Isolating Anthropogenic Wetland Loss by Concurrently Tracking Inundation and Land Cover Disturbance across the Mid-Atlantic Region, U.S.
Global trends in wetland degradation and loss have created an urgency to monitor wetland extent, as well as track the distribution and causes of wetland loss. Satellite imagery can be used to monitor wetlands over time, but few efforts have attempted to distinguish anthropogenic wetland loss from cl...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/9/1464 |
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| author | Melanie K. Vanderhoof Jay Christensen Yen-Ju G. Beal Ben DeVries Megan W. Lang Nora Hwang Christine Mazzarella John W. Jones |
| author_facet | Melanie K. Vanderhoof Jay Christensen Yen-Ju G. Beal Ben DeVries Megan W. Lang Nora Hwang Christine Mazzarella John W. Jones |
| author_sort | Melanie K. Vanderhoof |
| collection | DOAJ |
| description | Global trends in wetland degradation and loss have created an urgency to monitor wetland extent, as well as track the distribution and causes of wetland loss. Satellite imagery can be used to monitor wetlands over time, but few efforts have attempted to distinguish anthropogenic wetland loss from climate-driven variability in wetland extent. We present an approach to concurrently track land cover disturbance and inundation extent across the Mid-Atlantic region, United States, using the Landsat archive in Google Earth Engine. Disturbance was identified as a change in greenness, using a harmonic linear regression approach, or as a change in growing season brightness. Inundation extent was mapped using a modified version of the U.S. Geological Survey’s Dynamic Surface Water Extent (DSWE) algorithm. Annual (2015–2018) disturbance averaged 0.32% (1095 km<sup>2</sup> year<sup>-1</sup>) of the study area per year and was most common in forested areas. While inundation extent showed substantial interannual variability, the co-occurrence of disturbance and declines in inundation extent represented a minority of both change types, totaling 109 km<sup>2</sup> over the four-year period, and 186 km<sup>2</sup>, using the National Wetland Inventory dataset in place of the Landsat-derived inundation extent. When the annual products were evaluated with permitted wetland and stream fill points, 95% of the fill points were detected, with most found by the disturbance product (89%) and fewer found by the inundation decline product (25%). The results suggest that mapping inundation alone is unlikely to be adequate to find and track anthropogenic wetland loss. Alternatively, remotely tracking both disturbance and inundation can potentially focus efforts to protect, manage, and restore wetlands. |
| first_indexed | 2024-03-10T20:01:19Z |
| format | Article |
| id | doaj.art-6de8d5eef76643b1b771b96296f2700e |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T20:01:19Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-6de8d5eef76643b1b771b96296f2700e2023-11-19T23:31:29ZengMDPI AGRemote Sensing2072-42922020-05-01129146410.3390/rs12091464Isolating Anthropogenic Wetland Loss by Concurrently Tracking Inundation and Land Cover Disturbance across the Mid-Atlantic Region, U.S.Melanie K. Vanderhoof0Jay Christensen1Yen-Ju G. Beal2Ben DeVries3Megan W. Lang4Nora Hwang5Christine Mazzarella6John W. Jones7Geosciences and Environmental Change Science Center, U.S. Geological Survey, Denver, CO 80225, USAOffice of Research and Development, U.S. Environmental Protection Agency, Cincinnati, OH 45220, USAGeosciences and Environmental Change Science Center, U.S. Geological Survey, Denver, CO 80225, USADepartment of Geography, Environment and Geomatics, University of Guelph, Guelph, ON N1G 2W1, CanadaNational Wetlands Inventory Program, U.S. Fish and Wildlife Service, Falls Church, VA 22041, USARegion 5, Water Division, Wetlands Section, U.S. Environmental Protection Agency, Chicago, IL 60604, USARegion 3, Water Division, Wetlands Branch, U.S. Environmental Protection Agency, Philadelphia, PA 19103, USAHydrologic Remote Sensing Branch, U.S. Geological Survey, Leetown, WV 25430, USAGlobal trends in wetland degradation and loss have created an urgency to monitor wetland extent, as well as track the distribution and causes of wetland loss. Satellite imagery can be used to monitor wetlands over time, but few efforts have attempted to distinguish anthropogenic wetland loss from climate-driven variability in wetland extent. We present an approach to concurrently track land cover disturbance and inundation extent across the Mid-Atlantic region, United States, using the Landsat archive in Google Earth Engine. Disturbance was identified as a change in greenness, using a harmonic linear regression approach, or as a change in growing season brightness. Inundation extent was mapped using a modified version of the U.S. Geological Survey’s Dynamic Surface Water Extent (DSWE) algorithm. Annual (2015–2018) disturbance averaged 0.32% (1095 km<sup>2</sup> year<sup>-1</sup>) of the study area per year and was most common in forested areas. While inundation extent showed substantial interannual variability, the co-occurrence of disturbance and declines in inundation extent represented a minority of both change types, totaling 109 km<sup>2</sup> over the four-year period, and 186 km<sup>2</sup>, using the National Wetland Inventory dataset in place of the Landsat-derived inundation extent. When the annual products were evaluated with permitted wetland and stream fill points, 95% of the fill points were detected, with most found by the disturbance product (89%) and fewer found by the inundation decline product (25%). The results suggest that mapping inundation alone is unlikely to be adequate to find and track anthropogenic wetland loss. Alternatively, remotely tracking both disturbance and inundation can potentially focus efforts to protect, manage, and restore wetlands.https://www.mdpi.com/2072-4292/12/9/1464Chesapeake Baywetland fillharmonic regression: Landsatpermitsurface water |
| spellingShingle | Melanie K. Vanderhoof Jay Christensen Yen-Ju G. Beal Ben DeVries Megan W. Lang Nora Hwang Christine Mazzarella John W. Jones Isolating Anthropogenic Wetland Loss by Concurrently Tracking Inundation and Land Cover Disturbance across the Mid-Atlantic Region, U.S. Remote Sensing Chesapeake Bay wetland fill harmonic regression: Landsat permit surface water |
| title | Isolating Anthropogenic Wetland Loss by Concurrently Tracking Inundation and Land Cover Disturbance across the Mid-Atlantic Region, U.S. |
| title_full | Isolating Anthropogenic Wetland Loss by Concurrently Tracking Inundation and Land Cover Disturbance across the Mid-Atlantic Region, U.S. |
| title_fullStr | Isolating Anthropogenic Wetland Loss by Concurrently Tracking Inundation and Land Cover Disturbance across the Mid-Atlantic Region, U.S. |
| title_full_unstemmed | Isolating Anthropogenic Wetland Loss by Concurrently Tracking Inundation and Land Cover Disturbance across the Mid-Atlantic Region, U.S. |
| title_short | Isolating Anthropogenic Wetland Loss by Concurrently Tracking Inundation and Land Cover Disturbance across the Mid-Atlantic Region, U.S. |
| title_sort | isolating anthropogenic wetland loss by concurrently tracking inundation and land cover disturbance across the mid atlantic region u s |
| topic | Chesapeake Bay wetland fill harmonic regression: Landsat permit surface water |
| url | https://www.mdpi.com/2072-4292/12/9/1464 |
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