3 Dimensional Measurement by
Satellite Remote Sensing for Disaster Monitoring
Takahiro NAKAGAWA*, Masashi HYODO** and Masataka TAKAGI***
Department of Infrastru ture Systems Engineering
Ko hi University of Te hnology
Tosayamada, Ko hi, Japan*E-mail:115114ygs.ko hi-te h.a .jp***E-mail: takagi.masatakako hi-te h.a .jp

Summary : SHIKOKU Island in Japan has many slope failure disasters by the torrential rain every

year. The slope failures indu e other serious disaster su h as landslide, mud ow and debris ow.
Therefore, hidden slope failure must be found immediately. PRISM sensor mounted on ALOS has
three lines s anner with 2.5m ground resolution and it an be observed at the same time from sameorbit. Then, three dimensional (3D) measurements an be arried out in 2.5m spatial resolution. The
3D measurement using PRISM has a potential to dete t slope failure. In the present resear h work,a ura y veri ation of 3D measurement using PRISM was arried out and the possibility of wide
area monitoring of slope failure disaster was on luded. Result showed about 1 pixel error in z axis.
Then, at least 5m width of slope failure might be expe ted to dete t by PRISM using 3D perspe tive
proje tion.
Keywords : 3D Measurement, Slope Failure, Disaster Monitoringslope displa ement using multi temporal DSM data.
The goal of this resear h is generating a urate
Mud ow enormous foundation disaster had o DSM data and dete ting slope failure in using
urred by slope failure. It is ne essary to get
temporal DSM.
a s ent of slope failure before it o urred to reFollowing are resear h items to a hieve the goal.
du e the mud ow damage. It was diÆ ult to de Establishment of Ground ontrol point(GCP)te t slope failure in remote region of the ountry;
database using VRS measurement
for the reason, wide area monitoring te hnique
1

INTRODUCTION

by satellite images is expe ted. ALOS satellite
mounted PRISM sensor that has three lines s anner(Forward, Nadir, Ba kward) with 2.5 meters
ground resolution and it an be observed at thesame time from same orbit. In general known,
stereo image an be generated 3D data(DSM: Digital Surfa e model). Therefore, it is possible togenerate DSM by PRISM data and to extra t

Establishment of geometri model for PRISM

Generate DSM data for wide area from PRISM

A ura y evaluation of PRISM s DSM data

GEstablishment of hange dete tion method
using multi temporal DSM data
it would be developed to dete t mass movementValidate the hange dete tion

3D measurement of PRISM data will have a potential to dete t slope failure with the s ale of
25m2 in spatial distribution. In this paper, a system of DSM generation and a ura y of DSM will
be evaluated.
2

dangerous geologi al region of landslide be auseof fra ture by geologi al te toni line.

METHODOLOGY

To make DSM Data, Geometri Transformation
Model between image oordinate and ground oordinate must be de ided. Usually, RPC model
was used for 3D measurement[1℄[2℄. But to get
Figure 3.1 Test Areahigh a ura y, geometri orre tion by GCP datais needed[3℄ On the other hand, 3D perspe tive
In this study, Nadir and Ba kward images wereproje tion an be applied for geometri transformused. Forward image taken a pi ture from themodel. At least 11 GCPs are required to estabNorth and image pro essing was diÆ ult be auselish this model. Therefore, it is ne essary to esof Sunlight re e tion. Therefore, Forward image
tablish GCP data set in the test eld. GCPs weredoesn't use in this study. Figure3.2 shows PRISM
observed using GPS-VRS observation. Over 30
images of Nadir and Ba kward. Table 3.1 showed
points GCPs should be prepared in ea h test eld.
meta data of PRISM image.
Next orresponden e points between Nadir andBa kward image are requested for stereo mat hing.
At last 3D measurements was a hieved by obtained orresponden e points substituted for transformation model. The least square method wasapplied for al ulating 3D oordinates in this study.
Generated DSM was evaluated using validation
Figure 3.2
PRISM Images(Nadir, Ba kward)
points.

%3

USING DATAS

3.2

DEM Data

When 3D measurement, digital elevation model of50 mesh data in SHIKOKU Island was used to get
Test eld was sele ted around CHOJA in SHIKOKU
initial ondition for stereo mat hing in this study.
Island, JAPAN. Figure3.1 depi t geologi al mapin Shikoku. Red area and yellow area showed a3.1

PRISM image dataHITable 3.1

itemmeta data of PRISM imagesspe

Pro ess level
level 1B2Area
CHOJA in KOCHI
Width35km * 35km
DateApril in 2007
Ground resolution
2.5m

3.3

Ground Control Points

4

ACCURACY VERIFICATION
OF TRANSFORM MODEL

In this study 3D perspe tive proje tion was sele ted for geometri transform model. This equation is based on area sensor geometry. Groundoordinate(x,y,z) an be transformed to image ofPRISM oordinate(u,v).
a1 ; a2 ;    ; a11 are unknown parameters

8><>:%a x + a2 y + a3 z + a4u= 1Figure 3.3 showed distribution of GCP and validaa9 x + a10 y + a11 z + 1(4.1)
tion points. 45 points were observed using GPSa5 x + a6 y + a7 z + a8v=a9 x + a10 y + a11 z + 1
VRS observation. GPS-VRS observation an measure very a urately with a few entimeter. GCPs Be ause of PRISM is line sensor, 3D perspe tive
were observed at interse tions of road and the en- proje tion does not presented a urate model. Howter of bridges.
ever, using 3D perspe tive proje tion will makesatisfa tory result for geometri orre tion of highresolution satellite images. Unknown oeÆ ientswere al ulated from 24 GCPs data by least square
method.
Error was de ned in terms of di eren e between
image oordinates obtained by the al ulation andimage oordinates visually interpretation from satellite image. Table 4.1 showed residual error aroundvalidation points.

