Establishment of monitoring and hazard level …earth.esa.int/workshops/ALOS2008/participants/152/pres_152_Furuta.pdf · Establishment of monitoring and hazard level assessment system

ALOS PI Symposium 2008, Rhodes, Greece. 3-7 November 2008

Establishment of monitoring and hazard level assessment system for landslide disasters by ALOS, and its application

Ryoichi Furuta(1), Atsushi Yashima(2), Kazuhide Sawada(2), and Hiroshi Fukuoka(3)

(1) Remote Sensing Technology Center of Japan, 1-9-9 Roppongi, Minatoku, 106-0032 Tokyo, Japan

(2) Gifu University, 1-1 Yanagido, 501-1193 Gifu, Japan(3) Kyoto University, Gokasho, Uji, 611-0011 Kyoto, Japan


Research Objective

• Prototype landslide monitoring and assessment system proposed by the authors in 2003.– GIS, Analysis tools for estimation of landslide stability.– Existing information (DEM, Vector Map, etc.) was used.– Latest information (topography, land-cover, etc.) is necessary.

• To improve a landslide monitoring and assessment system, we apply the ALOS data.– DSM generation tool– Collapse-type landslide recognition tool

• To understand capability of PALSAR DInSAR to monitor very slow landslide movement on the steep slope.– Application to Zentoku landslide


Outline

• Improvement of “Landslide Monitoring and Assessment System”

• Analytical result of DInSAR of Zentoku Landslide.

• Conclusions


Improvement of a prototype system of “Landslide Monitoring and Assessment System”

• GIS based information system– Attribution Analysis Tool based on statistics– Landslide hazard level estimation tool based on

photogrammetric analysis and numerical analysis

• Tools for ALOS data utilization– Image reconstruction (L1B1 to Geocorded image)– Pan-sharpen image generation (modified HSI)– DSM generation– Collapse-type landslide recognition (based on face recognition

technique)


DEM&

Vector Map

ImageProcessingTool

DSMGeneratingTool

LandslideRecognitionTool

DInSARProcessor

Creep-type

Collapse-type AttributionAnalysisTool

Landslide

LandslideSimulationTool

PhotogrammetricAnalysisTool

LandslideSimulationTool

LandslideSimulationTool Very simple model

Numerical model

Numerical model

GIS

All of information is puttogether on the GIS platform


About DSM Generation Tool

• DSM generation tool– DSM is generated from a pair of PRISM image.

• Backward view – Nadir view• Forward view – Nadir view• Backward view – Forward view

– Generate DSM with several pixel spacing.• 2.5m ~ 90m

– Including filtering and interpolating function.• Noise (Residue) cut• IDW method for interpolation

– Accuracy of generated DSM (20m pixel spacing)• Approx. 12m for elevation (validated by 50m res. DEM)• Approx. 6m for horizontal direction (validated by 1:2500 vector

map)– Application

• Landslide stability, simulation, mapping, etc…


Processing flow of DSM Generation Tool

PRISM L1B1(Nadir)

PRISM L1B1(Oblique)

Image reconstruction&

Convert to UTM projection

Resolution selection

Conjugate point search

Convert to height

Filtering & interpolating

Output DSM

Bird’s eye view of generated DSMSSDA

©JAXA analyzed by RESTEC


Bird’s eye view of generated DSM of Gifu area

©JAXA, Analyzed by RESTEC


Development of Collapse-type Landslide Recognition Tool

• Point of view– The collapsed pattern of collapse-type landslide shows very similar

pattern.

• Method– Application of face recognition technique.

• Technique to recognize human face from image or video

– Collapse-type landslide areas are recognized by template of landslide pattern.

• Problem– Similar pattern like mine site, agriculture area, cloud area, etc. was

detected.

• Solution– Apply the masked image created by NDVI value to masked out error

area.


Processing flow of Collapse-type Landslide Recognition Tool

Template


Search similar area

ALOS/Optical image(product level 1B1)

Image re-construction

Filtering (masking)

Recognition result

0 45

90

135180225

270

315 0 45

90

135180225

270

315

Segmentation of input image by NDVI

We change the size of this template to recognize several scale of landslide


Result (fine)


Result of Collapse-type Landslide Recognition


Result (error by paddy fields)




Result (error by clouds)




Before After

Masked by segmentation image derived from NDVI value



DInSAR analysis for steep slope

• Aim– To understand capability

of DInSAR at steep slope

• Overview of test site– Zentoku landslide is one of

the active landslide in Japan.

– Average of slope angle: 28 deg. (Steep slope)

– Size of landslide; width 2000m, length 900m

NN

Image from:http://www.yamato.kkr.mlit.go.jp/YKNET/outline/landslide/landslide/work/moc/zentoku/zentoku01.html

Tokushima Pref.

500m


Relationship of analyzed data and monthly precipitation

0

100

200

300

400

500

1 2 3 4 5 6 7 8 9 10 11 12 13Month

Pre

cipi

tatio

n(m

m)

200620072008

10130828

0718

0716 10160831

2006

20072008

Ikeda station




Time series of DInSAR Result10130828

0718

0716 10160831

2006

20072008

(a)

(b) (c) (d)

(e)

(a) (b) (c)

(d) (e) (f)

All of image ©METI, JAXA analyzed by RESTEC

(f)

N

Az

Rg

-π +π


Simulation of landslide movement by very simple model

DInSAR result

Simulated result

Simulated image was analyzed by very simple model.

Liner model

yCLy

avedisavey

dWdd

dWdd

⋅−=

⋅−=

dave: Annual deformation / temporal base-lineWdis: Weighting by distance from the bottom of landslide.WCL: Weighting by distance from the center of landslide of each elevation.

-π +π


Conclusions

• We developed ALOS data processing tools to improve our prototype landslide monitoring and assessment system.

• Capability of developed tools are confirmed.– Approx. 12m accuracy for elevation. (DSM Generating Tool)– Good result and errors can be reduced by mask image of NDVI.

(Collapse-type Landslide Recognition Tool)

• DInSAR analysis for steep slope is complicated.– It is difficult to identify the movement area from DInSAR result.– Not so negative.– Proposed simulation model needs improvement.

• We should improve our tools to increase the accuracy of each result for operational use.

Documents

Establishment of monitoring and hazard level …earth.esa.int/workshops/ALOS2008/participants/152/pres_152_Furuta.pdf · Establishment of monitoring and hazard level assessment system