IJERD – International Journal of Environmental and Rural Development (2017) 8-1

Research article
erdAnalysis on Surface Deformation and Cracks in Paddy Fields
by 2016 Kumamoto Earthquake using GNSS andPhotogrammetry
TAKAHIKO KUBODERA*
Faculty of Science and Engineering, Toyo University, Saitama, Japan
Email: kubodera@toyo.jp

TAKANOBU SUZUKI
Faculty of Science and Engineering, Toyo University, Saitama, JapanHIROSHI MASAHARU
Faculty of Science and Engineering, Toyo University, Saitama, Japan

EIJI MATSUO
Faculty of Engineering, Kyushu Sangyo University, Fukuoka, Japan
Received 10 January 2017

Accepted 5 May 2017(*Corresponding Author)Abstract Paddy fields in Kumamoto Prefecture were struck seriously by the 2016 Kumamoto
Earthquake. The surface deformation and cracks damaged water distribution system for paddy
fields. In order to clarify damages with rapidity, the surveying combining the aerial-based
surveying and ground-based surveying was necessary. The aerial photogrammetry wasconducted for the surface deformation and crack area, to clarify them quantitatively. The aerial
photos were taken by an airplanes after the earthquakes. The aerial photogrammetry by airplane
is suited to compare the topographic model after earthquakes to the topographic model before
earthquakes, because the topographic model before earthquakes was surveyed by airplane. The
Global Navigation Satellite System (GNSS) surveying was also conducted at the ground points
in the area of aerial photos. The orthophoto mosaic and the Digital Elevation Model (DEM)
after the earthquakes were made from these surveying. Further, the orthophoto mosaic and theDEM after the earthquakes were input into the Geographic Information System (GIS), toanalyze the surface deformation and cracks in paddy fields. The accurate positions for cracks
were found by overlaying the translucent orthophoto mosaic on the existing map. The
differences between the DEMs before and after the earthquakes were analyzed by overlaying
the DEM after the earthquakes on the DEM before the earthquakes. As the results, it was foundthat the overall upheaval and the local cave-in arose in the focused paddy field. The overall
upheaval was 0.0 m - 0.4 m. The local cave-in was about 2.0 m. In order to check thedifferences between the DEMs before and after the earthquakes, the DEM after the earthquakeswas compared to the elevation value by the GNSS surveying at the verification points. As theresult, it was verified that the difference was 0.118 m as standard deviation.
Keywords aerial photogrammetry, GNSS, DEM, GIS, paddy field

INTRODUCTION
The Kumamoto Earthquake was a series of earthquakes that struck Kumamoto Prefecture in the southof Japan on and after April 14, 2016. A foreshock with a magnitude on the Japan MeteorologicalAgency seismic intensity scale of Mj 6.5 and with its hypocenter at a depth of 11 km struck theⒸ ISERD85

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Kumamoto area at 9:16 p.m. on April 14, 2016. At 1:25 a.m. on April 16, 28 h after the foreshock
occurred, the main shock with a magnitude of Mj 7.3 and with its hypocenter at a depth of 12 km
struck the same Kumamoto area that had experienced the foreshock (Kato el al., 2016). Kumamoto
Prefecture is highly productive in terms of agriculture, as evidenced by the fact that, before theearthquakes occurred, it was ranked the fifth most productive prefecture out of all the 47 prefectures inJapan in terms of the value of agricultural production. However, after the earthquakes, many paddy
fields were seriously damaged because the vertical deformation and cracks made it impossible toirrigate them.
In this study, we conducted aerial photogrammetry and a Global Navigation Satellite System(GNSS) survey, because a survey consisting of both aerial- and ground-based studies were necessary
for a prompt understanding of the complete picture of the damaged area. Aerial photogrammetry is asurveying technology utilizing ground-based three dimension (3D) models, which are constructed fromphotos taken from the sky, camera coordinate values, and coordinate values of ground control points(GCPs). In this study, we also built digital elevation models (DEMs) and orthophoto mosaics, because
these were obtainable through the aerial photogrammetry. DEMs are models of the elevations of theland surface, excluding the heights of buildings and vegetation. An orthophoto mosaic is a single aerial
photograph on which several orthographically projected aerial photographs are assembled. We
conducted the GNSS surveying of the devastated areas to obtain the coordinate values of the GCPs. AGNSS surveying is a survey method to determine the positions using signals from positioning satellites
such as the GPS, GLONASS and Galileo. The accuracy ranges from several meters to several
millimeters, depending on the method used. In this research, we conducted a network-based real time
kinematic (RTK) GNSS surveying to determine the coordinate values of the GCPs with high accuracyof several millimeters. We used the Geographic Information System (GIS) to determine the difference
between the DEMs before and after the earthquakes in order to clarify the vertical deformation of theland surface in the paddy fields quantitatively.
The satellites have been used for surveying in Kumamoto (Research Group for High-resolution
Satellite Remote Sensing, 2016; Obata and Iwao, 2016). The drones have been used for surveying inKumamoto (Ishiguro el al., 2016). In this research, we considered that aerial photogrammetry byairplane would be preferable to satellite or drone for the comparison of the DEMs before and after theearthquakes, because an airplane survey had already been conducted to obtain a DEM before theearthquakes. For this reason, we used aerial photos taken from an airplane after the earthquakes. InJapan, the Geospatial Information Authority of Japan (GSI) has built a detailed database of thecountry’s land surface with airplanes, and it released the DEM before the earthquakes free of charge.
We used aerial photogrammetry to build the DEM after the earthquakes, and analyzed the difference
between the DEMs before and after the earthquakes. At the same time, we overlaid orthophoto mosaics
we built from the aerial photogrammetry onto the existing maps to determine cracks on the land
surface in the paddy fields.
METHODOLOGY
Figure 1 shows the target area of the survey and analysis. Kumamoto Prefecture is located in thesouthern part of Japan. Of the large area damaged by the earthquakes, we selected Aso City in order tofocus on the damage to paddy fields. We used the photogrammetry software PhotoScan Professional,
which is a structure-from-motion (SfM) software product. PhotoScan Professional allows for aerial
triangulation with the help of multiple aerial photos and multiple GCPs. It creates DEMs throughimage matching and filtering treatments, and also creates orthophoto mosaics automatically. Fig. 2shows the 3D model that we created. The blue rectangles in the sky show the 3D position and attitudeof the aerial photographs. The circles on the land surface indicate the 3D positions of the GCPs where
we conducted the GNSS surveying. The coordinate system we used is the Japanese Geodetic DatumⒸ ISERD

