XDA28100502 - Agricultural Meteorological Disaster Monitoring Technology Patent

By fusing multi-source remote sensing imagery, an integrated data system for crop disease prediction and waterlogging disaster assessment is constructed. The dataset covers two core research themes: (1) Crop Disease Prediction: Based on prior knowledge of rice blast pathogen distribution, the Plant Senescence Reflectance Index (PSRI) and Normalized Difference Water Index (NDWI) are adopted to develop the Rice Blast Index (RBI).

Combined with habitat factors including Land Surface Temperature (LST), rainfall and historical survey data, a disaster assessment index DI is established to grade the severity of rice blast outbreaks. (2) Waterlogging Disaster Impact Assessment: Five evaluation indicators—cumulative precipitation, terrain, river network density, crop type and crop vulnerability—are selected from three dimensions: hazard of disaster-causing factors, sensitivity of disaster-prone environments and vulnerability of hazard-bearing bodies.