New automated method for extracting river information using optimized spectral threshold water index
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The accurate extraction of mountain river information is highly significant in water resource investigation and ecological environment protection. However, there are some problems in the existing methods of river information extraction, which are mainly the interference from shadows and buildings. Such interference leads to erroneous and redundant extraction of river information, which leads to inaccuracy or incompleteness. In this study, a precise extraction method of mountain river information is established using Landsat8 image and digital elevation model. The main steps of the river extraction method are as follows: (1) we propose the optimized spectral threshold water index to extract river information; (2) based on digital elevation model data, we simulate the mountain shadows of the study area to remove interference from them; (3) we establish the buffer zone of the river network using digital elevation model data to solve the problem of redundant extraction of river information; (4) we separately calculate and then standardize land surface temperature, albedo, and normalized different building index. The effects of buildings near the river are removed. Results show a relative accuracy of 97.52%. The new method decreases the interference of mountain shadows and buildings.
KeywordsLandsat8 Digital elevation model Mountain shadow River buffer zone Building removal
This research work was supported jointly by the National Key Research Program of China (Nos. 2016YFC0502300 and 2016YFC0502102), Chinese Academy of Science and Technology Services Network Program (No. KFJ-STS-ZDTP-036) and International Cooperation Agency International Partnership Program (Nos. 132852KYSB20170029 and 2014-3), Guizhou High-Level Innovative Talent Training Program “Ten” Level Talents Program (No. 2016-5648), United Fund of Karst Science Research Center (No. U1612441), International Cooperation Research Projects of the National Natural Science Fund Committee (Nos. 41571130074 and 41571130042), and the Science and Technology Plan of Guizhou Province of China (No. 2017-2966).
Compliance with ethical standards
The authors declare that they have no competing interests.
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