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http://dx.doi.org/10.7780/kjrs.2022.38.6.3.3

A Comparative Study of Reservoir Surface Area Detection Algorithm Using SAR Image  

Jeong, Hagyu (Disaster Information Research Division, National Disaster Management Research Institute)
Park, Jongsoo (Disaster Information Research Division, National Disaster Management Research Institute)
Lee, Dalgeun (Disaster Information Research Division, National Disaster Management Research Institute)
Lee, Junwoo (Disaster Information Research Division, National Disaster Management Research Institute)
Publication Information
Korean Journal of Remote Sensing / v.38, no.6_3, 2022 , pp. 1777-1788 More about this Journal
Abstract
The reservoir is a major water supply source in the domestic agricultural environment, and the monitoring of water storage of reservoirs is important for the utilization and management of agricultural water resource. Remote sensing via satellite imagery can be an effective method for regular monitoring of widely distributed objects such as reservoirs, and in this study, image classification and image segmentation algorithms are applied to Sentinel-1 Synthetic Aperture Radar (SAR) imagery for water body detection in 53 reservoirs in South Korea. Six algorithms are used: Neural Network (NN), Support Vector Machine (SVM), Random Forest (RF), Otsu, Watershed (WS), and Chan-Vese (CV), and the results of water body detection are evaluated with in-situ images taken by drones. The correlations between the in-situ water surface area and detected water surface area from each algorithm are NN 0.9941, SVM 0.9942, RF 0.9940, Otsu 0.9922, WS 0.9709, and CV 0.9736, and the larger the scale of reservoir, the higher the linear correlation was. WS showed low recall due to the undetected water bodies, and NN, SVM, and RF showed low precision due to over-detection. For water body detection through SAR imagery, we found that aquatic plants and artificial structures can be the error factors causing undetection of water body.
Keywords
Agricultural reservoirs; Synthetic aperture radar (SAR); Water body detection; Image classification; Image segmentation;
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Times Cited By KSCI : 8  (Citation Analysis)
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