10th Asian Regional Conference of IAEG (2015)

Development of analysis method using LiDAR data for three dimensional measurementof slope movement
Teruyuki KIKUCHI(1), Teruyoshi HATANO(2) , Yoshimichi SENDA(3)and Satoshi NISHIYAMA(4)(1) JP Design Co., Ltd., Japan
E-mail:kikuchi-t@jpde.co.jp(2) Electric Power Development Co., Ltd., Japan(3) Nakanihon Air Service Co., Ltd, Japan(4) Okayama Univ., Graduate School of Environmental and Life Science, Japan
Abstract
Three-dimensional laser group point data obtained by an airborne laser survey systemhave been utilized as measurement data for disaster mitigation measures. For example, theairborne laser survey is an effective method for estimating the volume of clods moved by awide-area landslide. The measurement accuracy of the laser group points，however, is not
sufficiently high to detect the precursory phenomena of slope failure. We propose a dataprocessing method to improve the accuracy of the laser group point data in order to estimate
minute movements of the slope. Our proposed method is an application of DEM dataprocessing, in which detailed topography can be extracted using only the laser data set frombelow a certain height from the ground surface. Next, we compute the accurate
displacement vector of the slope by matching the processing for the laser data image. We
analyze the movement of the actual debris slide and demonstrate the effectiveness of the
proposed method.
Keywords: laser group point data, slope failure, minute topography, displacement vector
1.

Introduction

obtain ground surface information from laser datawith little influence from vegetation, and to create a
topographic map with detailed land features. The
topographic map and analysis of the laser data makes
it possible to measure the volume of clods moved by
the landslide on the surface using time series data of
the DEM (Digital Elevation Model) (Chigira et al.,
2004; Chigira et al., 2015; Lucieer et al., 2013).
However, a LiDAR survey system that can monitor
the initial minute displacement of landslides has not
yet been established (Jaboyedoff, 2012). To detect orpredict the occurrence of a landslide or slope collapse,
further efforts are necessary to improve themeasurement accuracy of LiDAR data. From themeasurement method viewpoint, increasing thenumber of lasers reaching the ground surface iseffective for improving measurement accuracy, but isexpensive and time consuming because it requires ahigh performance laser scanner with high density andmeasurement conditions uninfluenced by vegetation.
As an alternative, improvement of the analysis
method has been proposed. For example, the use of aprocedure to create a mesh model of the slope andanalyze the movement of the mesh model as thedisplacement of the slope has often been carried out.

In recent years, disasters associated withabnormal weather such as “guerrilla rainstorms” haveoccurred. In particular, in Japan there is an increasing
risk of occurrence of various slope failures such as
slope collapses of shallow depth and debris slides, but
it is difficult to predict the occurrence of slope
failures and take preventive measures because it isdifficult to capture phenomena that are prognostic ofslope failure. Moreover, after the slope disaster, therisk of occurrence of a secondary disaster remains
high for a few days after the torrential rain stops.
Observation methods for wide-area slopes using
ground-installed equipment such as extensometers
have not been in widespread use because of the costand labor involved. Therefore, the development of a
new slope monitoring approach is needed.
Airborne LiDAR systems have been applied to
ground altitude measurements and topography
surveys since the 1960s by using the travel time of alaser mounted on an airplane, along with GNSS
(Global Navigation Satellite System) and IMU(Inertial Measurement Unit) to measure its position.
LiDAR surveying has the advantage of being able to1

10th Asian Regional Conference of IAEG (2015)

It is easy to analyze the displacement by tracing the
movement of the mesh. However, the accuracy of themodel depends on the size of the mesh data, and it isdifficult to analyze the displacement of a steep slope
such as a cliff.
In this paper, we propose a measurement andanalysis method for computing the movement ofslopes, including cliffs, with a high degree of
accuracy. We discuss the results of an experiment inan actual slide debris field and report the applicabilityof our proposed method.
2.

data, while it is easy to detect a concave topography
which is several meters deep and a tub-shaped minutetopography by using our method.
Fig. 1 Concept of method for extracting detailed

Method for analysis of slope displacement

We developed a method that can extract theminute topography from the original laser data byusing only the laser data from below a certain heightfrom the ground surface, as shown in Fig. 1. Fig. 2
shows the difference between the results of theconventional method using the original DEM data
and those of our proposed method in the case of theanalysis of minute topography. All laser data wasused in the conventional method, while in our
proposed method, data reflected by objects within acertain height range, for example 2 to 5 m from thesurface, were deleted in the analysis process. The
right-hand figure indicates that it is possible to detectfalling rocks and depressed and protruding parts of
the original topography using our proposed method,compared with the result shown in the left-handfigure. The result from the method developed here
has a resolution of 10 cm (Mukoyama, 2011; Zhang
et al., 2003).
Fig.3 shows the advantage of our proposed
method. The figure shows that it is hard to read thedetailed land features by using the conventional laser

topography
Fig. 2 Difference in detected minute topography.

