基于c波段RISAT-1 SAR图像的城市洪水制图:2016年印度班加罗尔洪水事件

V. S. K. Vanama, S. Shitole, Y. S. Rao
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引用次数: 0

摘要

城市洪水制图是灾害管理中一项严谨而关键的工作。2016年7月,印度大城市之一的班加罗尔经历了严重的洪灾。为了分析这次洪水事件,我们获取了洪水前后的RISAT-1卫星图像。利用各种变化检测方法对处理后的SAR图像进行洪水区域识别。水平样极化数据(HH)对于识别永久性水体和洪水灾区具有很高的敏感性。从DEM中提取的永久水体和高架区域在结果中被掩盖,以实现精确的城市洪水制图。结果表明,采用归一化变化指数(NCI)方法可以较好地识别洪水的空间分布。结果表明,差分和比值变化检测方法会导致洪水面积高估和低估,这可能与使用中等分辨率的RISAT-1 SAR图像有关。在城市地区,使用RISAT FRS模式获取的图像,由于其空间分辨率高,可能会获得更好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Urban Flood Mapping with C-band RISAT-1 SAR Images: 2016 Flood Event of Bangalore City, India
Flood mapping in urban areas is a rigorous and crucial task in disaster management. Bangalore, one of the Indian megacities, has experienced severe flooding in July 2016. To analyze this flood event, RISAT-1 satellite images were acquired before and after the flood. Various change detection methods were applied to the processed SAR images to identify the flood area. Horizontal like polarized data (HH) is highly sensitive to identify permanent water bodies and also flood affected areas. Permanent water bodies and high elevated areas extracted from DEM were masked out form the results for accurate urban flood mapping. The results show that the spatial distribution of flood was better identified by Normalized Change Index (NCI) method. The results reveal that difference and ratio change detection methods ensued in over and underestimation of flood area, which may be due to the use of moderate resolution RISAT-1 SAR images. In urban areas, the use of images acquired with RISAT FRS mode may give better results due to its high spatial resolution.
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