10th Asian Regional Conference of IAEG (2015)

Contributions of the Remote Sensing by Earth Observation Satellites
on Engineering Geology
Takeo TADONO(1), Hiroto NAGAI(1), Atsuko NONOMURA(2)and Ryoichi FURUTA(3)(1) Japan Aerospace Exploration Agency (JAXA), Japan
E-mail:tadono.takeo@jaxa.jp(3) Kagawa University, Japan, (3) Remote Sensing Technology Center, Japan
Abstract
Many natural disasters including landslides are depending on terrain conditions i.e.
topography, land-cover, land-use, soil composition, which are a kind of geospatial
information and some of them can be observed by earth observation satellites. In addition,
surface deformations may also be able to measure by satellites applying some processingtechniques. This study is described some usage examples to derive geospatial information
related to geology from satellite data, which is discussed how to contribute the satellite
remote sensing techniques for prevention and response to natural disasters.
The Japan Aerospace Exploration Agency is developing and operating earth
observation satellites. The Advanced Land Observing Satellite (ALOS, nicknamed“Daichi”) and ALOS-2 satellites are major contributors for monitoring land regions basedon their characteristics. The former was launched in 2006, and unfortunately completed themission life on May, 2011 that is after the 2011 off the Pacific coast of Tohoku Earthquake.
The later was launched on May, 2014, and is currently operating very well. In this paper,
some application examples will be showed using data acquired by ALOS and ALOS-2.
Keywords: remote sensing, ALOS, ALOS-2, geospatial information
1.

Introduction“Daichi-2” (ALOS-2) has been launched on May
24, 2014, and is now operating very well. ALOS-2
carries on an L-band Synthetic Aperture Radar(PALSAR-2) and be able to obtain precise surface
information in not only daytime but also nighttime
even under bad weather conditions (Shimada, 2013).
An advantage of PALSAR-2 is gives us subsidence
information by interferometry due to use its longer
wavelength of microwave as L-band. JAXA isconducted the emergency observations for assessing
damaged areas when natural disasters are happened.
An example of actual landslides monitoring occurredby the earthquake in Nepal 2015 is shown.

Many natural geohazards including landslide are
depend on terrain conditions i.e. topography,
land-cover, land-use, which are a kind of geospatial
information and some of them can be observed byearth observation satellites. This study is described
how to contribute the satellite remote sensing
techniques for prevention and response to suchnatural disasters, and show practical usage examples.
Topography is fundamental information for any
geospatial applications including geology. The Japan
Aerospace Exploration Agency (JAXA) is providing
the precise global digital 3D map called “ALOS
World 3D” (AW3D) that is processed using some 3
million images acquired by the Panchromatic Remotesensing Instrument for Stereo Mapping (PRISM)
onboard the Advanced Land Observing Satellite“Daichi” (ALOS) (Tadono et al., 2014). The digital
3D map consists of a 5 m mesh digital surface model(DSM), and a 2.5 m resolution of ortho-rectified
images (ORI), which enables us to express landterrain over the world. It can contribute to makehazard map in prevention phase as well.

2.

ALOS and ALOS-2

ALOS was launched on Jan. 24, 2006, and has
operated very well over the mission target life of fiveyears (Shimada et al., 2010). However, its operation
was official termination on May 12, 2011 due to apower generation anomaly. Notwithstanding, approx.
6.5 million-scenes of archived data by three
instruments covering the entire globe are available tousers. Fig. 1 shows an overview of ALOS, which1

10th Asian Regional Conference of IAEG (2015)

Fig. 1 Overview of “Daichi” (ALOS).
curried on two optical instruments called PRISM andAVNIR-2, and an L-band synthetic aperture radar
called PALSAR. PRISM image has a 2.5 m spatial
resolution with a 35 km swath width in triplet mode.
It performs along-track triplet stereo observation togenerate precise DSM. AVNIR-2 stands for theAdvanced Visible and Near-infrared Radiometertype-2, which has four radiometric bands of a 10 mresolution. A color image with a 2.5 m resolution canbe created using images of PRISM and AVNIR-2 as apan-sharpened image.
ALOS-2/PALSAR-2 is followed on mission ofthe ALOS/PALSAR with some improved functions.
PALSAR-2 can provide 1-3-m high-resolution
Spotlight and Strip map with multiple polarizations
with an imaging swath of 25/50/70 km, ScanSAR
with dual polarizations with a 350/490 km swath, ashorter temporal baseline of 14 days and spatial
baseline of within 1 km, emergency observation
service within a 12-h delay for any global target andespecially within a 72-h (74 h in the worst case) delay
as synchronized observation with the archives, i.e.
same off-nadir and observation mode, and ScanSAR
interferometry with more than 90% global beam
synchronization. Such function will be suitable anatural disaster monitoring and mitigation. Fig. 2
shows an overview of ALOS-2 in orbit.
3.

Fig. 2 Overview of “Daichi-2” (ALOS-2).

