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.