Automatic Filtering of Lidar Building Point Cloud in Case of Trees Associated to Building Roof

Tarsha Kurdi, Fayez and Gharineiat, Zahra ORCID: https://orcid.org/0000-0003-0913-151X and Campbell, Glenn ORCID: https://orcid.org/0000-0002-4249-2512 and Awrangjeb, Mohammad and Dey, Emon Kumar (2022) Automatic Filtering of Lidar Building Point Cloud in Case of Trees Associated to Building Roof. Remote Sensing, 14 (2):430. pp. 1-23.

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Abstract

This paper suggests a new algorithm for automatic building point cloud filtering based on the Z coordinate histogram. This operation aims to select the roof class points from the building point cloud, and the suggested algorithm considers the general case where high trees are associated with the building roof. The Z coordinate histogram is analyzed in order to divide the building point cloud into three zones: the surrounding terrain and low vegetation, the facades, and the tree crowns and/or the roof points. This operation allows the elimination of the first two classes which represent an obstacle toward distinguishing between the roof and the tree points. The analysis of the normal vectors, in addition to the change of curvature factor of the roof class leads to recognizing the high tree crown points. The suggested approach was tested on five datasets with different point densities and urban typology. Regarding the results’ accuracy quantification, the average values of the correctness, the completeness, and the quality indices are used. Their values are, respectively, equal to 97.9%, 97.6%, and 95.6%. These results confirm the high efficacy of the suggested approach.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Current – Faculty of Health, Engineering and Sciences - School of Surveying and Built Environment (1 Jan 2022 -)
Faculty/School / Institute/Centre: Current – Faculty of Health, Engineering and Sciences - School of Surveying and Built Environment (1 Jan 2022 -)
Date Deposited: 15 Mar 2022 23:10
Last Modified: 15 Mar 2022 23:10
Uncontrolled Keywords: LiDAR; classification; modelling; filtering; segmentation
Fields of Research (2008): 09 Engineering > 0909 Geomatic Engineering > 090905 Photogrammetry and Remote Sensing
Fields of Research (2020): 40 ENGINEERING > 4013 Geomatic engineering > 401304 Photogrammetry and remote sensing
Socio-Economic Objectives (2008): E Expanding Knowledge > 97 Expanding Knowledge > 970112 Expanding Knowledge in Built Environment and Design
Socio-Economic Objectives (2020): 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280104 Expanding knowledge in built environment and design
Identification Number or DOI: https://doi.org/10.3390/rs14020430
URI: http://eprints.usq.edu.au/id/eprint/46855

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