Mountain shadows in optical satellite images complicate the mapping of glacial lakes. Due to the rugged topography in periglacial alpine regions, many glacial lakes, especially smaller lakes, are partially shaded by mountain shadows in remotely sensed images. Shadows not only reduce
the accuracy of lake mapping but also make changes in lake area hard to detect. In this paper, the characteristics of mountain shadows in remotely sensed imagery are explored, and their spatial relationships with regards to glacial lakes are modelled. Building on the previously developed Glacial
Lakes Iterative Local Mapping (GLILM) method, a new water mapping approach is presented. The new method utilizes log-transformed spectral data and a normalized difference water index, NDWIblue, for delineating the boundaries of lakes within shadowed regions. The application of this
approach is explored within the context of mapping lakes across space and time using Landsat images in the glacially dominated Tianshan mountainous of Central Asia. The results demonstrate that glacial lakes, both in sunlit and in shaded areas, can be mapped reliably, and that the results
are useful for lake change analysis studies.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
Document Type: Research Article
Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China
Department of Geology and Geography, West Virginia University, Morgantown, West Virginia, USA
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Publication date: January 17, 2019
More about this publication?