Remote Sensing Identification of Flash Flood and Debris Flow Disaster Solid Source

Remote sensing plays a pivotal role in mapping and analyzing the dynamics of flash flood and debris flow disasters. Historically, flash floods and debris flows have led to significant casualties and property damage, often exacerbated by the interaction between floods and sediment sources. These sediments, originating from landslides, channel residues, or eroded slopes, contribute to the severity of these disasters. Despite its critical importance, the field of solid source identification using multi-temporal and multi-source remote sensing data remains underdeveloped. Existing research typically focuses on isolated instances without a cohesive approach to data integration and ongoing source monitoring, which is crucial for accurate prediction and mitigation efforts.

This research topic aims to advance scientific understanding and technical capabilities in the early detection and monitoring of solid sources in flash flood and debris flow disasters by utilizing remote sensing technology. Integrating various remote sensing data streams aims to enhance the precision and timeliness of identifying and tracking the evolution of these solid sources within watersheds. Such advancements are vital for developing effective disaster prevention and management strategies.

To explore this topic comprehensively, the scope of this Research Topic encompasses both theoretical advancements and practical applications. We intend to delve into:
• The integration and collaboration of multi-source remote sensing technologies for improved disaster analytics.
• Early detection methodologies for solid sources in challenging and complex environmental settings.
• High-precision monitoring techniques to track the evolution of solid sources over time.
We welcome articles focusing on, but not limited to, the following themes:
• Solid source identification using InSAR technology
• Object-oriented identification of solid sources from optical remote sensing images
• Change monitoring of solid sources using airborne LiDAR data
• Identification techniques involving heterogeneous, multi-source remote sensing data