Isolating Anthropogenic Wetland Loss

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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. Wetland loss due to changes in land use was identified by concurrently tracking disturbance and inundation dynamics across the Mid-Atlantic region (Pennsylvania, West Virginia, Virginia, Maryland, Delaware, and Washington, DC) using the Landsat archive. The annual (2015–2018, 30-meter resolution) products include (1) disturbance extent, (2) inundation extent, (3) declines in inundation extent, and (4) the intersection of disturbance and inundation. Disturbance was identified as a change in greenness, using a harmonic linear regression approach, and as a change in growing season brightness. Inundation extent was mapped using a modified version of the USGS Dynamic Surface Water Extent (DSWE) algorithm. Annual (2015–2018) disturbance extent across the region averaged 0.32% of the study area with the primary sources being residential and commercial development, silviculture, and mining. While year-to-year changes in inundation extent were substantial, the co-occurrence of disturbance and declines in inundation extent represented a minority of both change types, totaling 109 km2 over the 4-year period, and 186 km2 using the National Wetland Inventory dataset in place of the Landsat-derived inundation extent. When the annual products were evaluated with wetland and stream fill points permitted by the U.S. Army Corps of Engineers, 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.

A summary of the geographic distribution of disturbance, water loss, and intersection of the two datasets across the study area: (a) the density of National Wetland Inventory (NWI) wetlands, the density of (b) water loss, (c) disturbance, and (d) the intersection of disturbance and water loss. For a–d, density was calculated from a 5 × 5 window of raster cells using a 3-kilometer resolution. For b–d, density was based on the summed 2015–2018 annual outputs.


Author Name
Melanie Vanderhoof
Author Email