ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume V-3-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 33–38, 2020
https://doi.org/10.5194/isprs-annals-V-3-2020-33-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 33–38, 2020
https://doi.org/10.5194/isprs-annals-V-3-2020-33-2020

  03 Aug 2020

03 Aug 2020

A NEW INDEX FOR IDENTIFYING WATER BODY FROM SENTINEL-2 SATELLITE REMOTE SENSING IMAGERY

W. Jiang1,2, Y. Ni3, Z. Pang1,2, G. He4, J. Fu1,2, J. Lu1,2, K. Yang1,2, T. Long4, and T. Lei1,2 W. Jiang et al.
  • 1State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, China
  • 2Remote Sensing Technology Application Center, Research Center of Flood and Drought Disaster Reduction of the Ministry of Water Resources, Beijing, China
  • 3Sichuan Highway Planning, survey, Design and Research Institute Ltd, Sichuan, China
  • 4Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

Keywords: Sentinel-2, water body extraction, water index, information extraction, Otsu method, surface water mapping

Abstract. Water body plays an irreplaceable role in the global ecosystem and climate system. Sentinel-2 is a new satellite data with higher spatial and spectral resolution. Through analysing spectral characteristics of Sentinel-2 satellite imagery, the brightness of water body in vegetation red edge band and shortwave infrared band showe sharply different than that of the not water body. Therefore, a new type of water index SWI (Sentinel-2 Water Index) was proposed by combing those two bands. Four representative water types, which included Taihu Lake, the Yangtze River Estuary, the ChaKa Salt Lake and the Chain Lake, were selected as experimental areas. Normalized difference water index (NDWI) and Sentinel-2 Water Index (SWI) with Otsu method were employed to extract water body. The results showed that overall accuracy and Kappa coefficient of SWI were higher than that of NDWI and SWI was efficient index to rapidly and accurately extract water for Sentinel-2 data. Therefore, SWI had application potential for larger scale water mapping in the future.