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Landslide detection method of joint spectrum, digital elevation model double branch network

The application provides a kind of high-resolution image landslide detection method of combined spectrum, digital elevation model and auxiliary feature dual-branch network, including obtaining the high-resolution remote sensing image to be detected, digital elevation model and landslide true label;Extract auxiliary features, mine multiple characteristic factors from them and merge all images in channel;The image after merging is preprocessed, and landslide sample is generated;Different data enhancement means are used to increase the number and diversity of landslide data set;Residual and channel attention are added to the network model based on U-Net+++ to improve the network model;The image sample pair is respectively input into the improved U-Net+++ branch network, and the prediction result is obtained;The consistency of sample pair is mined and the model is optimized using the loss function;Based on the test sample, the model accuracy is evaluated and the landslide detection result map is output.The application provides a novel and effective landslide detection method, which can fully mine the invariance features of high-resolution landslide images and effectively improve the recognition accuracy of landslide.
Owner:CHINA UNIV OF GEOSCIENCES (WUHAN)