Fig. 3 Processing status and next released plan of
AW3D dataset tiles as of April 2015.
complete the global dataset by March 2016. Fig. 3
shows the AW3D dataset processing status as well as
next released plan as of April 2015. Approximately
11,000 tiles of the dataset out of 22,000 tiles havebeen completed as of April 2015, which iscorresponding to 60% in aerial fraction coverage ofthe global terrestrial regions. Priority of the dataprocessing areas is determined based on the userneeds and requirements. Therefore, North America,Greenland, and Antarctica have relatively lower
processing priorities, and are processing soon. Evenavailable PRISM archived data are used in AW3D asmuch as possible, the masks due to clouds are still
remaining in the first version of the dataset.
Fig. 4 shows an example of DSM/DEM image
comparison between (a) AW3D DSM in 5 m meshand (b) version 2 of the Shuttle Radar Topography
Mission (SRTM) in 90 m mesh as existing global
DEM in Tokyo, Japan. The color assignments of bothDSM/DEM are same, therefore they are clearly
seeing that AW3D DSM can identify more detail
textures and large buildings.
The aim of AW3D dataset generation is toprovide the global digital elevation data with precise
accuracy, therefore validations for widespread areas
are important. Two validation procedures are applied
operationally; (a) comparison between AW3D DSM
and existing global DEM i.e. SRTM version 3 (v.3) to
identify systematic errors and masks status inwidespread areas as a relative validation, and (b)evaluation using ground-based check points (CPs) as

Global Digital 3D Map by PRISM

PRISM global 3D map dataset processed inAW3D project consists of the precise DSM in 1degree tiles of lat/long frame units, and ORI ofnadir-looking image of PRISM in scene bases. The
precise DSM has 0.15 arcsec (approx. 5 m) horizontal
spacing with 5 m height accuracy (root mean squareerror, RMSE) as the target accuracy. This is achievedby stacking and mosaicking processing using
multi-temporal acquired scenes of DSM. The ORI has0.075 arcsec horizontal spacing, which corresponds toapprox. 2.5 m original resolution. The correlation
coefficient image (CCI) is an intermediate product of
the image matching processing in DSM generation. Asummary of CCI is given in the quality assessment
information (QAI) that is attached in the product. An
overview and technical challenging were summarized
by Tadono et al. (2014) and Takaku et al. (2014).
The AW3D dataset was released from March2014 in commercial bases, and is scheduled to be2

10th Asian Regional Conference of IAEG (2015)

Fig. 5 Histogram of height error evaluated by4,622 CPs in 103 tiles (red: AW3D DSM, andgreen: SRTM version 3 as a reference).

(a) AW3D DSM (5 m mesh).

Table 1 Validation results by 4,622 CPs.
DatasetAW3DRef) SRTM v.3

Ave. (m)
-1.51
-1.11

STDEV (m)
3.81
6.13

RMSE (m)4.10
6.23*Ave.: average, STDEV: standard deviation, Ref: reference

just a reference. It was confirmed 3.81 m (standarddeviation, STDEV) and 4.10 m (RMSE) of height
accuracy for AW3D DSM, which was gained thetarget accuracy of 5 m (RMSE). Similar evaluations
will be continued when new tiles are available.
An example of practical usage of AW3D ingeology, Fig. 6 shows the landslide volume
estimation in Koslanda, Sri Lanka, which wasoccurred on October 29, 2014. It affected more than
1,000 peoples (320 families) and over one hundred
were estimated to be missing based on the report. TheJapan International Cooperation Agency (JICA) SriLanka office was conducted the aerial survey on
November 5, 2014, and analyzed terrain height after
the landslide (JICA, 2014). As the results, thelandslide was approx. 100 m in width and 260 m inlength with an average depth of about 15 m, and themass was roughly estimated about 260,000 m3 andhalf remained on the upper slope.
Addition to AW3D DSM 5 m mesh dataset,
JAXA is started to publish a lower resolution version
free of charge for any users, which has a 1 arcsec(approx. 30 m) resolution of AW3D DSM (AW3D30)
dataset that is created based on original 5 m mesh
DSM dataset. Two resampling methods are applied tocalculate AW3D30 i.e. averaging and median
resampling. The nearest neighbor resampling will beadded in next release. Fig. 4 (c) shows an example ofAW3D30 DSM, and can be seen that still remaining
terrain feature details. AW3D30 DSM should have 5m height accuracy as target, and similar validation
will be conducted. The first release of AW3D30 wasoffered East Asia, including Japan, and South East
Asia regions since May 18, 2015, and will expand theareas to all over the world. AW3D30 dataset isexpected to be useful for scientific research,education, as well as for the private service sector thatuses geospatial information (JAXA EORC, 2015).

(b) SRTM version 2 DEM (90 m mesh).

