Hayakawa et al. Progress in Earth and Planetary Science (2017) 4:3
DOI 10.1186/s40645-016-0116-3

Progress in Earth andPlanetary Science

RESEARCH ARTICLE

Open Access

Seismic and inter-seismic ground surface
deformations of the Murono mud volcano(central Japan): a laser scanning approach
Yuichi S. Hayakawa1*, Shigekazu Kusumoto2 and Nobuhisa Matta3

Abstract
A small mud volcano in Murono, Niigata Prefecture, north-central Japan, shows active ground surface
displacements, not only when large earthquakes occur in the region but also during quiescent periods between
earthquake events. The site recently underwent abrupt deformations due to strong regional earthquakes in 2004,
2007, 2011, and 2014, while gradual surface deformations were reported during quiescent periods between theearthquakes. To detect the spatial distribution of the changes in the mud volcano’s ground surface elevation, we
carried out multi-temporal terrestrial laser scanning. Point cloud datasets were registered at different times byminimizing the distance between the closest points in different clouds for stable ground features, which revealed
centimeter- to decimeter-scale deformations around the domain of the conspicuous uplift. The spatial distributionof the deformation triggered by the earthquakes, including both central uplift and peripheral subsidence, exhibits
an elliptical pattern, on which open crack fractures, associated with the earthquake-triggered uplift, were formed.
The displacement and stress fields for the earthquakes were modeled numerically, and anomalously high pressure
and/or weakening of the surficial materials was expected for the formation of fractures in the local domain. In
contrast, continuous uplift was observed during the inter-seismic quiescent periods, the domain of which seems tohave changed after the strong earthquake in 2014. In the coming years, further measurements will be necessary to
unravel the physical subsurface mechanics of the mud volcano.
Keywords: Mud volcano, Terrestrial laser scanning, Point cloud, Digital elevation model, Cracks

Introduction
Mud volcanoes are characteristic landforms that occur
in both subaerial and submarine areas, formed by the
cumulative extrusion of liquid mud (Brown 1990;
Hovland et al. 1997; Kopf 2002). There are thousands ofonshore and offshore mud volcanoes on the Earth(Milkov 2000; Dimitrov 2003), which vent liquid mud,water, gas, and (occasionally) oil, either periodically or
continuously (Hovland et al. 1997). Mud volcanoes arerecognized as a significant source of gas emissions,
including carbon dioxide and methane, into the atmosphere. This emitted gas is supplied from deeply buried
sediments (Dimitrov 2002, 2003; Milkov 2005) and may
contribute to global climate change (Etiope 2005; Judd
* Correspondence: hayakawa@csis.u-tokyo.ac.jp
1
Center for Spatial Information Science, The University of Tokyo, 5-1-5
Kashiwanoha, Kashiwa, Chiba 277-8568, Japan
Full list of author information is available at the end of the article2005). The chemical and isotopic components of themud, which include water and oil, can be an indicator ofnatural resources such as petroleum (Kopf 2002; Milkov
2005) and can be strongly affected by near-surface(several to tens of kilometers in depth) geological structures, particularly in compressive tectonic zones(Martinelli and Dadomo 2005b; Feyzullayev et al. 2005;
Mazzini 2009).
The activity of mud volcanoes is strongly related totectonic conditions such as the seismicity of the region(Panahi 2000, 2005; Martinelli and Dadomo 2005a;
Mellors et al. 2007; Mazzini 2009). In many cases, large
remote earthquakes trigger mud volcano eruptions(Chigira and Tanaka 1997; Mellors et al. 2007; Mori andKano 2009). In rare cases, these eruptions can, in turn,trigger weak local earthquakes (Panahi 2005). Furthermore, surface deformation of and gas emission frommud volcanoes can occur not only periodically through© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made.

Hayakawa et al. Progress in Earth and Planetary Science (2017) 4:3

the occurrence of earthquakes but also continuously inquiescent regimes (Dimitrov 2002; Etiope 2005; Moerz
et al. 2005; Kusumoto et al. 2014). Among other factors,
the surface deformation of mud volcanoes is one of themost distinct and clear indicators of their activity(Hovland et al. 1997). Therefore, investigating the morphological characteristics and dynamics of surface deformation is crucial in revealing the detailed
mechanisms and future activity of mud volcanoes. In
particular, although earthquake-triggered surface deformation of mud volcanoes is often obvious (e.g.,
Manga et al. 2009; Onishi et al. 2009; Rudolph andManga 2012), inter-seismic deformation of mud
volcanoes is relatively less well recognized, necessitating
further investigation (Kusumoto et al. 2014).
The deformation of active mud volcanoes has been investigated using various approaches on a wide variety of
scales (e.g., Kopf 2002; Wang and Manga 2010). For
large mud volcanoes (on the scale of hundreds of meters
to kilometers), surface deformation can be detected bylong-range remote sensing techniques, including satelliteinterferometric synthetic aperture radar (InSAR)(Mellors et al. 2007; Fukushima et al. 2009; Antonielli etal. 2014), aerial photographs (Shakirov et al. 2004; Istadi
et al. 2009), and airborne laser scanning (ALS) (Doshida
et al. 2007). Detection of surface deformation of small
mud volcanoes (smaller than hundreds of meters) requires finer measurements that may include leveling,
total station, and the use of high-precision global navigation satellite system (GNSS) (e.g., Onishi et al. 2009;
Kusumoto et al. 2014, 2015). Even these approaches areoften limited in their ability to reveal the spatial variation of surface deformation because of the low spatial
density of their measurement points. As an efficient approach for exploring spatially variable deformation oflandforms, terrestrial laser scanning (TLS) has been applied to obtain high-definition topographic data by using
dense point clouds on the ground surface (e.g., Heritageand Large 2009; Whitworth et al. 2006; Hayakawa andOguchi 2016). TLS enables the detection of temporalchanges in topography at millimeter to centimeter scales
when the measurements are performed multiple times
and the multi-temporal point clouds are accurately registered to each other (Lane et al. 2003; Teza et al. 2007;
Olsen et al. 2009; Milan et al. 2011; DeLong et al. 2015).
Thus, this approach is potentially advantageous in the detection of spatially variable surface deformation of small
mud volcanoes, although such application of TLS on mud
volcanoes has been limited so far.
Performing a preliminary analysis on TLS data,
Hayakawa et al. (2016) measured temporal changes in
the ground surface of a small mud volcano in Murono,
central Japan, within an accuracy of centimeters. This
study expands this analysis to a longer time period,

Page 2 of 16

including two major earthquakes that affected the study
region, aiming to give a primitive discussion on the links
between the surficial changes and subsurface fluid
dynamics of the mud volcano, with and without the
impact of earthquake events.