Table 4.1 Residual Error of 3D Proje tion Modelaround Validation Point (Unit: Meter)

ImageColumn Row
Nadir
2.043 1.886
Ba kward 1.683 1.912
Figure 3.3

Lo ation of GPS VRS Observation

A ura y showed within 2.5m around validaIn this study, 24 points were used as GCP and
21 points were used as validation points. Ob- tion point. This numeri number was proper forserved GCPs on satellite image were sele ted by about 1 pixel in PRISM image.
visual interpretation. An a ura y of visual interpretation showed within 1 pixel.

5IMAGE MATCHING

63D MEASUREMENT

Automated extra tion of orresponden e point from When the olumn(u) and row(v) of the orresponthe stereo images by the image mat hing must den e point in stereo pair image are input, unbe established. Least squares mat hing is power- known values are ground oordinates (X, Y, Z).
ful method for image mat hing. However, initial The number of equations is two in ea h image.
oordinates must be given. Then, determination Then the total number of equations be ome four
method of initial oordinates must be developed. in the ase of stereo imagery. Therefore, three
To a quire an initial ondition of the least squares unknown values (X, Y, Z) an be solved by least
mat hing, PRISM images were onverted into groundsquare method.
oordinates by geometri model. This image isalled ortho image(Figure 5.1). To generate ortho
image, DEM of 50 mesh data in SHIKOKU Island
was used. When Nadir and Ba kward images wereonverted into the same oordinate system, it anbe expe ted to image mat hing be omes easy.

Figure 6.1

7GeometrimodelACCURACY EVALUATION
OF 3D MEAUREMENT

Figure 5.1

Ortho image Nadir and Ba kward

82,000 of orresponden e points was obtained among
Same oordinates of two ortho images trans- 90,000 points as a result of the image mat hing,form original image oordinate by transform model and 3D oordinates were al ulated. Cal ulated
and this value is used as initial ondition of least 3D oordinate was onverted digital surfa e model(Figuresquares mat hing. Then orresponden e points 7.1). 3D data ompared with GPS data of valibetween original Nadir image and Ba kward im- dation point for a ura y evaluation. Error wasage were extra ted. Be ause of satellite image de ned in terms of di eren e between Z valuessize, it takes mu h time to make DSM data in of validation point and al ulated one. Table 4.1
whole area. Therefore in this study, image mat h- showed residual error around validation points ining was arried out range of 1500m * 1500m (300pixelZ value. Maximum error showed 3.5 m and RMSE
* 300pixel).
showed 2.4 m a ura y that was very small rangeof error. Figure 7.2 and 7.3 showed lo ation ofvalidation points on Nadir image of PRISM.

Figure 7.1 Bird's Eye View of Generated Digital Surfa e Model

Table 7.1 Residual Error of 3D Measurement (Unit:Meter)

Point No. Z(GPS) Z(PRISM) Error
1
297.956299.493 -1.536
2291.025
291.398 -0.373
3290.097
287.595 2.502
4
327.953
324.479 3.474
5325.426
323.690 1.736
6
312.236309.774 2.462
7306.098
307.069 -0.971
8309.322
312.575 -3.253
9309.049311.938 -2.889
10315.088
311.910 3.178
11319.438
317.350 2.088
12324.520
322.466 2.054
13289.559
291.716 -2.157
14317.969
315.710 2.259
RMSE 2.364

Figure7.2 Lo ationofValidation

Point(VP)on

Nadir Image of PRISM

Figure 7.3 Lo ation of VP on shaded relief map byWhen satellite image ompared with 3D data, DSM data
there were some noises in pla e of low ontrast
area su h as forest or at area. As for su h a area, 8 DISCUSSION AND CONCLUthe possibility of the mat hing error will be high.
SIONS
Therefore a ura y of validation points thanks in
In this study the a ura y of 3D measurement
part to advantaged pla e of high ontrast area.
an get within 2.5m was predi ted. This a ura yis almost PRISM s ground resolution a ura y.
However, the following problems were remaining.
Image mat hing takes too mu h time. So it is ne -Gessary to make transa tion speed fast in a future
study.
Su h forest and at area where low ontrast of theimage, espe ially attribute noise was generated tomiss mat hing. Be ause of validation point wasobserved by GPS observation, it was not possible to observe in the forest where the signal of
the GPS satellite was not aught easily. If missmat hing de rease in low ontrast area, A urate
DSM an be expe ted for disaster monitoring.

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