(c) AW3D30 DSM (30 m mesh).
Fig. 4 Comparison among (a) AW3D DSM (5mmesh), (b) SRTM version 2 (90m mesh), and (c)AW3D30 DSM (30m mesh) in Tokyo, Japan.
an absolute validation.
The absolute height validation of AW3D DSM
dataset was conducted using 4,662 CPs distributed in
103 tiles as an initial validation that located in not
only Japan area but also foreign countries. Fig. 5shows the histogram of height error evaluated by4,662 CPs, where red bars are the results for AW3DDSM, and green bars are for SRTM v.3 as justreference. The shapes of histograms look Gaussian
distribution with almost zero peaks, but AW3D’s one
is much sharp than SRTM’s one. Table 1 summarizes
statics of evaluation of AW3D DSM and SRTM as3

10th Asian Regional Conference of IAEG (2015)

Fig. 6 Example of landslide volume estimation in Koslanda, Sri Lanka. This shows slope profiles change
compared AW3D DSM (dash line as before event) and the analyzed by aerial survey (the red line) after theevent (©JICA).

Fig. 7 PALSAR-2 image observed on April 26,
2015 acquired by the emergency observation.
Green lines are identifiable ridges (as markings ofterrain), a red polygon is showed the debris
covered riverbed area, and a pink polygon is theestimated damaged area. The background image isan ALOS pan-sharpened image.

Fig. 9 ALOS pan-sharpened image acquired onOct. 12, 2008. Green lines and a pink polygon aresame with Fig. 7.
4.

Natural Disaster Monitoring by ALOS-2

As an example of emergency observation result
by ALOS-2, the earthquake occurred in Nepal onApril 2015 is summarized.
Corresponding to the emergency requests from“Sentinel Asia” and the “International Charter”
related to the earthquake occurred in Nepal on April
25, 2015, JAXA performed an emergency
observation at 7:02 (GMT) on April 26, 2015 by
PALSAR-2 onboard ALOS-2. Fig. 7 is a close-up
image acquired by the PALSAR-2 Ultra Fine mode (3m resolution, HH polarization). It shows a post-quake
situation around Langtang village, Nepal, which islocated on a famous trekking route in the Nepal
Himalayas. The brightness of the image represents
the signal received by PALSAR-2, which is theamplitude of the backscattering microwave from theground. Comparison between this image and pre-Fig. 8 PALSAR-2 image observed on Dec. 28,
2014 as before the earthquake. Green lines, a pink
polygon, and the background image are same withFig. 7.

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10th Asian Regional Conference of IAEG (2015)

and ALOS-2 introduce the basic observation scenario,
which is acquired the data systematically as
foreground mission operation plan. This is anadvantage JAXA’s land observation mission tocontribute disaster monitoring as well as preventions.
5.

Conclusions

In this paper, contributions of the satellite remotesensing for response and prevention to naturaldisasters, which includes practical examples tomonitor landslides were described.
Topography is a fundamental information not
only geology but also any geospatial applications.
Although PRISM data were acquired from 2006 to2011, derived DSMs has the best height accuracy inthe global digital elevation dataset, therefore AW3D
project have particularly large expectations for manyusers. It can also be used as base map in the disastermonitoring and mitigations. Also, AW3D30 DSM
dataset was introduced that now freely available.
ALOS-2 is now operating that carried on
PALSAR-2 and can be observed not only daytime but
also nighttime even under bad weather conditions. A
practical example to monitor landslide caused by theearthquake in Nepal 2015 was introduced, whichanalyzed only amplitude image. PALSAR-2 has a big
potential to apply the interferometry to measuresubsidence caused by earthquake, volcanic activity as
well as potential dangerous landslides. This will also
contribute to monitor natural disasters.

Fig. 10 Birds-eye view of pan-sharpened image
taken by PRISM and AVNIR-2 on Oct. 12 2008.
Green lines and a pink polygon are same with Fig.
7.
quake image suggests a large displacement ofavalanche and/or landslide covering the river bed. For
comparison, a close-up image acquired before theearthquake, December 28, 2014, is shown in Fig. 8. A
great change can be identified on the surface. Fig. 9 isa pan-sharpened image obtained by ALOS PRISM
and AVNIR-2 on October 12, 2008 as a reference.
The bright points and a valley-shaped feature denoted
in Fig. 8 correspond to buildings and water flow,respectively. Damaged area is estimated to be thepink polygon because of their disappearances.
Fig. 10 shows birds-eye views around thedamaged area from two angles, in which the ALOS
pan-sharpened image is overlaid on PRISM DSM.
The damaged area is located on the bottom of aU-shaped valley, above which several glaciers aredistributed. A large displacement induced by theearthquake is implied here.
An emergency observation with ALOS-2
estimated that the damaged area affected by adisplacement in Langtang village ranges approx.
1,500 m in width and 700 m in length as shown in Fig.
7. These results have been reported to the concerned
authorities immediately to support their rescue andrecover activities. JAXA will continue theobservation in Nepal in cooperation with them.
As seen from the above example, the images
acquired both pre- and post-event are most importantto response natural disasters because change detection
is a fundamental approach. Therefore, both ALOSAcknowledgements
The authors thank our collaborators from NTT
DATA Corp. and RESTEC for participating in the
ALOS Global Digital 3D Map project, in particular,
we are grateful to Mr. J. Takaku for technicalsupports and Dr. K. Tsutsui for management efforts.
References
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Landslide (2nd Report), Japan International
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10th Asian Regional Conference of IAEG (2015)

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