Methods/Experimental
Study site

The Murono mud volcano is located in Tokamachi City,
Niigata Prefecture in north-central Japan (Fig. 1). The
monthly mean air temperature ranges from −0.2 °C in
January to 24.9 °C in August, and the mean annual precipitation is 2496.7 mm, about one third of which is supplied as snow in winter (Japan Meteorological Agency2016). Many fold structures in the NE-SW direction arepresent in the area, and the study site is located in thevicinity of an unnamed anticline limb between the
Gimyo anticline and the Naradate syncline (Noda 1962,
Takeuchi et al. 2000) (Fig. 1b). The substrate rock in the
study site is massive black mudstone of the Early
Pliocene Sugawa Formation, which widely covers boththe unnamed and Gimyo anticlines (Sm in Fig. 1b).
Younger rock formations (Late Pliocene to Early
Pleistocene) appear toward the Naradate syncline southeast (Fig. 1b), while older rocks appear in the farther
southeast areas, toward another major anticline (theMatsunoyama anticline, outside the map boundary ofFig. 1b). Because of such geological structures, there isabundant production of petroleum and natural gas, aswell as hot springs in the area. The activity of the
Murono mud volcano can be a key to unraveling the
subsurface structure and mud flow dynamics in the area.
As a result, various studies have been carried out involving this mud volcano using geodetic, geophysical, andgeochemical approaches (e.g., Onishi et al. 2009; Shinya
and Tanaka 2009; Suzuki et al. 2009; Etiope et al. 2011).
While convex-up relief is commonly observed in large
mud volcanoes that are hundreds of meters in lengthand tens of meters in height (Higgins and Saunders
1974; Chigira and Tanaka 1997), the small Murono mud
volcano has a relatively flat surface, with a very small
mound having a height of only decimeters.
The altitude of the site is about 316 m above sea level(a.s.l.), and the main active area of the mud volcano isapproximately 130 m × 180 m (Fig. 1c). The western sideof the site is partially deformed, while the center of thesite, which contains a vent, does not show obvious uplift(Kusumoto et al. 2014, 2015). In contrast, the easternside has particularly large and frequent deformations. A
portion of this side approximately 50 m × 60 m (Fig. 1c)
was selected as the target zone of this study.
In the last decade, large earthquakes have hit the region frequently, and the mud volcano has been significantly deformed by the strong jolts. Such deformations

Hayakawa et al. Progress in Earth and Planetary Science (2017) 4:3

aPage 3 of 16bcFig. 1 Study area: Murono mud volcano. a Overview. b Regional view on a background of a 1:50,000 geological map (after Takeuchi et al. 2000)
with topographic hillshade. Black solid and dashed lines indicate the anticline and syncline structures, respectively. Sm massive black mudstone of
the Sugawa Formation (Early Pliocene), Tm, Ta, Ts massive siltstone, interbedded sandstone and siltstone, and thick-bedded sandstone, respectively, of
the Tamugigawa Formation (Late Pliocene), Hs interbedded sandy siltstone of the Higashigawa Formation (Late Pliocene), Uc marine sand with gravelof the Uonuma Formation (Late Pliocene to Early Pleistocene). c Aerial image of the study site. The present vent of the mud volcano is at the center,and this study’s target zone is located in the eastern side of the area. Triangular arrows indicate locations and directions of photographs shown in Fig. 2of the site have been investigated by different methodsof topographic measurements, including GNSS, leveling,
and TLS surveys. At the time of the Niigata-ken

Chuetsu-oki Earthquake (Mw = 6.6, epicenter 44 km
away from the site) in July 2007, the maximum acceleration at a monitoring station near the site (NIG021-

Hayakawa et al. Progress in Earth and Planetary Science (2017) 4:3

Tokamachi, 21 km away) was recorded to be 3.02 cm/s2(National Research Institute for Earth Science and Disaster Resilience 2016). Although there was the Niigata-ken
Chuetsu Earthquake in October 2004 (Mw = 6.7, epicenter 33 km away from the site) with the maximum acceleration of 17.5 cm/s2 at NIG021, the influence of thisearthquake on the mud volcano is unknown.
Onishi et al. (2009) performed extensive GNSS surveys
at the site with more than 4000 measurement points overthe paved ground surface in June 2006 and September
2008. Although the direct influence of the 2007 earthquake
is unknown due to the 1 year time lag between earthquake
and the later measurement, it was assumed that theamount of vertical deformation of the mud volcano during
this period was closely related to the 2007 earthquake.
According to the widespread GNSS measurements, thecumulative vertical deformation of the ground surface inthe period from 2006 to 2008 was spatially variable: themaximum uplift was observed to be approximately
400 mm near the central portion of the mud volcano (thenorthwestern half of the surveyed target zone; Fig. 1c),while the easternmost side of the mud volcano (thesoutheastern half of the surveyed target zone; Fig. 1c)showed less uplift (<100 mm) (Onishi et al. 2009). The areaof high uplift is spatially correlated with a high attenuation
zone for ground penetrating radar (Yokota et al. 2008),
indicating the presence of very shallow mudstone layers
decomposed into soft clay with high water content. On theother hand, the area with less uplift correlates well with azone of high S-wave velocity in a very shallow (<20 mdeep) area (Onishi et al. 2009), likely unaffected by the
mud volcano activity.
The North Nagano Prefecture Earthquake (Mw = 6.4,
epicenter 16 km away, maximum acceleration of
3.08 cm/s2) in March 2011 and the Nagano-ken
Kamishiro Fault Earthquake (Mw = 6.7, epicenter 76 km
away, maximum acceleration of 0.22 cm/s2) inNovember 2014 also caused remarkable vertical deformations of greater than 200 mm (revealed by laser scanning) and 46 mm (by leveling survey), respectively(Matta et al. 2012; Kusumoto et al. 2015; National Research Institute for Earth Science and Disaster Resilience2016). Vertical deformation continues even in the interseismic period with seasonal variations of about ±5 mm,
revealed by leveling surveys (Kusumoto et al. 2014). Although it is known that the land manager repaired theground pavement after distinct cracks were identified
subsequent to the earthquakes (Fig. 2), we suppose that
artificial modifications had only limited effects on thesurface elevation because their purpose was only to replace the fractured pavement, which would not change
the surface elevation significantly. Indeed, the fractures
formed in 2011 (Fig. 2a, c, e) are almost as clean as observed in 2013 (Fig. 2b, d, f ), but the pavement surface

