The present paper aims to determine the best spectral index for extraction of surface water bodies and considerable variation in water surface area during the period between 1990 and 2018. Five spectral indices are tested using Landsat series (1990, 2000, 2009 and 2018) and their performance in delineating surface water are assessed. The results of each algorithm have been matched and verified by Pearson correlation and root mean square error (RMSE). The results indicated that a modified normalized difference water index (MNDWI) was created for 1990, 2000, 2009 and 2018 by RMSE with accurate spatial information on waterbodies of 23.54, 33.14, 22.87 and 17.28 respectively. The estimated area of surface water bodies is increased by 2207.28 ha (1990–2018) derived through MNDWI. Hence, the process could be very useful for accurately mapping and monitoring surface water.

本文旨在确定1990年至2018年期间提取地表水体的最佳光谱指数和水表面积的显着变化。使用Landsat系列（1990、2000、2009和2018）测试了五个光谱指数，评估划定地表水的性能。每种算法的结果均已通过Pearson相关性和均方根误差（RMSE）进行了匹配和验证。结果表明，RMSE为1990年，2000年，2009年和2018年创建了修改后的归一化差异水指数（MNDWI），其中水体的准确空间信息分别为23.54、33.14、22.87和17.28。通过MNDWI得出的地表水体估计面积增加了2207.28公顷（1990-2018年）。因此，