; M. Joseph Hughes; Robert E. Kennedy; Thomas Loveland; Gretchen G. Moisen; Todd A. Schroeder; James Vogelmann; Curtis E. Woodcock; Limin Yang; Zhe Zhu

doi:10.3390/f8040098

How similar are forest disturbance maps derived from different Landsat time series algorithms?

Forests

By: Warren B. Cohen, Sean P. Healey, Zhiqiang Yang, Stephen V. Stehman, C. Kenneth Brewer, Evan B. Brooks, Noel Gorelick, Chengquan Huang, M. Joseph Hughes, Robert E. Kennedy, Thomas Loveland, Gretchen G. Moisen, Todd A. Schroeder, James Vogelmann, Curtis E. Woodcock, Limin Yang, and Zhe Zhu

https://doi.org/10.3390/f8040098

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Abstract

Disturbance is a critical ecological process in forested systems, and disturbance maps are important for understanding forest dynamics. Landsat data are a key remote sensing dataset for monitoring forest disturbance and there recently has been major growth in the development of disturbance mapping algorithms. Many of these algorithms take advantage of the high temporal data volume to mine subtle signals in Landsat time series, but as those signals become subtler, they are more likely to be mixed with noise in Landsat data. This study examines the similarity among seven different algorithms in their ability to map the full range of magnitudes of forest disturbance over six different Landsat scenes distributed across the conterminous US. The maps agreed very well in terms of the amount of undisturbed forest over time; however, for the ~30% of forest mapped as disturbed in a given year by at least one algorithm, there was little agreement about which pixels were affected. Algorithms that targeted higher-magnitude disturbances exhibited higher omission errors but lower commission errors than those targeting a broader range of disturbance magnitudes. These results suggest that a user of any given forest disturbance map should understand the map’s strengths and weaknesses (in terms of omission and commission error rates), with respect to the disturbance targets of interest.

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Additional publication details
Publication type	Article
Publication Subtype	Journal Article
Title	How similar are forest disturbance maps derived from different Landsat time series algorithms?
Series title	Forests
DOI	10.3390/f8040098
Volume	8
Issue	4
Year Published	2017
Language	English
Publisher	MDPI
Contributing office(s)	Earth Resources Observation and Science (EROS) Center
Description	98, 19 p.
Country	United States
Google Analytic Metrics	Metrics page