Left: analysis result of conventional method. Right:
analysis result of proposed method

Fig.3 Example of reading the detailed land features using the method shown in Fig.1.
It was possible to read 2 m deep concave topography and 3 m wide tub-shaped topography.

2

10th Asian Regional Conference of IAEG (2015)

matching method processing are the angle ofinclination between pixels adjacent to each other, thedegree of depressed and protruding parts within the
narrow area of 5 pixels, and the degree of depressedand protruding parts within the wide area of 25 pixels.
The three-dimensional displacement is calculated
from the amount of movement of the measurement
point detected by the processing described above. The
proposed method has the advantage of being able tomeasure the displacement of measurement points on avariety of land features, including a vertical cliff withoverhang topography, by calculating the displacementof the measurement point directly from the laser point
group data without using a mesh model (Hsiao et al.,
2004; Palenzuela at el., 2014; Ventura et al., 2011).

Fig. 4 Matching method for image. The amount of
movement of the measurement point represented by
the yellow circle is computed using the first andsecond surveying images. The white square is
specified as the search area in the second surveying
image and in the first surveying image. The same
point in the first and second images is specified as themeasurement point using the angle of inclination andthe degrees of ups and downs.

3.

Application of our method

3.1 Topography and geology of test field
The landslide area is located on the southern
margin of the Akaishi Mountains in western Shizuoka
Prefecture, Japan. Most of the major summits in thearea range in altitude from 700 to 800 m. A principal
river, the Tenryu River, cuts into the mountains withv-shaped valleys and steep slopes. Its morphologicallandscape has a youthful form. The Tenryu Riverflows to the Pacific Ocean from north to south. The
comparable height difference between the Tenryu
River and peaks in the area is about 700 m. Largelandslide scars are found sporadically on both slopes
along the Tenryu River. The measurement object is alarge landslide mass on a tributary of the Tenryu
River. The maximum size of the mass is 250 m inwidth, 900 m in length, and 580 m in height. The

Next, we developed a data processing method forthe laser point group data to compute thedisplacement at each measurement point on thesurface of the slope. The topography of the slope has
been generally represented in a mesh model, whereas
we measured the displacement directly from the lasergroup created by the method described above. The
displacement of the measurement point is calculatedusing the matching method for image data createdusing the laser data as follows: we select an arbitrary
measurement point in the area obtained by the second
survey, then search for that point in the image fromthe first survey, as shown in Fig. 4. The search is
performed within a radius of 50 pixels from theselected measurement point. The parameters in theFig. 5 Bird's eye view image of the landslide area produced from DEM and Orthophoto data3

10th Asian Regional Conference of IAEG (2015)

average slope angle is 33°. The landslide has had along history of sliding and flowing. The terrain of themass is divided into three landslide blocks. The area
is underlain by crystalline schist of the Sanbagawa
Metamorphic Belt, which forms the outer zone ofSouthwest Japan. The schist is commonly fragile orsoft owing to schistosities, cleavages, close joints,
and weathering near the surface. Bedrocks in thelandslide area are composed of basic schist and pelitic
schist. The pelitic schist is partially found on theupper part of the slope. The schist strikes NE–SW
and dips 40°–60°NW. The slope of the landslide hasan anti-dip slope. A debris slide occurred in thelandslide area on September 30, 2014 as shown in Fig.
5. The geology and Landslide map is shown in Fig. 6.
The debris slide mass, which consisted of sand andgravel with residual soils, was on the western part ofBlock I that was the latest landslide block. The crownof the slide was 380 m and its toe was 220 m inaltitude. The slope angle before the slide was about
40°. The dimensions of the slide were within 250 m
in length, 90 m in width, and 13 m in depth. The
volume of the moved clod was about 30000 m3. Fourdays previously, on September 26, heavy rainfall
triggered the slide. The precipitation near the site
registered 166 mm. The base of Block I had beenstrongly eroded by a tributary that flows into the
Tenryu River, from west to east. Debris slides
occurred frequently on Block I along the tributary. In
the first two months after the slide, a forest road on
Block II was displaced by tens of centimeters.
Movement of slides or flows within Block I andBlock II around the debris slide area have been active
up to now. Movement within Block III was inactive
because mitigation measures that included drainage
and anchor works had been implemented for Block

