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Abstract：
Background: Recent developments in optical satellite remote sensing have led to a new era in the detection of surface water with its changing dynamics. This study presents the creation of surface water inventory for a part of Pune district (an administrative area), in India using the Landsat 8 Operational Land Imager (OLI) and a multi spectral water indices method. Methods: A total of 13 Landsat 8 OLI cloud free images were analyzed for surface water detection. Modified Normalized Difference Water Index (MNDWI) spectral index method was employed to enhance the water pixels in the image. Water and non-water areas in the map were discriminated using the threshold slicing method with a trial and error approach. The accuracy analysis based on kappa coefficient and percentage of the correctly classified pixels was presented by comparing MNDWI maps with corresponding Joint Research Centre (JRC) Global Surface Water Explorer (GSWE) images. The changes in the surface area of eight freshwater reservoirs within the study area (Bhama Askhed, Bhatghar, Chaskaman, Khadakwasala, Mulashi, Panshet, Shivrata, and Varasgaon) for the year 2016 were analyzed and compared to GSWE time series water databases for accuracy assessment. The annual water occurrence map with percentage water occurrence on a yearly basis was also prepared. Results: The kappa coefficient agreement between MNDWI images and GSWE images is in the range of 0.56 to 0.96 with an average agreement of 0.82 indicating a strong level of agreement. Conclusions: MNDWI is easy to implement and is a sufficiently accurate method to separate water bodies from satellite images. The accuracy of the result depends on the clarity of image and selection of an optimum threshold method. The resulting accuracy and performance of the proposed algorithm will improve with implementation of automatic threshold selection methods and comparative studies for other spectral indices methods.
摘要：
背景：光学卫星遥感的最新发展使地表水的动态变化进入了探测的新时代。这项研究提出了为浦那地区（行政区域）的一部分创建地表水清单，在印度，使用Landsat8操作土地成像仪（OLI）和多光谱水指数方法。方法:对13张Landsat8OLI无云图像进行地表水检测分析。采用改进的归一化差异水指数（MNDWI）光谱指数方法来增强图像中的水像素。使用阈值切片方法和试错方法区分地图中的水和非水区域。通过将MNDWI图与相应的联合研究中心（JRC）全球地表水浏览器（GSWE）图像进行比较，提出了基于卡帕系数和正确分类像素百分比的精度分析。研究区域内八个淡水水库表面积的变化（BhamaAskhed，Bhatghar,Chaskaman,Khadakwasala,Mulashi,Panshet,Shivrata,和Varasgaon）对2016年进行了分析，并与GSWE时间序列水数据库进行了比较，以进行准确性评估。还编制了年度水发生图，其中包含每年的水发生百分比。结果：MNDWI图像和GSWE图像之间的卡帕系数一致性在0.56至0.96的范围内，平均一致性为0.82，表明一致性很强。结论：MNDWI易于实现，是一种从卫星图像中分离水体的足够准确的方法。结果的准确性取决于图像的清晰度和最佳阈值方法的选择。随着自动阈值选择方法的实施以及其他光谱指数方法的比较研究，所提出算法的精度和性能将得到改善。
