Research on Impervious Surface Extraction Method in Rural Areas Based on High Resolution UAV Images and U-Net Network
In response to the major challenges of high-preci-sion impervious surface extraction in rural regions,we use UAV image as the data source and design an extraction strate-gy that incorporates shadow removal and U-Net network. First,the shadow pixels are identified using the multi-stage Otsu thresholding approach to handle the problem of interfer-ence arising from the high number of shadow pixels in the im-age,and then the linear correlation correction method is ap-plied to compensate for the shadows. Second,considering the dispersed distribution of impervious surface in rural regions and their low proportion,the U-Net network model is em-ployed to extract impervious surface due to the dispersed dis-tribution of impervious surface in rural regions and their low proportion. Comparative studies demonstrate that the ap-proach presented in this paper can successfully overcome the impacts of shadow pixels and insufficient sample to produce high accuracy extraction of small micro impervious surface in rural regions.
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