Urban spatial planning mainly relies on multiband remote sensing images.However,it is difficult for traditional pattern recognition methods to accurately analyze land covers from remote sensing images.On the premise of accurate land type classification,we propose a method of remote sensing image segmentation and contour extraction based on Mask R-CNN with ResNet-101-RPN as backbone network.The method includes the following steps:data acquisition,image defogging,statistical analysis of land covers on remote sensing image,land segmentation and contour acquisition.The proposed method is trained and tested on a challenging satellite tile dataset.Experimental results show that the method can obtain satisfactory land segmentation and contour extraction results by 0.907 of mean average precision (mAP) and 31.33 pixel of mean average distance error (mADE).