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IJERD – International Journal of Environmental and Rural Development (2017) 8-1(JGD) 2011 Plane-rectangular Coordinate System Area 2 (Matsumura el al., 2004; Tsuji andMatsuzaka, 2004; Imakiire and Hakoiwa, 2004; Geospatial Information Authority of Japan, 2011). We
successfully created a group of 3D points on the land surface through aerial photogrammetry. On thenear side of the Fig. 2, the site of the landside disaster triggered by the earthquakes can be seen. The
aerial photographs were taken on July 5, 2016. The digital aerial camera provides its orientation
accurately because it was calibrated. Using the RTK GNSS surveying and Inertial Measurement Unit(IMU) technology, it was possible to provide the coordinate axes and attitudes of the digital aerial
camera with high accuracy of several tens of millimeters.

Aerial photos
Aso City
Paddy fields

LandsideFig. 1 Target area in KumamotoFig. 2 The 3D model by aerial photogrammetry

Table 1 SD values of residual errors of the mostprobable values of nine GCPs

SDX [m]

Y [m]

H [m]

0.088

0.149

0.149

Fig. 3 GNSS surveying
As the photograph in Fig. 3 shows, we conducted a network-based RTK GNSS surveying inKumamoto on the 23rd and 24th of July 2016. We used the Trimble R10 for the GNSS surveying, andthree types of satellite: GPS, GLONASS, and the Quasi-Zenith Satellite System (QZSS). In addition,
we used two frequency bands: L1 and L2. The geoid model we used was “GSIGEO2011” (Miyahara elal., 2014; Kubodera el al., 2016). For conducting the GNSS surveying on the ground, we selected thefour corners of the course, sites accessible by car, and pavements so that the aerial camera could takeclear photographs. Based on the surveying calculations from the GNSS surveying, we found that thestandard deviation (SD) of the most probable value was less than 0.01 m. We conducted aerialⒸ ISERD87

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triangulation based on the 3D coordinate values of the camera and the GCPs. Table 1 shows the SD
values of residual errors of the most probable values of nine GCPs. The SD values for the X and Y
coordinates and elevation H were lower than 0.15 m, indicating a high accuracy. We created a DEM
after the earthquakes with 1 m mesh, in order to determine the differences between the DEMs before
and after the earthquakes as well as the elevation values. In addition, we created orthophoto mosaics togain a clearer picture of the damage.
RESULTS AND DISCUSSION
Specifying the Position of Cracks with Orthophoto Mosaic
Figure 4 shows the orthophoto mosaic developed on the GIS. For the aerial photogrammetry, we used
the JGD2011 Plane-rectangular Coordinate System Area 2. The GIS software used was ArcGIS 10.4.1.
We used the existing map as a background for confirmation of the positions. By doing this, we foundthat the created mosaic was developed on the designated positions correctly. The orthophoto mosaic
indicates that this area consists of paddy fields. Subsequently, we set the transmission of theorthophoto mosaic at 50% and overlaid it onto the existing map to specify the positions of cave-ins. As
shown in Fig. 5, we successfully specified the exact positions of the cracks. We were able to confirm
cracks along the fault that occurred in the paddy fields. Fig. 6 shows a photograph taken by the second
author of this study immediately after the earthquakes occurred in the area surrounding the paddy fields.
It shows several cracks created along the fault. This visually confirms that there was a cave-in about 2m deep.

