Abstract: Single tree detection can assist forestry statistics in getting information such as position,width and diameter of the crowns,so it is of great significance for the development of precision forestry.In order to solve the problem of inaccurate canopy delineation in single-tree canopy detection,this paper proposed a single tree detection algorithm based on morphological Snake model for remote sensing images.Firstly,the forest features are analyzed.Then the local maximum method is used to extract treetops according to the forest feature map and the distance map.After this,the contour of Snake model is initialized for all crowns according to treetops,after evolution of the contour,the final detection result of individual trees is obtained.In order to verify the effectiveness of the method,this paper gave comparative analysis of the region growing method,template matching method,watershed method and the proposed morphological snake model method.The experimental results show that the proposed method is more accurate and the shape of the crown is more realistic.Compared with the other three methods,the detection score is 6% higher and the area average difference is reduced by 0.5m².

Key words: Morphology, Remote sensing, Single tree detection, Snake model