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. 2023 Jun 17;23(12):5678.
doi: 10.3390/s23125678.

Non-Destructive Measurements for 3D Modeling and Monitoring of Large Buildings Using Terrestrial Laser Scanning and Unmanned Aerial Systems

Affiliations

Non-Destructive Measurements for 3D Modeling and Monitoring of Large Buildings Using Terrestrial Laser Scanning and Unmanned Aerial Systems

Mircea-Emil Nap et al. Sensors (Basel). .

Abstract

Along with the development and improvement of measuring technologies and techniques in recent times, new methods have appeared to model and monitor the behavior of land and constructions over time. The main purpose of this research was to develop a new methodology to model and monitor large buildings in a non-invasive way. The methods proposed in this research are non-destructive and can be used to monitor the behavior of buildings over time. A method of comparing point clouds obtained using terrestrial laser scanning combined with aerial photogrammetric methods was used in this study. The advantages and disadvantages of using non-destructive measurement techniques over the classic methods were also analyzed. With a building located in the University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca campus as a case study and with the help of the proposed methods, the deformations over time of the facades of that building were determined. As one of the main conclusions of this case study, it can be stated that the proposed methods are adequate to model and monitor the behavior of constructions over time, ensuring a satisfactory degree of precision and accuracy. The methodology can be successfully applied to other similar projects.

Keywords: 3D modeling; 3D monitoring; TLS; UAS.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 16
Figure 16
Point-to-point displacements/deformations—western façade from the northern perspective.
Figure 17
Figure 17
Point-to-point displacements/deformations—western façade from the southern perspective.
Figure 18
Figure 18
Point-to-point displacements/deformations—southern facade.
Figure 19
Figure 19
Point-to-point displacements/deformations—southern facade from the eastern perspective.
Figure 20
Figure 20
Point-to-point displacements/deformations—eastern facade.
Figure 1
Figure 1
Research paradigm [50].
Figure 2
Figure 2
Proposed workflow for 3D modeling and monitoring [10].
Figure 3
Figure 3
Modeling/monitoring network.
Figure 4
Figure 4
(a) The raw point cloud obtained from the registration of the first epoch of measurements (visualization based on the intensity of the reflected laser beam). (b) The raw point cloud obtained from the registration of the first epoch of measurements (view based on the RGB code taken from the images).
Figure 5
Figure 5
Flight plan—screen capture from Map Pilot Pro.
Figure 6
Figure 6
Detailed filtering of the point cloud using profiles.
Figure 7
Figure 7
(a) Point cloud obtained from terrestrial laser scanning in the first epoch of measurements filtered within Leica Cyclone (RGB code taken from the images). (b) Point cloud obtained from terrestrial laser scanning in the second epoch of measurements filtered within Leica Cyclone (RGB code taken from the images).
Figure 8
Figure 8
Dense point cloud (left) and TIN network overview (right).
Figure 9
Figure 9
The results obtained after filtering the dense point cloud based on altitudes (terraces and ceilings).
Figure 10
Figure 10
Overview of the 3D model (left) and a detailed view of the 3D model (right).
Figure 11
Figure 11
Metal elements of the merged dataset—Global Mapper.
Figure 12
Figure 12
Metal elements from the merged dataset—Leica Cyclone—view based on the RGB code taken from the images.
Figure 13
Figure 13
Metal elements from the merged dataset—Leica Cyclone—view based on the intensity of the reflected laser beam.
Figure 14
Figure 14
Overview of the ICHAT building from the merged dataset—Leica Cyclone—view based on the intensity of the reflected laser beam.
Figure 15
Figure 15
Point-to-point displacements/deformations—northern facade.
Figure 21
Figure 21
Detailed view of a cross-section.
Figure 22
Figure 22
Histogram: point volume—displacement range.

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