Automatic identification of the lake area at Qinghai-Tibetan Plateau using remote sensing images

被引:18
|
作者
Liu, Zhaofei [1 ]
Yao, Zhijun [1 ]
Wang, Rui [1 ]
机构
[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
基金
中国国家自然科学基金;
关键词
Automatic interpretation; Area error analyses; Sub-pixel classification; Lake area change; Landsat; 8; Tibetan plateau; DIFFERENCE WATER INDEX; SELIN CO; NDWI; PRECIPITATION; TEMPERATURE; IMPACTS; ERRORS; GPS;
D O I
10.1016/j.quaint.2018.10.023
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
The lake area of the Qinghai-Tibetan Plateau (QTP) was identified using an automatic waterbody interpretation method. The spectral reflectance of water is much lower than that of other land-surface materials in remote sensing images. The method made use of this characteristic, and divided the lake area into pure water pixels and mixed pixels. In total, 4051 field-collected ground control points of the boundaries of the 17 lakes were used to calibrate and validate the method. The lake area changes from the 1980s to 2015 were also analyzed. It can deal with the mismatch between the grid image boundaries and vector real lake boundaries. Results indicate that it is necessary to consider this mismatch when identifying waterbodies based on remote sensing images, especially in the case of waterbodies with an irregular shape. The method can distinguish waterbodies from wetlands and glaciers, and the interpretation accuracy was improved. In 2015, 1177 lakes with an area larger than 1 km(2) were recorded; the total lake area of the QTP was 43873.6 km(2). In general, the QTP lakes have expanded during the past several decades. The lake area has increased by 18.3% from the 1980s to 2015. This indicates expansion in the Northern Tibetan Plateau and shrinkage in the southern region of the QTP. The changes of precipitation were the main reasons for lake area changes on the QTP. However, the increased glacier melt runoff played a dominant role in the upper regions of the Yalungzangbo and Yellow rivers. The method proposed herein can be easily applied to other studies to monitor waterbodies based on remote sensing images, especially in the case of large waterbodies.
引用
收藏
页码:136 / 145
页数:10
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