Page 4 of 16

was not truly flattened and the uplifted deformations
surrounding the paved surface remain.
Data acquisition and analysis
Topographic measurements by terrestrial laser scanning

Field surveys were carried out four times between June
2011 and November 2015. The North Nagano Prefecture
Earthquake (March 2011) occurred before any of thesesurveys, and the Kamishiro Earthquake (November2014) occurred just before the third one.
The terrestrial laser scanners used for the measurements
include a Topcon GLS-1500 scanner for the first set ofmeasurements in 2011 and Trimble TX5 scanners for theother measurements in 2013 to 2015. The GLS-1500 is amedium-range scanner, with a maximum measurable distance of 500 m at a scan rate of 30,000 points per secondand a range accuracy of 4 mm within 150 m of the unit
(Topcon 2010). The TX5 is a lightweight short-range
scanner with phase-based laser ranging capability, with amaximum measurable distance of 120 m at a maximum
scan rate of 900,000 points per second, and a range accuracy of 0.3–1.1 mm at 10–25 m from the unit (Trimble
Navigation Limited 2012). Topcon ScanMaster v.2.1 andTrimble RealWorks v.8.1 software, bundled with the scanners, were used for the data processing of the point
clouds. Both scanners have the ability to adjust their horizons using built-in inclination sensors.
Because laser emissions are directional, measurements
taken from only one scan position may result in insufficient point cloud coverage with a large fraction of
shadows in the data (Hayakawa and Oguchi 2016). In
order to cover the target area correctly with a laser scanner, multiple scan positions should be set in the field at
the time of each measurement. The point clouds fromthe different scan positions must then be registered andmerged to obtain point cloud data coverage of the entire
target zone (internal registration). For this, we apply a
cloud-based registration method, which utilizes partial
point clouds that represent key morphological features,
including the ground surface of the target area, tree
trunks, and poles in the surrounding area. In this cloudbased registration, the iterative closest point (ICP)
algorithm is performed to minimize the distances between the nearest points on key features (Besl and
McKay 1992; Bergevin et al. 1996). In this algorithm, apoint cloud is iteratively transformed to fit another reference point cloud, based on overlapping areas with thesame morphological features. The amount of error of
the cloud-based registration depends primarily on thedensity of the points, and accuracy on the scale of several millimeters can be obtained if the point density has
millimeter-scale spacing (e.g., Teza et al. 2007). The registered point clouds are all merged into one point clouddata point for each survey time.

Hayakawa et al. Progress in Earth and Planetary Science (2017) 4:3

Page 5 of 16

a

b

c

d

e

f

Fig. 2 Photographs of the site. a, c, e The open cracks on the surface pavement formed by the 2011 earthquake. b, d, f The repaired pavement.
Photograph locations are shown in Fig. 1c

The georeference of the point clouds, i.e., the externalregistration of the merged point cloud onto geographicalcoordinates, was primarily performed using several target references whose geographical coordinates (inUniversal Transverse Mercator (UTM) Zone 54N,
JGD2000 datum) are obtained from GNSS measurements with the capability to post-process carrier-phasecorrections. We used a Trimble GeoExplorer 6000XH as
a receiver, and the positioning log data were correctedusing data from nearby GEONET (GNSS network inJapan) base stations, provided by the Geospatial Authority of Japan. The fix solution provides centimeter-levelaccuracies for the GNSS positioning. However, GNSSbased georeferencing errors of point clouds often exceed
centimeters, which restrict accurate comparison of thepoint clouds at different times. Therefore, we refined thealignment of the point clouds at different times bymeans of cloud-based ICP registration based on featuresthat are thought to stay in the same location, and do notchange shape, distributed around the target zone. For
this process, the changing main target area of measurement is cropped out, and stable areas that do not include changes in surrounding areas, such as major tree
trunks, electric poles, and buildings, are used for thealignment. The ICP procedure was repeatedly applied torefine the external registration to minimize the point-topoint distances between the clouds. The third measurement dataset in 2014 was set as the reference, as it had
the most accurate GNSS-based georeferencing. Each of
the other datasets was successively aligned to its adjacent dataset.
To examine the topographic changes in the groundsurface at the target zone, the zone was first extracted
from the original point cloud, while unnecessary points

