GLOBMAP SWF: A global annual surface water cover frequency dataset during 2000–2020

作者：Yang Liu, Ronggao Liu, Bopan Zhi · 发表于：Elsevier eBooks · 年份：2022 · DOI：10.1016/b978-0-443-21485-1.00064-9 · 被引用次数：20 · 研究领域：Flood Risk Assessment and Management、Remote Sensing and LiDAR Applications、Hydrology and Watershed Management Studies

Abstract. The extent of surface water has been changing significantly due to climatic change and human activities. However, it is challenging to capture the interannual changes of inland water bodies due to their high seasonal variation and abrupt change. In this paper, a global annual surface water cover frequency dataset (GLOBMAP SWF) was generated from the MODIS land surface reflectance products during 2000–2020 to describe the seasonal and interannual dynamics of surface water. Surface water cover frequency (SWF) was proposed as the percentage of the time period when a pixel is covered by water in a year. Instead of determination of the water directly, the SWF was estimated indirectly by identifying land observations among annual clear-sky observations to reduce the influence of clouds and variability of water bodies and surface background characteristics, which helps to improve the applicability of the algorithm for different regions across the globe. The generated dataset shows better performances for frozen water, saline lakes, bright surfaces and regions with frequent cloud cover compared with the two high-frequency surface water datasets derived from MODIS data, and it captures more intermittent surface water but may underestimate small water bodies when compared with two high-resolution datasets derived from Landsat data. Compared with the high-resolution SWF maps extracted from Sentinel-1 data in eight regions that cover lakes, rivers and wetlands, the R2 reaches 0...