An algorithm for building extraction from airborne LiDAR data under adaptive local spatial-spectral consistency

被引：0

作者：

Wang, Liying ^{[1
]}

Zhang, Kangli ^{[1
]}

Li, Xinao ^{[1
]}

You, Ze ^{[1
]}

Feng, Yong ^{[2
]}

机构：

[1] School of Geomatics, Liauning Technical University, Fuccin

[2] Division of Geoinformation Management, Department of Natural Resources of Liaoning Province, Shenyang

来源：

Cehui Xuebao/Acta Geodaetica et Cartographica Sinica | 2024年 / 53卷 / 12期

基金：

中国国家自然科学基金;

关键词：

airborne LiDAR; building extraction; global Statistical characteristic; point cloud; spatial-spectral consistency;

D O I：

10.11947/j.AGCS.2024.20230517

中图分类号：

学科分类号：

摘要：

All the existing studies use the global Statistical characteristics of laser reflection intensity of buildings to aid the extraction of buildings from airborne LiDAR data, but this Solution cannot meet the needs of comprehensive and accurate extraction of buildings with different spectra in large-scale complex urban scenes. Therefore, a building extraction method from airborne LiDAR data based on adaptive local spatial-spectral consistency is developed. The proposed method first converts raw airborne LiDAR data into 3D image. Then, the seeds are selected according to the characteristics of building elevation jump and edge approaching straight line. Subsequently, the connected components that are spatially and spectrally consistent with the seedsare labeled as the building roof,in which the spectral consistency is given by the Statistical intensity properties of an indi-vidual building. Finally, the building facade is extracted by combining the spatial constraint of the extracted building roof and the local intensity consistency constraints. This method solves the problern of accurate extraction of buildings that do not con-form to the global Statistical characteristic of the spectrum by self-adapting to the local spectrum of each individual building, improves the use value of point cloud spectral information, and thus broadens the application scenarios of point cloud spectral Information. Three airborne LiDAR datasets of urban scene with different complexities provided by International Association for Photogrammetry and Remote Sensing are used to test the feasibility and effectiveness of the proposed method. The experi-mental results show that the proposed method can excellently extract buildings in scenes with different complexities. The aver-age completeness, accuracy and quality of the building extraction results are 99. 0%, 98. 0% and 96. 8%, respectively, which are obviously better than the traditional building extraction method using the global Statistical properties of the spectrum. © 2024 SinoMaps Press. All rights reserved.

引用

页码：2349 / 2360

页数：11

共 31 条

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