Near-Real-Time Flood Disaster Monitoring Based on Moonlight and Multi-Source Remote Sensing: A Case Study of Zhengzhou Rainstorm
Abstract
The increasing frequency of natural disasters such as floods has led to severe casualties and substantial economic losses. Consequently, near-real-time flood disaster monitoring has become critical for effective disaster response and accurate damage assessment. However, traditional approaches relying on daytime optical imagery and SAR data often suffer from long satellite revisit cycles and data acquisition latency, while nighttime Earth observation remains limited by the absence of adequate illumination. This study proposes an innovative framework that integrates moonlight Earth observation to enable near-real-time flood monitoring and loss assessment and is applied to the 7.20 Zhengzhou rainstorm event. Compared to conventional disaster monitoring techniques, integrating moonlight observations shortens the effective data acquisition period to approximately one day, significantly improving temporal responsiveness compared with conventional techniques. The innovative framework identifies a flood-affected area of 722.93 km2 and estimated economic losses of 107.96 billion yuan in the disaster-affected region. The results indicate that the moonlight data source has significant capacity for near-real-time disaster monitoring and disaster loss assessment and highlight the potential broad impact of this study in relevant fields.