Hayakawa et al. Progress in Earth and Planetary Science (2017) 4:3

representing vegetation and other artificial objects suchas buildings and poles were removed. Then, the digital
elevation model (DEM), a two-dimensional raster dataset representing the topography projected on the UTM
coordinates, was generated from the extracted point
cloud. Geographic information system (GIS) software(ESRI ArcGIS 10.3) was used for the DEM data processing. The resolution of DEMs is determined based on thespatial density of their point cloud data. In the conversion from point cloud to DEM, a triangular irregular
network (TIN) model is generated to perform linear
interpolation for the randomly distributed points. Furthermore, areas far from the scanner position, that haveinsufficient point density, less overlapping scan coverage,
or vegetation (mostly low-height plants, <40 cm) where
the ground surface is hard to detect, were cropped out by
setting a mask on the DEM and excluded from the following analyses. Three section lines were then set in the target zone to extract topographic profiles from the DEMs.
Topographic data comparisonsA 2 m resolution DEM, obtained by ALS and used as
the initial condition of the comparative analysis withTLS data, was also used for topographic data comparisons. The ALS measurements were performed in July
2004 by Kokusai-Kogyo Co., and a filtered digital terrain
model (DTM) was derived, showing the ground surface
in the region after removing ground objects such as
vegetation and buildings (Fig. 1b).
Differences in DEMs were then computed for eachperiod between consecutive survey times. The four periods
are defined as period I, 2004 to 2011; period II, 2011 to2013; period III, 2013 to 2014; and period IV, 2014 to 2015.
Crack mapping and numerical modeling of stress field

Since the target zone exhibited apparent ellipticalbulging of the ground surface with distinct open cracks
in the paved surface at the time of the June 2011 measurement, the open cracks (fractures) were traced using
the DEM generated for that time. Hillshade image andlocal variation of elevation calculated from the DEM(3 × 3 cell statistics) were supportively used to highlightthe crack features to be manually extracted. The generalorientation of the crack lines was then summarized.
Cracks with orientations similar to those in 2011 werealso visually observed at the time of measurement in
December 2014, just after the Kamishiro Earthquake, although they could not be mapped because they were notdistinctly open enough to be identified as a surficial
shape in the point cloud.
We performed numerical modeling of the vertical displacement and stress fields for crack formation associated with the elliptical uplift. The vertical displacement
field of a uniformly loaded elliptical plate with a clamped

Page 6 of 16edge is given as follows (e.g., Timoshenko andWoinowsky-Krieger 1959):
2x2 y 2uz ¼ w0 1− 2 − 2 ;
a b

ð1Þ

where a and b are the semi-major axis and semi-minor
axes, respectively, and


p 24
16
24 −1
w0 ¼
þ
þ
:
ð2Þ
D a4 a2 b2 b4
In Eq. (2), p is a load acting uniformly on the plate
and D is the flexural rigidity of the plate defined by thefollowing equation:
D¼

Eh3
:
12ð1−v2 Þð3ÞHere, h, E, and v are the thickness, Young’s modulus,
and Poisson’s ratio of the plate, respectively.
Since the horizontal displacement components of thevertical displacement are ux = −z(∂uz/∂x) and uy =−z(∂uz/∂y) (e.g., Timoshenko and Woinowsky-Krieger
1959; Nakahara et al. 2001), the horizontal displacement
fields at the surface (z = h/2) are given as follows:


2w0
x2 y2
ð4Þ
ux ¼ 2 hx 1− 2 − 2 ;
a
a b


2w0
x2 y 2
ð5Þ
uy ¼ 2 hy 1− 2 − 2 :a bbStress fields (σx, σy, σz, τxy, τyz, τzx) occurring on theplate surface caused by bending due to load p are given
as




 
3p 1
v 1 3
v 2 1 1 3v 2
x
y ;
þ
−
þ
−
þ
lh2 a2 b2 a2 a2 b2
b2 a2 b2




 
3p v
1 1 3v 11 v
3
σ y ¼ 2 2 þ 2 − 2 2 þ 2 x 2 − 2 2 þ 2 y2 ;
lh a
b a a
b
b a
b
σx ¼

ð6Þ
ð7Þ

−6ð1−vÞ
pxy;
a2 b2 h2 lð8Þ

σ z ¼ τ yz ¼ τ zx ¼ 0;

ð9Þ

τ xy ¼and l is defined by
l¼

3
2
3
þ 2 2þ 4:
4
a
a b
b

ð10Þ

Results and Discussion
Summary of topographic data

Based on the land cover type (paved or vegetation) andthe availability of data as shown by the overlapping TLS
point clouds, the target area for the analysis (2188 m2)

Hayakawa et al. Progress in Earth and Planetary Science (2017) 4:3

was defined on the paved ground surface (Fig. 3a). Figure 4
shows an oblique view of the point clouds, and Table 1
summarizes the properties of the four point clouds foreach TLS measurement. The density of the point clouds
in the area of interest ranges from 583.9 to 35,814.1 points
per square meter, which is equivalent to an average point
spacing of 5.3–41.4 mm. Consequently, the DEM resolution achievable from these point clouds is 50 mm forthe 2011 data and 10 mm for 2013, 2014, and 2015.

Page 7 of 16

The 2011 point cloud is relatively sparse compared tothe others because of the limitations of the device used(medium-range GLS-1500 scanner). Although the point
clouds from 2013 to 2015 were all obtained using thesame TX5 short-range scanner, the point densities vary
due to differences in the scanning settings and environmental conditions. Particularly, the relatively sparsedensities for 2014 and 2015 are due to wet conditions
on the ground surface from rain (Fig. 4c, d).

abFig. 3 Detailed view of the target zone in the Murono mud volcano. a Areas showing number of overlaps of the TLS measurements. The target
zone is shown by a yellow polygon. b Location of the three profile sections (Fig. 7) in the target zone

Hayakawa et al. Progress in Earth and Planetary Science (2017) 4:3

Page 8 of 16

a

b

c

d

Fig. 4 Point clouds obtained by TLS in a 2011, b 2013, c 2014, and d 2015. The point clouds are shown in RGB colors, although the 2015 point
cloud is in monochrome because color capturing was skipped in the field as there was insufficient sunlight after sunset

The accuracy of the internal registration ranges over
2.9–9.8 mm, which is sufficiently small for the average
spacing of the entire set of point clouds. As noted before, the third measurement dataset in 2014 was set as
the reference, and each dataset was successively aligned
to the adjacent dataset. The external registration errors
from the ICP algorithm were 6.2–19.8 mm for this dataset. These are comparable to the previous accuracy

assessment for TLS measurement at this site reported by
Hayakawa et al. (2016). Changes in the land surface exceeding these values (>20 mm) are discussed in the following sections.
Temporal changes in surface elevation

Differences in the elevations of the DEMs, rasterizedfrom the point clouds, were computed for each period.