III at 510 m in altitude.
3.2 Result of experimental trial and discussion
Fig. 7 shows the analysis result of the distributionof altitude differences in the slope failure area using
our proposed method that deleted the laser point
group data from over a certain height. The laser point
group data density of the laser scanner on the airplanein the specification was in the range of 100 to 120 m2,
and 5 to 10% of them reached the ground surface.
This figure shows the difference of the altitude
between the first and second surveys. It was foundthat it was possible to measure the minute topography
from the limited laser point group data.
Fig. 8 shows the distribution of displacements inthe area where the debris slide occurred. Arrows in
the figure indicate the magnitude and direction of thedisplacement. The upper figure shows thedisplacement calculated using all the laser point
group data, while the lower figure shows thedisplacement estimated using laser data analyzed byour proposed method. In the case of the analysis
result shown in the upper figure, it is clear that there
are several locations where displacement was notdetected because it was impossible to represent theminute topography. On the other hand, the lower
figure shows that it was possible to calculate thedisplacement at all locations, including the steep cliff
where the debris slide occurred. These results show
the benefit of analyzing a collapse phenomenon using
our technique. Fig. 9 shows the distribution of
displacements over the entire area analyzed using ourtechnique. This result coincides with the following
results of the field survey shown in Fig. 5: thedimensions of the debris slide were within 250 m
long, 90 m wide, and 13 m deep. At the center ofFig. 6 Geology and Landslide map of the area where the landslide occurred4

10th Asian Regional Conference of IAEG (2015)

100m
Fig.7 Distribution of altitude change after debris slide.
Blue areas show the locations where the altitude was5
m lower, while red areas show the locations where
the altitude was 5m higher after debris slide.

Fig.8 Distribution of displacement in the area wheredebris slide occurred. The upper figure show theanalysis result by using all laser point group data. The
lower figure show the result by our proposed method.

Landslide block I, deformation of more than 4 m wasobserved, and at the end of Landslide block I,
deformation was not observed. Displacement of tensof centimeters on a road in Landslide block II
occurred, as shown in Photo 1. Non-moved block wasinactive because mitigation measures had been
implemented. Fig. 9 shows the characteristics of theabove-mentioned topography, and it can be seen that

our technique can express extensive topographychanges in detail.
Verification of measurement accuracy of the
proposed method was carried out in the area shown in
Fig. 9. Table 1 shows the analysis results in each area
shown in Fig. 8. In the table, the computed minimum
and maximum displacements in each area are shown,as well as the analysis result of the displacement of

Non moved block

Photo 1

Fig. 9 Distribution of analyzed displacement vectors

510th Asian Regional Conference of IAEG (2015)

Table 1 Displacement vector computed by our proposed method in each landslide block. “Minimum” and“Maximum” indicate minimum and maximum magnitudes of displacement. Units are m.

Number of measurement points
Minimum
Maximum

Landslide block I

Landslide block II

Non-moved block

533
0.06
4.93

287
0.06
2.07

22
0.03
0.35

of shallow landslides and susceptibility assessment
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Chigira, M., Hiraishi, N., Ching-Ying, T., & Matsushi,
Y. (2015). Catastrophic Landslides and Their
Precursory Deep-Seated Gravitational Slope
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Photo1 Deformation appeared on the surface of theroad in Landslide block II area.
the measurement points in Non-moved block, where
topographical change has not occurred. In otherwords, the amount of displacement at themeasurement point in Non-moved block indicates theaccuracy of our measurement technique. It is foundthat it was possible to detect displacements of morethan about 0.4 m. This result demonstrates that our
technique can detect movements of the landslide witha high degree of accuracy.
4.

Conclusions

In this study, we developed a technique formeasuring slope displacements using three
dimensional laser point group data, or LiDAR data. In
this technique, we used only the laser data that isreflected from objects at heights of 2–5 m from theground surface. Moreover, we developed a matching
method for images created from the limited laser
point group data in order to compute displacements
using time series laser data. Experimental trials were
performed to verify the applicability of our proposed
method, and the results show that more thanapproximately 0.4 m changes in the displacement of
the slope could be detected in the area where a debris
slide occurred. We have demonstrated that it ispossible to expand the applicability of airborne laser
surveying to monitor slope failure by using themethod proposed here.
References
Chigira, M., Duan, F., Yagi, H., & Furuya, T. (2004).
Using an airborne laser scanner for the identification

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