Evaluating the Performance of Terrestrial Laser Scanning for Landslide Monitoring

Zam, P. M. Mat; Fuad, N. Ahmad; Yusoff, Ahmad Razali; Majid, Zulkepli

doi:10.5194/isprs-archives-xlii-4-w9-35-2018

Cited by 7 publications

(5 citation statements)

References 9 publications

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“…According to existing research, the higher the density of the point cloud, the higher the precision [14][15][16][17][18][19][20]. Since the precision of laser point cloud data in this paper was slightly higher than that of image point cloud data, it is reasonable to conclude that the density of the optimal image point cloud data is slightly higher than that of the point cloud.…”

Section: Precision Relationship Between Point Cloud Data and Image Point Cloud Datamentioning

confidence: 82%

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A Novel Method for Density Analysis of Repaired Point Cloud with Holes Based on Image Data

et al. 2021

Remote Sensing

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Repairing point cloud holes has become an important problem in the research of 3D laser point cloud data, which ensures the integrity and improves the precision of point cloud data. However, for the point cloud data with non-characteristic holes, the boundary data of point cloud holes cannot be used for repairing. Therefore, this paper introduces photogrammetry technology and analyzes the density of the image point cloud data with the highest precision. The 3D laser point cloud data are first formed into hole data with sharp features. The image data are calculated into six density image point cloud data. Next, the barycenterization Bursa model is used to fine-register the two types of data and to delete the overlapping regions. Then, the cross-section is used to evaluate the precision of the combined point cloud data to get the optimal density. A three-dimensional model is constructed for this data and the original point cloud data, respectively and the surface area method and the deviation method are used to compare them. The experimental results show that the ratio of the areas is less than 0.5%, and the maximum standard deviation is 0.0036 m and the minimum is 0.0015 m.

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Section: Precision Relationship Between Point Cloud Data and Image Point Cloud Datamentioning

confidence: 82%

“…Additionally, an alternative way to improve the precision in low density point clouds is to increase the point density. Mat Zam et al [15] obtained and registered the point cloud data of four different resolutions in the landslide area. The higher the resolution, the higher the density of the point cloud data.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Density Analysis of Repaired Point Cloud with Holes Based on Image Data

et al. 2021

Remote Sensing

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“…Therefore, control points are set in the non-deformation area, and point clouds in different periods are registered by using control points to obtain surface subsidence. The C2C method was applied to landslide monitoring to calculate landslide displacement [ 23 ]. Then, an upgraded method on C2C was proposed, which used a combination of point distance and statistical sampling to measure deformation directly from point cloud data without mesh or curve fitting to maximize data integrity and minimize errors [ 16 ].…”

Section: Research and Applications Of Tls In Ground Surface Deformati...mentioning

confidence: 99%

Review on the Research and Applications of TLS in Ground Surface and Constructions Deformation Monitoring

Teng

Shi

Wang

et al. 2022

Sensors

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With the gradual maturity of the terrestrial laser scanners (TLS) technology, it is widely used in the field of deformation monitoring due to its fast, automated, and non-contact data acquisition capabilities. The TLS technology has changed the traditional deformation monitoring mode which relies on single-point monitoring. This paper analyzes the application of TLS in deformation monitoring, especially in the field of ground surface, dam, tunnel, and tall constructions. We divide the methods for obtaining ground surface deformation into two categories: the method based on point cloud distance and the method based on displacement field. The advantages and disadvantages of the four methods (M2M, C2C, C2M, M3C2) based on point cloud distance are analyzed and summarized. The deformation monitoring methods and precisions based on TLS for dams, tunnels, and tall constructions are summarized, as well as the various focuses of different monitoring objects. Additionally, their limitations and development directions in the corresponding fields are analyzed. The error sources of TLS point cloud data and error correction models are discussed. Finally, the limitations and future research directions of TLS in the field of deformation monitoring are presented in detail.

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“…The survey coordinates of scanning data for this method are calculated directly relative to the known point (Mat Zam et al, 2018). It is a method conducted similar to the general survey for cadaster or topography survey.…”

Section: Gls 2000 Specificationsmentioning

confidence: 99%

Integration Between Unmanned Aerial Vehicle and Terrestrial Laser Scanner in Producing 3d Model

Adnan

Darwin

Ariff

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

Self Cite

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Abstract. Unmanned Aerial Vehicles (UAV) frequently used for obtaining 2D or 3D data acquisition. Meanwhile, Terrestrial Laser Scanners (TLS) are used for obtaining only 3D data acquisition. However if both are integrated, they were able to produce a more accurate data. The purpose of this study is to investigate the possible integration of point clouds obtained by TLS with UAV images at T06 FBES building through the aerial survey where the roof is scanned and ground survey which scans the facades‟ building. Topcon GLS 2000 and DJI Inspire 1 UAV were used to acquire the data at the field. The aerial data and ground data were processed using Pix4D and Scanmaster respectively. The data integration process is done by converting both point clouds into the same coordinate system and then by aligning the same points of both points clouds in Cloud Compare. For verification purposes, dimensional survey was done and there are several distances were taken from the study area to validate the accuracy assessment. The result of residuals between the dimension survey and integration is 0.183 m which is below 1 meter. The result of this study is a 3D model of UTM T06 FBES building based on the point cloud accuracy in cm level. To conclude, the integration between these two methods can be implemented to produce an accurate 3D model.

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Evaluating the Performance of Terrestrial Laser Scanning for Landslide Monitoring

Cited by 7 publications

References 9 publications

A Novel Method for Density Analysis of Repaired Point Cloud with Holes Based on Image Data

A Novel Method for Density Analysis of Repaired Point Cloud with Holes Based on Image Data

Review on the Research and Applications of TLS in Ground Surface and Constructions Deformation Monitoring

Integration Between Unmanned Aerial Vehicle and Terrestrial Laser Scanner in Producing 3d Model

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