Citation: Jia, H.; Zhu, G.; Guo, L.; He,
J.; Liang, B.; He, S. An Improved
Point Clouds Model for
Displacement Assessment of Slope
Surface by Combining TLS and UAV
Photogrammetry. Appl. Sci. 2022, 12,
4320. https://doi.org/10.3390/
app12094320
Academic Editor: Mauro Lo Brutto
Received: 1 March 2022
Accepted: 22 April 2022
Published: 25 April 2022
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Article
An Improved Point Clouds Model for Displacement
Assessment of Slope Surface by Combining TLS
and UAV Photogrammetry
He Jia
1,2
, Guojin Zhu
3,4,
*, Lina Guo
5
, Junyi He
1,2
, Binjie Liang
1,2
and Sunwen He
6
1
State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University,
Tianjin 300072, China; jiahe_1130@tju.edu.cn (H.J.); tjuhejunyi@foxmail.com (J.H.);
liangbinjie@tju.edu.cn (B.L.)
2
School of Civil Engineering, Tianjin University, Tianjin 300072, China
3
PowerChina Kunming Engineering Corporation Limited, Kunming 650041, China
4
School of Water Conserwancy and Hydropower Engineering, Hoha University, Nanjing 210024, China
5
School of Civil Engineering, Yunnan Technology and Business University, Kunming 651701, China;
guolina2006@163.com
6
Power Construction Corporation of China, Beijing 100048, China; 14jhesw@powerchina.cn
* Correspondence: zhuguojin_kmy@163.com
Abstract:
TLS can quickly and accurately capture object surface coordinates. However, TLS point
clouds cannot cover the entire surface of the target object, due to block of view and limitation of
measurement condition. Thus, using it to monitor deformation of slope reduces the detection accuracy
of slope surface deformation. To overcome the drawbacks, a method to improve TLS point clouds by
UAV photogrammetric point clouds is proposed. The two kinds of point clouds are registered as the
new multi-view point clouds by PCA and ICP. The locations of monitoring points are extracted based
on HSL color space recognition method from the new multi-view point clouds to analyze the surface
displacement. At present, the proposed method has applied in a highway slope in Yunnan Province,
and complete point clouds were successfully constructed. A RTK survey was used to compare and
verify the proposed method. The verification result demonstrate that the difference of displacement
between two measurement methods is less than 10 mm. Comprehensive experiments demonstrate
that the proposed method is reliable and meets the slope displacement monitoring standard.
Keywords: TLS; UAV photogrammetric point clouds; registration; slope surface displacement
1. Introduction
The deformation of highway high slope usually causes the slope instability, which
will lead to the occurrence of landslide and great harm to human society. Thousands of
landslides have been reported annually, all over the world, and the number has extremely
increased in recent years [
1
,
2
]. At present, highway high slopes are widely distributed,
and the instability of highway slope brings great loss to human society [
3
]. Therefore, it
has attracted the attention of governments, as well as experts and researchers in related
fields worldwide.
Common slope stability monitoring methods, in project application, include laser scan-
ner measurement, RTK positioning technology and UAV point clouds measurement [
4
–
6
].
At present, the more conventional slope deformation measurement method is the topo-
graphic survey carried out by Total Station and GNSS devices, as data acquisition sources
of slope displacement. The accuracy of these methods, meet the accuracy requirements of
slope measurement. However, there are many problems in the process of slope measure-
ment, such as large amounts of tasks and vulnerable monitoring equipment a potential
danger to the life of the surveyors during the steep slope operation.
Appl. Sci. 2022, 12, 4320. https://doi.org/10.3390/app12094320 https://www.mdpi.com/journal/applsci
