Terrain feature semantic modeling method based on remote sensing image and LiDAR analysis

The embodiment of the invention provides a topographic feature semantic modeling method based on remote sensing images and LiDAR analysis. The method comprises the following steps: acquiring a high-resolution remote sensing image and LiDAR data; extracting a first topographic feature based on the high-resolution remote sensing image, and extracting a topographic object based on LiDAR data; performing edge fusion on the first topographic feature and a topographic object to obtain a topographic feature after edge fusion; and performing semantic modeling on the topographic features after the edge fusion. In this way, various earth observation data can be fully integrated, accurate extraction of topographic features is achieved, the topographic feature extraction result is combined with topographic knowledge defined by the ontology, and consistent description and standardized expression of the topographic feature knowledge are achieved in the aspects of time and space, scale, function, semantics and the like. 本发明