Fig. 5 Cracks in paddy fields

Fig. 4 Orthophoto mosaic developed on the GIS

Fig. 6 Actual cracksⒸ ISERD

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Differences between the DEMs before and after the Earthquakes
For the DEM before the earthquakes, we used the results (5 m mesh, elevation value in units of 0.01 m)
obtained from the GSI. For the analysis of the difference between the DEMs before and after theearthquakes, we set the mesh sizes of the DEM before and after the earthquakes to 1 m. Fig. 7 shows
the results of the analysis. We deducted the elevation values of the DEM before the earthquakes fromthose of the DEM after the earthquakes to obtain the differences. We blacked out the objects with aheight difference greater than 3 m because these were assumed to be vegetation or buildings. The
analysis results indicate that the area on which we focused underwent upheaval as a whole. Whenfocusing on the agricultural roads, it was found that they underwent upheaval of 0.0–0.4 m. The paddy
fields apparently underwent greater upheaval than the agricultural roads, but ambiguous places such as
vegetation showed a low accuracy in matching. The rectangular part in the center of Fig. 7 is thecracked part shown in Fig. 5. Based on the analysis of the differences between the DEMs before andafter the earthquakes, we successfully clarified the vertical deformation both dimensionally andquantitatively.

Fig. 7 Differences between the DEMs before and after the earthquakes
Accuracy Verification of Elevation Values
As Table 2 shows, we compared the elevation values of the DEM after the earthquakes and those of theGNSS after the earthquakes at verification points to verify the accuracy of the constructed DEM after
the earthquakes. At these verification points, we did not adopt the GCPs by aerial triangulation, butrather conducted a GNSS surveying on the points. The GNSS showed a higher accuracy than the DEM.
Based on the above results, we found that the elevation values of the DEM and the GNSS after theearthquakes closely matched each other with the discrepancies between them ranging from +0.031 m
to +0.196 m. The SD of the elevation values of the DEM after the earthquakes was 0.118 m, assumingⒸ ISERD89

IJERD – International Journal of Environmental and Rural Development (2017) 8-1

that the elevation values of the GNSS after the earthquakes were true values. That is, it is possible tostate that the DEMs after the earthquakes was accurate with an SD of 0.118 m.
Table 2 Accuracy verification of elevation values
Elevation value [m]Name of point

DEM after earthquake GNSS after earthquake

Discrepancy

1482.608

482.577+0.0312479.938

479.888+0.0503478.280

478.084+0.196

SD0.118

Comparison of the DEMs before and after the Earthquakes with the Lateral Profile
We found several points where a cave-in could be confirmed by the orthophoto mosaic of Fig. 5, eventhough it was not possible to detect these when comparing the differences between the DEMs before
and after the earthquakes, such as in the rectangle in Fig. 7. The reason for this may be that, although
the point caved-in, it underwent upheaval as a whole. For this reason, we compared the DEMs before
and after the earthquakes using a lateral profile. Fig. 8 shows the transverse line A–A’ used to compare
the DEMs before and after the earthquakes. We designated Points B, C, D, E, and F at distances of 4,20, 30, 60, and 70 m from Point A. This rectangular area is the same as that shown in Fig. 5. Although
the earthquakes caused a cave-in, a large difference could not be detected when comparing the DEMs
before and after the earthquakes. This is presumably because the overall area underwent upheaval, thus
causing a relative cave-in. Fig. 9 shows a cross section along the line A–A’. The section from Point A toPoint B is a paved agricultural road, and it underwent upheaval of about 0.9 m as a result of theearthquakes. This upheaval can be observed from Points A to C. However, a sharp cave-in from thelevel before the earthquakes can be detected from Points C to E. At Point D, where the sharpest cave-in
was observed, the height difference was about 2 m from the land surface. It could also be determinedthat upheaval resumed from Points F to A’. When comparing the DEMs before and after theearthquakes, it was found that the paddy fields had a more irregular elevation profile on the DEM after
the earthquakes. This is presumably because the image mapping has a low accuracy in areas withvegetation. As a whole, we successfully clarified the vertical deformation of the cracks on the fault
dimensionally and quantitatively.

Fig. 8 Differences between the DEMs before and after the earthquakes at the cracksⒸ ISERD90

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Fig. 9 Cross section at the cracks
CONCLUSIONAs the conclusions, the following points are summarized in this study.
(1) The exact positions of the cracks in paddy fields were specified by the orthophoto mosaic.
(2) Based on the analysis of the differences between the DEMs before and after the earthquakes,
the vertical deformation was clarified dimensionally and quantitatively.
(3) The SD of the elevation values of the DEM after the earthquakes was 0.118 m, assuming thatthe elevation values of the GNSS after the earthquakes were true values. That is, it is possible
to state that the DEMs after the earthquakes was accurate with an SD of 0.118 m.
ACKNOWLEDGEMENTS
The Information Provision Support Team of the Major Disaster Management Headquarters of GSI
provided the aerial photos used in this research in order to support the recovery project implemented byKumamoto Prefecture. We gratefully acknowledge the kindness and support they extended to our study.
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