Flood Image

Flood image analysis focuses on automatically extracting meaningful information from images of flood events, primarily to improve flood mapping and response. Current research emphasizes developing advanced deep learning models, including transformers and convolutional neural networks, often incorporating multimodal data (e.g., incorporating terrain data and rainfall patterns) to improve accuracy and speed in estimating floodwater depth and segmenting flooded areas. These advancements are crucial for enhancing early warning systems, post-disaster needs assessments, and ultimately, mitigating the devastating impacts of floods, particularly in developing countries where manual analysis is prevalent. Furthermore, research is addressing the detection of manipulated or synthetic flood images to ensure the reliability of data used in these critical applications.