Table 1 Properties of TLS-derived point clouds for each measurement
Measurement occasion

1

2

3

4

Year

2011

2013

2014

2015

Date

Jun. 23

Dec. 5

Dec. 4

Nov. 27

Terrestrial laser scanner used

GLS-1500

TX5

TX5

TX5

Number of scan position

4

8

7

10

Weather conditions

Cloudy

Sunny

Rainy

Rainy to cloudy

Internal registration error (mm)

4.0

2.9

7.9

9.8

Horizontal GCP error (mm)

–

–

12.1

11.7

Vertical GCP error (mm)

–

–

23.1

17.3

Number of GCPs

–

–

11

3

External registration errors (mm)

6.2

15.7

–

19.8

Total number of measured points

1,973,134

130,137,112

102,864,460

47,933,335

Number of points used

1,082,832

52,158,136

69,169,926

30,018,333

Coverage area (excluding no data cells) (m2)

1854

2187

1931

2122

Point density (pt/m2)

583.9

23,845.2

35,814.1

14,143.6

Average point spacing (mm)

41.4

6.5

5.3

8.4

Hayakawa et al. Progress in Earth and Planetary Science (2017) 4:3

The centimeter-scale vertical changes in the ground surface appear to be spatially variable (Fig. 5). Figure 6
shows the histograms of surface elevation changes, displaying their aerial percentage for each period (I–IV),and Table 2 shows the basic statistics (mean, standard
deviation, 1st and 99th percentiles) and the mean rate ofelevation change. Here, in order to avoid erroneous outliers, the 1st and 99th percentiles serve as proxies forthe minimum and maximum values. Figure 7 illustrates
the topographic profiles of the target area at the different
times. The initial ground surface in 2004 appears to berelatively flat (Fig. 7), and changes in elevation aroundthe dome-like uplift (Fig. 5) seem to accumulate, forming a symmetric pattern of profiles throughout themeasurement periods (Fig. 7). On the other hand, thesoutheastern area is characterized by a continuous decrease in ground surface elevation since 2004 (Figs. 5
and 7c). More details of the temporal changes in the

Page 9 of 16

Fig. 6 Distribution of elevation differences within the target zone foreach period

a

b

c

d

Fig. 5 Differences in DEMs for each period, showing temporal changes in ground surface elevation. Areas in blue indicate uplift, while areas inyellow to red show subsidence. a Period I (July 2004 to June 2011, 83 months). b Period II (June 2011 to December 2013, 29 months). c Period III(December 2013 to December 2014, 12 months). d Period IV (December 2014 to November 2015, 12 months)

Hayakawa et al. Progress in Earth and Planetary Science (2017) 4:3

Page 10 of 16

Table 2 Amount and rate of changes in ground surface elevation for each period
Period

I

II

III

IV

Year

2004–20112011–20132013–2014

2014–2015

Duration (months)

85

30

12

Strong earthquakes and maximum acceleration

2

12
2

2004 Chuetsu (17.5 cm/s )2007 Chuetsu-oki (3.02 cm/s2)
2011 N Nagano (3.08 cm/s2)

2014 Kamishiro (0.22 cm/s )Mean elevation change (mm)

44.1

4.7

0.2

11.6

Standard deviation of elevation change (mm)

128.4

19.8

19.0

12.8

1st percentile−222.5

−34.8

−46.3

−19.5

99th percentile

397.5

59.7

30.0

30.0

Mean rate of elevation change (mm/year)

6.2

1.9

0.2

11.7

a

b

c

Fig. 7 Topographic profiles along the sections in the target zone.
Locations of the three section lines (A–A', B–B', and C–C') are shown in
Fig. 3b. The areas outside the target zone are masked with gray in (c)ground surface elevation for each period are described
below.
In period I, positive changes in elevation (uplift) areapparent around the center of the target zone where
there was a concentration of distinct open cracks forming an elliptical pattern in 2011 (P in Fig. 5a). On theother hand, negative changes (subsidence) were also
found in the surroundings (Fig. 5a). The most distinct,
wide ranging changes in both the positive and negative
directions (Fig. 6) are likely due to both the longest
elapsed time between measurements (approximately
7 years) and the distinct changes caused by the two large
earthquakes, which had accelerations of 17.5 cm/s2 by
2004 Chuetsu and about 3.0 cm/s2by 2007 Chuetsu-oki
and 2011 North Nagano (Fig. 5a, Table 2). Over the entire period, uplift seems to have been more dominant
than subsidence, resulting in a net elevation change of
44.1 mm with a maximum uplift of 397.5 mm (Table 2).
Onishi et al. (2009) detected a maximum surface upliftof about 400 mm in the conspicuous uplift area during
2006 and 2008. Based on the map provided by Onishi etal. (2009), the spatially averaged uplift of this period(2006–2008) in the target zone is visually assumed to bearound 200 ± 50 mm, which is considerably higher thanthe mean uplift of period I (44.1 mm) observed in thisstudy (Table 2). Even if the subsided area is excluded,
the mean value for only the uplifted area in period I is
calculated to be 133 mm, which is still smaller than theassumed mean uplift during 2006–2008. This indicatesthat considerable subsidence could have occurred in theconspicuous uplift area during the inter-seismic periodof 2008–2011. Slight post-earthquake subsidence was actually observed in the area after the 2011 earthquake as
described later (period II, Fig. 7b), and such subsidence
could have been dominant after the 2007 earthquake.
Although the details are unknown, extensive repair work
might also explain the ground surface reset after 2008.
In any case, supposing that the ground surface elevation

