Application Approaches of Multi-source Remote Sensing in Typhoon Forecasting

Abstract

Typhoons cause severe coastal hazards, including strong winds, heavy rainfall, and storm surges, making accurate monitoring and prediction essential for disaster prevention. This paper examines the application of multi-source remote sensing in typhoon prediction, focusing on its working principles, technical processes, practical value, and representative case analysis. Compared with traditional single-source observation, multi-source remote sensing integrates active and passive sensing data from ground-, air-, and space-based platforms, thereby overcoming the limitations of individual sensors in spatial, temporal, and spectral resolution. The study analyses the roles of SAR, geostationary meteorological satellites, and microwave radiometers in capturing typhoon structure, wind fields, thermal conditions, and atmospheric parameters. It further outlines the general workflow for multi-source remote sensing, including data acquisition, preprocessing, physical parameter inversion, and data fusion, to build a three-dimensional, continuous observation system. Taking Typhoon Ma-on as a case, the paper shows that multi-source remote sensing can effectively monitor the typhoon throughout its life cycle, improve the identification of its centre, structure, intensity, and evolution, and provide reliable support for forecasting and emergency response.