Band selection optimization for constructing water indices based on Sentinel-2A/B data
XIA Xingsheng1,2,3(), LEI Boyang1,2,3, DOU Chunjuan1,2,3, CHEN Qiong1,2,3, PAN Yaozhong1,4
1. Key Laboratory of Tibetan Plateau Land Surface Processes and Ecological Conservation (Ministry of Education), Qinghai Normal University, Xining 810016, China 2. Qinghai Provincial Key Laboratory of Physical Geography and Environmental Process, School of Geographical Science, Qinghai Normal University, Xining 810016, China 3. Academy of Plateau Science and Sustainability, Qinghai Normal University, Xining 810016, China 4. State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
The simple and efficient water index method has been widely used to monitor and identify surface water along with its spatiotemporal variations. However, with the application of narrow-band multispectral sensors, this method faces a challenge in selecting optimal bands with similar features when the data source changes during large-scale water monitoring. Guided by the normalized difference water index (NDWI) and the modified NDWI (MNDWI), and based on the Google Earth Engine (GEE) platform, this study constructed water indices using the green bands and eight red bands from the Sentienl-2A/B multispectral sensor data. Employing Otsu's method, this study identified and extracted water bodies in six quadrats measuring 90 km × 90 km across different temporal and spatial ranges in China. The results indicate that the optimal band combination for water body extraction varied across different times and locations. Compared to the eight water indices constructed from the Sentienl-2A/B multispectral sensor data, the water index based on the combination of B3 and B11 bands, combined with Otsu's method, achieved optimal water identification and extraction results. These results were observed in summer in the lake regions of the Northeast China Plain and mountains, the eastern plains, the Inner Mongolian Plateau, the Yunnan-Guizhou Plateau, Xinjiang, and the Qinghai-Tibet Plateau. In both spring and summer, the water index based on the combination of B3 and B11 bands exhibited an overall accuracy (OA) exceeding 90% and a Kappa coefficient above 0.9, indicating its applicability across different time periods. Overall, the results of this study provide a reference for the design and development of sensors targeting water extraction and monitoring, and for feature band selection in water monitoring and extraction applications based on narrow-band remote sensing data.
夏兴生, 雷博洋, 窦春娟, 陈琼, 潘耀忠. 基于Sentinel-2A/B数据构建水体指数的波段优选[J]. 自然资源遥感, 2025, 37(6): 64-76.
XIA Xingsheng, LEI Boyang, DOU Chunjuan, CHEN Qiong, PAN Yaozhong. Band selection optimization for constructing water indices based on Sentinel-2A/B data. Remote Sensing for Natural Resources, 2025, 37(6): 64-76.
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2025, Vol. 37 
), 雷博洋1,2,3, 窦春娟1,2,3, 陈琼1,2,3, 潘耀忠1,4
