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Strategies for 3D Modelling of Buildings from Airborne Laser Scanner and Photogrammetric Data Based on Free-Form and Model-Driven Methods: The Case Study of the Old Town Centre of Bordeaux (France)

Authors :
Domenica Costantino
Gabriele Vozza
Vincenzo Saverio Alfio
Massimiliano Pepe
Source :
Applied Sciences, Vol 11, Iss 22, p 10993 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

This paper presents a data-driven free-form modelling method dedicated to the parametric modelling of buildings with complex shapes located in particularly valuable Old Town Centres, using Airborne LiDAR Scanning (ALS) data and aerial imagery. The method aims to reconstruct and preserve the input point cloud based on the relative density of the data. The method is based on geometric operations, iterative transformations between point clouds, meshes, and shape identification. The method was applied on a few buildings located in the Old Town Centre of Bordeaux (France). The 3D model produced shows a mean distance to the point cloud of 0.058 m and a standard deviation of 0.664 m. In addition, the incidence of building footprint segmentation techniques in automatic and interactive model-driven modelling was investigated and, in order to identify the best approach, six different segmentation methods were tested. The segmentation was performed based on the footprints derived from Digital Surface Model (DSM), point cloud, nadir images, and OpenStreetMap (OSM). The comparison between the models shows that the segmentation that produces the most accurate and precise model is the interactive segmentation based on nadir images. This research also shows that in modelling complex structures, the model-driven method can achieve high levels of accuracy by including an interactive editing phase in building 3D models.

Details

Language :
English
ISSN :
20763417
Volume :
11
Issue :
22
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.1c4b3a84511d479791b3421f528d6a6b
Document Type :
article
Full Text :
https://doi.org/10.3390/app112210993