A refined flood submerged area extraction method based on spaceborne SAR images

Abstract

The present invention provides a method for extracting a refined flood submerged area based on a spaceborne SAR image, comprising: S1, acquiring a SAR image of a target area, performing superpixel segmentation and threshold segmentation on the SAR image to obtain a segmentation result, and according to the segmentation result Obtain the background percentage, and calculate the feature vector of each image object; S2, construct an undirected graph by processing the superpixel segmentation result, the background percentage and the feature vector, and obtain the class label of some nodes; S3, according to the described The undirected graph and the obtained class labels of some nodes are used to train the graph convolutional neural network, and the class of other nodes is predicted through the trained graph convolutional neural network, and the submerged water body extraction result is obtained; S4. The distribution of the water body after inundation is different from the distribution of water body before the flood, and the flooded area is obtained. The invention can take into account the characteristics of the image objects and the spatial relationship between the image objects, and can significantly improve the extraction accuracy of the flood submerged area in the SAR image.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing and information extraction, and in particular relates to a refined flood submerged area extraction method based on spaceborne SAR images. Background technique [0002] In recent years, the global climate has been abnormal, and floods have occurred frequently. Since last year, my country has experienced the Yangtze River embankment burst, Henan Zhengzhou Xinxiang flood, Inner Mongolia reservoir dam break and Shanxi flood, etc., causing many casualties and incalculable economic losses. The rapid extraction of flood submerged areas is beneficial to emergency relief, disaster loss assessment and post-disaster reconstruction, etc., which has great research significance and is imperative. Remote sensing satellite observation is the main way to observe the earth. Synthetic aperture radar satellites play an important role in emergency disaster reduction because of their significan...

AI Technical Summary

Problems solved by technology

Therefore, this method has the following problems: a) requires a large amount of manually labeled data; b) requires a large amount of computing resources to train the network; c) needs to be deployed on a high-performance platform

At present, the methods for extracting inundated areas are mainly the above three methods, and these methods are mainly aimed at ordinary water body areas, and cannot be fully applied to flooded areas

Therefore, there is a lack of fine extraction methods for flooded areas, especially those using high-resolution SAR images

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