Vanderhoof Melanie K, Christensen Jay, Beal Yen-Ju G, DeVries Ben, Lang Megan W, Hwang Nora, Mazzarella Christine, Jones John W
Geosciences and Environmental Change Science Center, U.S. Geological Survey, Denver, CO 80225, USA.
Office of Research and Development, U.S. Environmental Protection Agency, Cincinnati, OH 45220, USA.
Remote Sens (Basel). 2020 May 5;12(9):1464. doi: 10.3390/rs12091464.
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 year) 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 over the four-year period, and 186 km, 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.
湿地退化和丧失的全球趋势促使人们迫切需要监测湿地范围,并追踪湿地丧失的分布情况及原因。卫星图像可用于长期监测湿地,但很少有人尝试将人为导致的湿地丧失与湿地范围受气候驱动的变化区分开来。我们提出了一种利用谷歌地球引擎中的陆地卫星存档数据,同时追踪美国中大西洋地区土地覆盖扰动和淹没范围的方法。扰动被定义为利用谐波线性回归方法得出的绿度变化,或生长季亮度变化。淹没范围则使用美国地质调查局动态地表水范围(DSWE)算法的修改版本进行绘制。每年(2015 - 2018年)的扰动平均占研究区域的0.32%(每年1095平方千米),且在森林地区最为常见。虽然淹没范围呈现出显著的年际变化,但扰动与淹没范围下降同时出现的情况在两种变化类型中占少数,在四年期间总计109平方千米,若使用国家湿地清单数据集代替陆地卫星得出的淹没范围,则为186平方千米。当用许可的湿地和溪流填充点对年度产品进行评估时,95%的填充点被检测到,其中大部分是由扰动产品检测到的(89%),而由淹没范围下降产品检测到的较少(25%)。结果表明,仅绘制淹没范围不太可能足以发现和追踪人为导致的湿地丧失。相反,远程追踪扰动和淹没范围可能会集中精力保护、管理和恢复湿地。