Hayakawa et al. Progress in Earth and Planetary Science (2017) 4:3

after 2008 decreased to the level of the mean uplift in
2006–2008 (~200 mm) due to either natural subsidenceor artificial modification, the uplift directly affected by the2011 earthquake is assumed to be about 200 mm. This is
the maximum value of the potential uplift by the 2011
earthquake. Since separating the effects of the 2007 and2011 earthquakes precisely is difficult, we assume thepotential uplift by the 2011 earthquake to be 0–200 mm.
On the other hand, the large area of subsidence seen inperiod I (partially reaching <−200 mm; Figs. 5a and 6,
Table 2) was not fully recognized in 2006–2008 by Onishi
et al. (2009). They only provided a map showing a limitedarea of subsidence in the peripheral area, although theexact locations of subsidence were not mentioned and are
difficult to identify in their map. The subsidence could
have occurred following the 2007 earthquake, as noted
above. However, as in the case of period III described later,
the subsidence could also be co-seismic. Our data for
period I have insufficient temporal resolution to identify
the exact timing and amount of such a co-seismic upliftand subsidence in 2007 and 2011, but the possibility thatboth uplift and subsidence occur at such a local scale as aresult of earthquakes is worth further assessment withrespect to the co-seismic activity of the mud volcano.
Although the time span of period II (30 months) is
longer than periods III and IV (12 months for each), theunchanged area is the largest in period II (white areas inFig. 5b and the highest peak in Fig. 6), likely because of thelack of distinct earthquakes. The mean elevation change
was slightly positive (4.7 mm; Table 2), however. Although
this amount of uplift is less than the significant level ofchange detection limit (20 mm), the spatial variation in the
uplift indicates that partial uplift around the previous
cracks (P in Fig. 5b) contributed to the net positive change.
Note that the large maximum value of uplift in period II(59.7 mm, Table 2) could be due to the difference in the
deep crack bottom in 2011 and repaired surface in 2013
and the amount of natural uplift could be a few centimeters (Fig. 7a). In addition, the eastern side shows some
negative changes (Q in Fig. 5b), which is also apparent insections B–B′ and C–C′ (Fig. 7b, c). Although the area
where subsidence exceeded the detectable level (20 mm) islimited, this demonstrates that post-earthquake uplift andsubsidence in period II is spatially variable.
In period III, the elliptical pattern of uplift in the central portion is obvious (P in Fig. 5c), while subsidence
also appears on the eastern side (R in Fig. 5c). The contrast of uplift and subsidence is also clear in profile section C–C′ (Fig. 7c). Compared with periods II and IV,
the histogram of elevation change in period III has arelatively wide distribution (Fig. 6), but the mean change
is nearly zero (Table 2). This suggests that the 2014
earthquake likely affected the spatial pattern, including
both uplift and subsidence. The maximum uplift

Page 11 of 16(30 mm) in this period roughly corresponds to that derived from a leveling survey (46 mm, Kusumoto et al.
2015) but is less than that observed in period I. Thismay be attributed to the relatively low acceleration experienced in the area (0.22 cm/s2) in the 2014 earthquake(Table 2).
Unlike the earlier periods, period IV shows less change
in the central portion, having no detectable differences(±20 mm), while it shows positive surface changes (uplift) on the eastern side (S in Fig. 5d). Though not exceeding the significant level of ±20 mm, slightsubsidence is also observed in the southwestern side of
profile section A–A′ (Fig. 5a). Thus, the spatial patternof uplift and subsidence in this period is quite different
from the others. Furthermore, the histogram of elevation
change in period IV shows a biased positive trend (Fig. 6),
and the mean value of uplift is large (11.6 mm; Table 2).
In turn, detectable subsidence areas are almost absent inperiod IV (Fig. 5d). The mean uplift rate of period IV(11.7 mm/year for 12 months) is considerably higher
than that of period II (1.9 mm/year for 30 months). Bothare assumed to be gradual since there were no distinct
earthquakes in either period.
Formation of surface fractures by earthquakes

In the earthquake-affected periods I and III, the areas of
uplift show elliptical spatial patterns (Fig. 5a, c). The cumulative changes in surface elevation after the first TLS
measurement, from 2011 to 2015, also reflect this elliptical pattern, whose major axis direction was W36°N(Fig. 8). Figure 8 also shows the mapped crack lines on
the paved ground surface found in June 2011, whose
average orientation is W37.5°N, almost the same as thatof the elliptic uplift. This may reflect the undergroundfluid dynamics of the mud, likely caused by pressure
variability triggered by the earthquakes. Here, we discuss
the fracture patterns and pressure estimates related tothe earthquakes. As noted, in these earthquake-affectedperiods, there were not only areas of uplift but also areasof subsidence, particularly in the southeastern side of
the target zone. Although Onishi et al. (2009) argued
that because no significant surficial change was present
through the 2007 earthquake, the southeastern area isunaffected by the mud volcano activity, the presence ofsubsidence found in this study may suggest that the
mud volcano affects the surrounding area extensively,
inducing subsurface lateral migration of fluid mud.
However, the target zone of this study does not seem tocover the entire peripheral area that may experiencesubsidence. It does include the area with conspicuous
uplift that exhibits more clear features, comprising theelliptical uplift pattern and surficial fractures. Therefore,
we simply focus on the pressure mechanisms of upliftand fractures.

