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

Author(s):

Zhiqiang Yang
Stephen V. Stehman
C. Kenneth Brewer
Evan B. Brooks
Noel Gorelick
Chengqaun Huang
M. Joseph Hughes
Thomas R. Loveland
James E. Vogelmann
Curtis E. Woodcock
Limin Yang
Zhe Zhu

Year:

2017

Publication type:

Scientific Journal (JRNL)

Primary Station(s):

Rocky Mountain Research Station

Historical Station(s):

Pacific Northwest Research Station

Source:

Forests. 8: 98.

Description

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.

Citation

Cohen, Warren B.; Healey, Sean P.; Yang, Zhiqiang; Stehman, Stephen V.; Brewer, C. Kenneth; Brooks, Evan B.; Gorelick, Noel; Huang, Chengqaun; Hughes, M. Joseph; Kennedy, Robert E.; Loveland, Thomas R.; Moisen, Gretchen G.; Schroeder, Todd A.; Vogelmann, James E.; Woodcock, Curtis E.; Yang, Limin; Zhu, Zhe. 2017. How similar are forest disturbance maps derived from different Landsat time series algorithms? Forests. 8: 98.

Cited

Publication Notes

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  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
https://www.fs.usda.gov/treesearch/pubs/54976