This invention discloses a method for predicting urban flood disasters based on
satellite infrared brightness temperature and
precipitation data. The method includes: combining
satellite infrared brightness temperature and
precipitation data to identify relevant data of complete lifecycle MCSs (Multi-Category
System Components); extracting and filtering CCS area evolution data; determining the optimal value of the
sensitivity coefficient; fitting the relationship function between CCS area and time, determining the most vigorous development time as the center point, determining the slope
critical threshold based on the
sensitivity coefficient, and finding boundary points to divide the development, maturity, and dissipation stages; finally, integrating urban underlying surface characteristics and a waterlogging model to quantitatively predict the level of urban flood disasters and push
emergency response measures, optimizing the prediction results and response plans through a dynamic feedback mechanism. This invention can accurately capture the essential characteristics of each stage of MCSs, and based on the capture results, achieve full-process
automation from meteorological monitoring to flood prediction and
emergency response.