Many studies forecastfloodsusing models, but these methods require a lot of hydro-meteorological data and complex cycle calculations. With the rich source of satelliteimages and the perfection of the technique, it is possible to effectively monitor and forecastfloods and natural disasters. The study's objective is to monitor the status of the flood situation in the MekongRiverBasinusingsatelliteimages. The study usedMODISimages at 8-day temporal and 500-meter spatial resolution. Consider a mixed pixel object as the surfacewater. If the EVI (Enhanced Vegetation Index) and LSWI (Land SurfaceWater Index) are < 0.1, then it remains submerged for an extended time. As a flood, if EVI > 0.1 but < 0.3. The classification of continuous flooded areas as long-term inundated objects, with the flood and mixed pixels and water-related pixels with a flood duration > 180 days. There was a high correlation between EVI and LSWI. Risk flood maps are the foundation for delineating a floodforecasting approach during the flood season. The precision is 91 percent. This low-cost weekly floodforecasting system provided a new method for disaster early warning utilizing satelliteimages
Tạp chí khoa học Trường Đại học Cần Thơ
Lầu 4, Nhà Điều Hành, Khu II, đường 3/2, P. Xuân Khánh, Q. Ninh Kiều, TP. Cần Thơ
Điện thoại: (0292) 3 872 157; Email: tapchidhct@ctu.edu.vn
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