Precise Cadastral Survey of Rural Buildings Based on Wall Segment Topology Analysis from Dense Point Clouds

Abstract

The renewal and updating of the cadastre of real estate is a long and tedious task for land administration, especially for rural buildings that lack unified design and planning. In order to retain the required accuracy of all points in the register, huge extensive manual editing is often required. In this work, a precise cadastral survey approach is proposed using Unmanned Aerial Vehicle (UAV) imagery-based stereo point clouds. To ensure the accuracy and uniqueness of building outer walls, the non-maximum suppression of wall points that can separate noise and avoid repeated extraction is proposed. Meanwhile, the multiple cue weighted RANSAC, considering both point-to-line distance and normal consistency, is proposed to reduce the influence of building attachments and avoid spurious edges. For a better description of wall topology, the wall line segment topology graph (WLTG), which can guide the connection of adjacent lines and support the searching of closed boundaries through the minimum graph loop analysis, is also built. Experimental results show that the proposed method can effectively detect the building vector contours with high precision and correct topology, and the detection completeness and correctness of the edge corners can reach 84.9% and 93.2% when the mean square error is below 10 cm.