Hayakawa et al. Progress in Earth and Planetary Science (2017) 4:3

Page 12 of 16

Fig. 8 Cumulative surface elevation changes throughout periods II–IV based on TLS-derived data. Traces of the open cracks observed in 2011 areshown as solid black lines. Dashed line indicates the elliptical uplift zone

Although Kusumoto et al. (2015) pointed out that the
uplift area was elliptical with major and minor axes ofabout 80 and 40 m, respectively, the conspicuous, essential uplift area is narrower. In previous studies, the conspicuous uplift areas were reported in the same location,and they have a common size with major and minor
axes of about 40 and 30 m, respectively. In order tofocus on the mechanisms of uplift and fracture formation observed in this study, we modeled the uplift area
using a = 20 m and b = 15 m for Eqs. (1)–(10).
In the study area, an elastic surface layer, estimated to
be about 1 m thick, was identified using the surface
wave method, which estimates distributions of shearwave velocity by surface wave inversion (Onishi et al.
2009). In addition, because the layer is at the surface andits elastic constants have not been measured, we assumed a low Young’s modulus of 1 GPa and a typicalPoisson’s ratio of 0.25 for the layer (e.g., Bell 2000).
We first estimated the magnitude of an overpressurethat could form the uplift that potentially reached
200 mm, caused by the 2011 North Nagano Prefecture
Earthquake. To assess the maximum uplift, we took x =y = 0 in Eq. (1) and, with Eqs. (1), (2), and (3), obtained
the equation that gives the maximum uplift,12ð1−v2 Þp 2416
24 −1
uz max ¼þþ
:a4 a2 b2 b4
Eh3
We rewrite this equation as

ð11Þ



Eh3 uz max 24
16
24
;
þ
þ
p¼
12ð1−v2 Þ a4 a2 b2 b4

ð12Þ

and by taking a = 20 m, b = 15 m, v = 0.25, h = 1.0 m,
E = 1 GPa, and uz_max = 200 mm, we obtained p =14.26 kPa as the overpressure that gives an uplift of
200 mm.
In Fig. 9a, we show the vertical displacement field
caused by the overpressure (p = 14.26 kPa). The calculated vertical displacement field turns out to be consistent with the observed vertical displacement field.
Figure 9b shows the distribution of the principal stressaxes around the center part of the uplift. The maximum
principal stress axes, σ1, are distributed along the major
axis of the elliptical uplift area, and the minimum principal stress axes are perpendicular to σ1, so they are distributed along the minor axis of the elliptical uplift area.
This indicates that if the minimum principal stressexceeded the tensile strength of the medium, open fractures (cracks) would appear at the surface and theirstrike directions would correspond to the direction of
the maximum principal stress axis, which is the major
axis of the elliptical uplift area.
Fractures observed at the surface are distributed along
the major axis of the elliptical uplift area (Fig. 8). This
distribution pattern is consistent with the direction of
the maximum principal stress axis shown in Fig. 9b. In
addition, the observed fractures are basically open fractures, including some strike-slip fracturing, and it is
known that the in situ tensile strength of most of theHayakawa et al. Progress in Earth and Planetary Science (2017) 4:3

ab

Fig. 9 Modeled vertical displacement and stress fields. Verticaldisplacement and principal stress fields estimated for a uniformly
loaded elliptical plate model with a clamped edge. a Verticaldisplacement field caused by overpressure of 14.26 kPa(displacement in meters). The modeled plate is 1 m thick with
Young’s modulus of 1 GPa and Poisson’s ratio of 0.25. b Principal
stress field caused by overpressure of 14.26 kPa. Blue and red ticks
are the maximum principal stress and minimum principal stress axes,
respectively. Stresses are in megapascal

rocks is between 0.5 and 6 MPa (e.g., Haimson andRummel 1982; Amadei and Stephansson 1997; Schultz
1997; Gudmundsson 2011). The general tensile strengthof asphalt mixtures is known to be around 4 MPa whencolder than 0 °C but less than 1 MPa when thetemperature is more than 10 °C (Yoshida et al. 2001).
Since the maximum calculated stress σ3 was about
1.5 MPa (Fig. 9b), an uplift of 200 mm can form fractures at the paved asphalt surface, particularly in higher
summer temperatures. From the observed data and simulated results, we can conclude that an elliptical upliftarea potentially reaching 200 mm can be explained byan overpressure change as high as 14.26 kPa. Furthermore, we can conclude that fractures were formed as
the minimum principal stress (>1.5 MPa) exceeded thetensile strength at this elliptical area surface and were

Page 13 of 16

propagated in the direction of the maximum principal
stress axes. In turn, assuming that the tensile strength ofthe paved asphalt surface is as low as 1 MPa, fractures
could have formed with an uplift of 133 mm or more.
Although the exact uplift amount by the 2011 earthquake is unknown, the calculation above indicates thepotential uplift at this time, given the extensive formation of fractures, to be approximately 100–200 mm.
Although Onishi et al. (2009) does not report on theoccurrence of fractures, fractures would have formed
and been observed at the surface because the uplift,
which exceeded 400 mm, would have produced a minimum principal stress of more than 3 MPa. On the other
hand, since it is estimated that the uplift of 46 mm
caused by the 2014 Kamishiro Fault Earthquake(Kusumoto et al. 2015) would have produced a minimum principal stress of 0.35 MPa, the uplift would nothave formed open fractures if the pavement’s tensile
strength at the site were 0.5 MPa or higher. However,many open fractures were actually observed at the surface, and their distribution pattern was similar to thepattern shown in Fig. 8. Although the tensile strength ofasphalt material can drop to 0.2–0.4 MPa at atemperature of around 20 °C (Yoshida et al. 2001), theground surface temperature of the site on the autumn
night of the earthquake (22:08 on November 22) could
not have been that high. From observations of open fracture formation caused by such low tensile stress, we caninfer a decrease of the tensile strength at this site, including in the subsurface rocks, caused by repeated tensile fracturing, since conspicuous uplifts by earthquakes
and fractures have always been formed in the same area,
at least until the 2014 earthquake (Fig. 5).
Seismic and inter-seismic surface deformations

