Construction and analysis of dali water segmentation dataset of sar images

Flood disasters last for a long time and are destructive, so it is necessary to obtain the submerged area in a timely and effective manner, which is very important for reducing disaster losses and monitoring floods. The main contribution of this paper is to construct a dataset for training and validation of deep learning algorithms for flood detection for Gaofen-3. To overcome the scarcity of SAR datasets for water segmentation, this paper constructs a refined water segmentation dataset named Dali Water Segmentation (Dali-WS) based on the Gaofen-3 satellite in China. The dataset provides abundant rural waters in Dali County, and 1776 chips were handlabeled for further research. We also report extensive performance for the state-of-the-art segmentation algorithms. Additionally, comprehensive evaluations of state-of-the-art segmentation algorithms are presented, demonstrating the challenging nature of the dataset and its potential for driving further advancements in flood detection. The findings of this study are expected to contribute to the progress of flood detection and recognition research.