Disaster Monitoring Analysis Using Multi-source Remote Sensing Data

In recent years, significant shifts in global climate patterns have led to an increase in natural disasters worldwide. Flooding has become one of the most impactful, while extreme drought conditions are alarmingly common. China, in particular, faces high susceptibility to floods, facing challenges such as flash floods, riverbank breaches, inundated farmlands, and urban waterlogging brought about by intense rainfall, all of which pose grave threats to people’s safety and property. The northern regions of Jiangsu Province, located in the East Asian monsoon climate zone, experience the compounded effects of typhoons and heavy rainfalls, resulting in recurring drought and flood cycles. This study analyzed the spatiotemporal hydrological trends at two stations in Jiangsu — Dongtai and Funing — over a three-year span. It showcased the regional water cycle’s variability by comparing hydrological parameters across locations. The study’s findings confirm the effectiveness of water level and flow retrieval models that employ remote sensing data to predict hydrological changes. Such data is critical for the management of regional water resources and the mitigation of flood-related disasters.