The spatial pattern of the mud volcano’s vertical displacement was found to be different for the earthquakeaffected periods (I and III) and the inter-seismic periods(II and IV). The elliptical pattern of the uplift and thesubsidence distribution, as well as the formation of surface fractures, characterizes the earthquake-affected periods (Fig. 5a, c), whereas the gradual changes in theinter-seismic periods are spatially variable but result in
the dominance of uplift (Table 2).
Although the ground surface tends to generally riseduring the inter-seismic period, the patterns of surface
uplift are different for period II and period IV. In period
II, the uplift pattern follows the crack fractures formedby the 2011 North Nagano Prefecture Earthquake, i.e.,
the largest uplifts are observed along the crack lines(Figs. 5b and 7a). Similarly, the center of uplift is concentrated in the northwestern area in periods I–III. In
contrast, a widespread uplift pattern in period IV wasfound in the eastern side of the target area (Figs. 5d andHayakawa et al. Progress in Earth and Planetary Science (2017) 4:3

7b), while fewer changes were observed in thenorthwestern area where the conspicuous uplift had
been previously observed (Figs. 5d and 7a). This shift in
the location of uplift may indicate a change in local subsurface fluid dynamics after the 2014 Nagano-ken
Kamishiro Fault Earthquake. The earthquake could havetriggered a change in the local pressure field within thedomain of the mud volcano.
A large-scale change in the center of the activity of a
mud volcano may be related to the dynamics constrained by the lithological and tectonic structures thatexist at depths of hundreds of meters to kilometers (e.g.,
Kopf 2002; Planke et al. 2003; Istadi et al. 2009; Shinya
and Tanaka 2009). Using the controlled source audiofrequency magneto-telluric (CSAMT) method, low resistivity areas indicating mud chambers, located several
hundred meters to kilometers from the surface, havebeen found around the Murono mud volcano (Suzuki etal. 2009). However, since the observed surface deformations in the Murono mud volcano are small, it is more
likely that the slight change of several meters in the surface activity observed for the Murono mud volcano is related to shallower subsurface structure within tens ofmeters in depth. In fact, very shallow low-velocity layers(1 to 5 m deep or deeper than 13 m) were observed by
Onishi et al. (2009).
Although Kusumoto et al. (2014) suggested overpressure changes in fluid mud flow were a direct source ofground surface deformation during the quiescent phase,the details of the subsurface fluid dynamics remain to beclarified by geophysical measurements, and the relationship between fluid mud flow and surface deformation
has not yet been directly revealed. As shown in thispaper, subtle changes in the surface topography indicate
changes in subsurface fluid activity, providing a guideline
for further geophysical analyses. Also, in order to obtaina clearer pattern image of the shift of the central portionof uplift of the mud volcano, it is necessary to carry out
repeated, widespread additional topographic measurements to monitor the activity in the following years.

Conclusions
We performed TLS measurements on the small mud
volcano at Murono, central Japan, revealing the spatial
variations of its vertical displacements at the centimeterscale. The detection of such spatially variable small-scalechanges including both central uplift and peripheral subsidence, as well as the mapping of small topographic
features including open cracks, enabled us to discuss thedetailed changes in both seismic and inter-seismic deformations of the ground surface of the mud volcano. We
also quantified the magnitude of the pressure field induced by earthquakes by modeling the pressure required
to produce the cracks observed in the conspicuous,

Page 14 of 16

elliptical uplift area. The cracks suggested the presenceof a local pop-up of subsurface fluid induced by theearthquakes, as well as the weakening of surface materials by repeated uplift. The uplift pattern in the quiescent period was found to be similar during periods I–III
but changed after the 2014 Nagano-ken Kamishiro Fault
Earthquake, suggesting changes in subsurface fluid
dynamics after that earthquake. Further topographic
measurements, as well as other geophysical data, are expected to provide a better understanding of the localscale subsurface mechanisms of the mud volcano. In
particular, although the modeled uplift and fracture formation were limited to a small conspicuous area
(20 m × 15 m), more widespread modeling efforts that
include the surrounding subsidence area will further
clarify the mechanisms of the mud volcano activity, forwhich expanding the target area of measurement would
be necessary. Increased frequency of topographic measurements, particularly after a strong earthquake, would
also be helpful in revealing detailed temporal changes in
the mud volcano.
Abbreviations
a.s.l.: Above sea level; ALS: Airborne laser scanning; CSAMT: Controlled source
audio-frequency magneto-telluric; DEM: Digital elevation model; DTM: Digitalterrain model; GIS: Geographic information system; GNSS: Global navigation
satellite system; ICP: Iterative closest point; InSAR: Interferometric synthetic
aperture radar; TIN: Triangular irregular network; TLS: Terrestrial laser
scanning; UTM: Universal Transverse Mercator
Acknowledgements
We thank the editor and the two anonymous reviewers for their critical but
constructive comments, which greatly improved the manuscript. We would
like to thank Editage (https://www.editage.jp) and FORTE (https://www.fortescience.co.jp/) for English language editing. This work is supported by JSPS
KAKENHI Grant Number JP25702014 and is a part of the joint research of
CSIS, The University of Tokyo.
Funding
Not applicable
Availability of data and materials
The data used in this paper are available for research purposes at JoRAS(Joint Research Assist System): https://joras.csis.u-tokyo.ac.jp/dataset/show/id/
15003201000.
Authors’ contributions
YSH performed the TLS measurements in the field and analyzed the data, as
well as drafting this manuscript. SK carried out numerical modeling, drafted
the manuscript, and obtained permission for the field survey. NM planned
the initial field measurements and discussed the results we obtained. All
authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Center for Spatial Information Science, The University of Tokyo, 5-1-5
Kashiwanoha, Kashiwa, Chiba 277-8568, Japan. 2Graduate School of Scienceand Engineering for Research, University of Toyama, 3190 Gofuku, Toyama
City, Toyama 930-8555, Japan. 3Graduate School of Education, Okayama
University, 3-1-1 Tsushimanaka, Okayama City, Okayama 700-8530, Japan.

Hayakawa et al. Progress in Earth and Planetary Science (2017) 4:3

Received: 31 May 2016 Accepted: 23 December 2016

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