Interannual and Seasonal Variations of Hydrological Connectivity in a Large Shallow Wetland of North China Estimated from Landsat 8 Images

作者：Ziqi Li, Wenchao Sun, Haiyang Chen, Baolin Xue, Jingshan Yu, Zaifeng Tian · 发表于：Remote Sensing · 年份：2021 · DOI：10.3390/rs13061214 · 被引用次数：35 · 研究领域：Flood Risk Assessment and Management、Land Use and Ecosystem Services、Remote Sensing and LiDAR Applications

Hydrological connectivity is an important characteristic of wetlands that maintains the stability and functions of an ecosystem. This study investigates the temporal variations of hydrological connectivity and their driving mechanism in Baiyangdian Lake, a large shallow wetland in North China, using a time series of open water surface area data derived from 36 Landsat 8 multispectral images from 2013–2019 and in situ measured water level data. Water area classification was implemented using the Google Earth Engine. Six commonly used indexes for extracting water surface data from satellite images were compared and the best performing index was selected for the water classification. A composite hydrological connectivity index computed from open water area data derived from Landsat 8 images was developed based on several landscape pattern indices and applied to Baiyangdian Lake. The results show that, reflectance in the near-infrared band is the most accurate index for water classification with >98% overall accuracy because of its sensitivity to different land cover types. The slopes of the best-fit linear relationships between the computed hydrological connectivity and observed water level show high variability between years. In most years, hydrological connectivity generally increases when water levels increase, with an average R2 of 0.88. The spatial distribution of emergent plants also varies year to year owing to interannual variations of the climate and hydrological reg...