Extracting method for structure data in geographic data of oblique aviation photography

Abstract

The invention discloses an extracting method for structure data in geographic data of oblique aviation photography. The method comprises the following steps that three-dimensional geographic model data of oblique aviation photography are stored into a three-dimensional topological relative network data structure; classification obliquity values are set, and space triangle faces are classified into the large-gradient faces and the small-gradient faces; the triangle faces with the adjacent relation are combined to obtain a plurality of isolated space polygons and a plurality of isolated space triangle faces which are not combined; all the isolated space polygons generated by the large-gradient faces are extracted from the original model; the space polygons internally provided with holes exist in the extracted isolated space polygons generated by the large-gradient faces, the isolated space polygons generated by the small-gradient faces and the space triangle faces are searched for data corresponding to the holes, and the corresponding holes are filled with the data. The extracting method is used for extracting and classifying ground surface structures, and later application of oblique aviation photography is enriched.

Description

technical field [0001] The invention relates to the technical field of aerial oblique photography, in particular to a method for extracting structure data from geographical data of aerial oblique photography. Background technique [0002] Aerial oblique photogrammetry: refers to oblique geographic positioning and measurement systems. The basic principle is to install cameras in front, back, left and right, and vertical directions on the aircraft to continuously take pictures of the earth's surface, form a three-dimensional comparison by overlapping the photos, and then calculate the three-dimensional space coordinates through the front intersection of the rays. This method of photogrammetry is referred to as "tilt measurement". The application of inclination measurement includes: (1) The inclination measurement data can extract 3D building models, trees, iron towers and other objects that are obviously protruding from the ground surface; DEM); (3) Apply the tilt measuremen...

AI Technical Summary

Problems solved by technology

[0003] However, the 3D model data obtained by tilt measurement is all the data integrated into one model, and the computer cannot distinguish which are buildings, trees, iron towers, and other surface structures.

Because these structures have not been extracted, they cannot be individually assigned attributes, which severely limits later applications

Since the ground structures and surface data are all fused together, the correct 3D ground elevation model (DEM) cannot be generated

Moreover, when drawing a two-dimensional plane vector topographic map, manual drawing of building plane lines is inefficient, difficult, and error-prone

[0004] The 3D model data generated by the current aerial tilt measurement products is a large synthesis, which cannot assign attributes to each building, cannot generate surface elevation models, and cannot directly provide vector topographic maps for measuring the area and location of buildings.

In addition, the main principle of building extraction based on aerial photogrammetry photos is to extract the edge contour of the building through color gradient difference to generate a plane vector map, which cannot handle three-dimensional data, and buildings with complex roof color and indistinct edge gradient cannot be processed; while laser-based Point cloud building extraction products, the main principle is based on the height difference of adjacent point clouds and iterative window filtering. This method can effectively filter buildings or trees with regular outlines, but cannot handle buildings with complex outlines, Also not available for areal data from aerial inclinometers