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Automated Change Detection Methods for Satellite Data that can Improve Conservation Implementation

Michael J. Evans, Jacob W. Malcom
doi: https://doi.org/10.1101/611459
Michael J. Evans
aDefenders of Wildlife, Center for Conservation Innovation, 1130 17th St. NW, Washington, DC 20036
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  • For correspondence: mevans@defenders.org
Jacob W. Malcom
aDefenders of Wildlife, Center for Conservation Innovation, 1130 17th St. NW, Washington, DC 20036
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Abstract

A significant limitation in biodiversity conservation has been the effective implementation of laws and regulations that protect species habitats from degradation. Flexible, efficient, and effective monitoring and enforcement methods are needed to help conservation policies realize their full benefit. As remote sensing data become more numerous and accessible, they can be used to identify and quantify land cover changes and habitat loss. However, these data remain underused for systematic conservation monitoring in part because of a lack of simple tools. We adapted and developed two generalized methods that automatically detect land cover changes in a variety of habitat types using free and publicly available data and tools. We evaluated the performance of these algorithms in two ways. First, we tested the algorithms over 100 sites of known change in the United States, finding these approaches were effective (AUC > 0.90) at distinguishing between areas of land cover change and areas of no change. Second, we evaluated algorithm effectiveness by comparing results to manually identified areas of change in four case studies involving imperiled species habitat: oil and gas development in the range of the Greater Sage Grouse; sand mining operations in the range of the dunes sagebrush lizard; loss of Piping Plover coastal habitat in the wake of hurricane Michael (2018); and residential development in beach mouse habitat. The relative performance of each algorithm differed in each habitat type, but both provided effective means of detecting and delineating habitat loss. Our results show how these algorithms can be used to help close the implementation gap of monitoring and enforcement in biodiversity conservation and we provide a free online tool that can be used to run these analyses.

Article impact statement Methods for automating the detection of habitat loss in satellite images that can be used to monitor and enforce conservation policy.

Footnotes

  • Additional algorithm testing locations have been included, and the manuscript was reformatted for submission to Conservation Biology.

  • https://github.com/mjevans26/ACD_methods

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted January 15, 2020.
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Automated Change Detection Methods for Satellite Data that can Improve Conservation Implementation
Michael J. Evans, Jacob W. Malcom
bioRxiv 611459; doi: https://doi.org/10.1101/611459
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Automated Change Detection Methods for Satellite Data that can Improve Conservation Implementation
Michael J. Evans, Jacob W. Malcom
bioRxiv 611459; doi: https://doi.org/10.1101/611459

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