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The extraction of plateau lakes from SAR images based on Faster R-CNN and MorphACWE model |
DONG Tiancheng1(), YANG Xiao1, LI Hui2, ZHANG Zhi1(), QI Rui3 |
1. Institute of Geophysics & Geomatics, China University of Geosciences, Wuhan 430074, China 2. School of Earth Science,China University of Geosciences, Wuhan 430074, China 3. 32023 Troops, Dalian 116032, China |
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Abstract Lakes in the Tibetan Plateau constitute one of the most important natural factors in the plateau ecological environment. So, it is an urgent task to investigate and monitor lakes in the Tibetan Plateau. Because of the unique backscatter characteristics of water body in the image, the extraction and analysis of the lake based on SAR image has become a research hotspot. In order to further eliminate the interference of surface features and improve the classification accuracy, this paper proposes a high-precision lake extraction FR-MorphACWE (Faster Region-based Convolution Neural Network-MorphACWE) model of SAR image. The Interferometric Wide Swath (IW SLC) of the European Space Agency's sentinel-1A interference wide-band mode is used as the main data source, and the sentinel-2a multispectral image level-1c product is used as the reference data source. This model combines the morphological analysis advantages of Faster R-CNN target detection algorithm and the contour extraction advantages of MorphACWE model. The classification experiments were carried out from extraction of comprehensive interference multi-lake. The target detection algorithm was applied to eliminate non - lake surface disturbance. On such a basis, the active contour model was used to extract the lake boundary, and the morphological characteristics and radar reflection characteristics of plateau lakes were fully utilized to achieve high-precision extraction of plateau lakes from the south of Naqu City to the north of Xigaze City in Tibet. The experimental results show that the accuracy of the algorithm can reach 99.71% and the accuracy and recall rate are higher than 98% in the situation of multi-lake interference.
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Keywords
Target detection
Faster R-CNN
CV model
SAR
plateau lake extraction
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Corresponding Authors:
ZHANG Zhi
E-mail: 741204260@qq.com;171560655@qq.com
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Issue Date: 18 March 2021
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