Proficient Remote Sensing Method using GEE-SAR Data Analysis for Early Flood Disaster Mapping in Sri Lankan Major River Basins

Abstract

Although, there are high population densities living around some of the major river basins due to the fertility of the areas, even in the case of minor floods, these settlements are constantly at risk due to flow of this excess water to the Dry Residential Areas. When such over-flooding occurs in the river basins, it is important to have real-time remote mapping, causality determination, and analyzing method to prevent disasters and to deploy emergency response teams to rescue human lives. Nevertheless, the use of aerial images for geographical mapping of such critical areas is difficult and unclear due to the cloudy atmosphere that exists with heavy rainfall and other environmental disturbances. To circumvent such obstacles, we propose a novel method that employs Sentinel 1 SAR data, as well as a speckle filter, to further refine the critical flood events over a free-defined period. Compared to the existing optical sensing methods (MODIS, Landsat etc.), the proposed method gives more accuracy in data analysis and prediction. In land cover classification test, it achieves 94.41% accuracy. The method combined with user-friendly GEE-SAR based platform, foremost over normal aerial photograph analysis as it avoids any environmental disturbances. Thus, the general public here without computer literacy can be informed timely about the threats via phones, etc. Hence, this research study with our novel risk identification method and formulated applet will protect those lives near the rivers. The proposed methodology based approach can be used for flood daunted river basins exist anywhere in the world