THƯ VIỆN BỘ NÔNG NGHIỆP VÀ PHÁT TRIỂN NÔNG THÔN

Abstract: Many studies forecast floods using models, but these methods require a lot of hydro-meteorological data and complex cycle calculations. With the rich source of satellite images and the perfection of the technique, it is possible to effectively monitor and forecast floods and natural disasters. The study's objective is to monitor the status of the flood situation in the Mekong River Basin using satellite images. The study used MODIS images at 8-day temporal and 500-meter spatial resolution. Consider a mixed pixel object as the surface water. If the EVI (Enhanced Vegetation Index) and LSWI (Land Surface Water 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 flood forecasting approach during the flood season. The precision is 91 percent. This low-cost weekly flood forecasting system provided a new method for disaster early warning utilizing satellite images.