August 25, 2005

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Identification of Landslides with combined RS and GIS data. Kuo-Hsin Hsiao, Jin-King Liu , Ming-Fong Yu. Speaker : Kuo-Hsin Hsiao. August 25, 2005. Identification of Landslides with combined RS and GIS data. List of Contents. 1. Introduction 2. Landslide Detection - PowerPoint PPT Presentation

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August 25, 2005

Kuo-Hsin Hsiao, Jin-King Liu, Ming-Fong Yu

Speaker : Kuo-Hsin Hsiao

Identification of Landslides with combined RS and GIS data

Identification of Landslides with combined RS and GIS data

1. Introduction

2. Landslide Detection

3. Results of landslide interpretation

4. Concluding Remarks

List of Contents

1. Introduction ◆ Geologic and terrain characteristics in TAIWAN

◆ Climate condition – typhoon, torrential rainfall

◆ R.S. data – spatial、 temporal resolution resolution, data acquisition, time required for interpretation, combined information of GIS, etc.

Highly fractured rock formations

Variations of Geologic Conditions: A section across Taiwan

Lithology-conglomerates

Requirement of A Monitoring and Early Warning System• Both for Emergency Response and for Mitigation Policy

• Landslide Detection Using Satellite Images– High Frequency Periodic Observation and Measurem

ents : Month~Year– Data : SPOT-5 or Formosat-2

.

.

Objectives of the study:• Periodic landslide Monitoring for Sustainable Managem

ent using high resolution data (for detecting small landslides)

• Prevention of Illegal Land Use and Deterioration• Disaster Damage Estimation

Background

Orbit of FORMOSAT-2Orbit of FORMOSAT-2

Sun-Synchronous OrbitAltitude = 891 km; Inclination = 99.10 deg; Period = 14 Rev/day

IntroductionIntroduction

Research Area: Shihmen Reservoir

Research Area: Shihmen ReservoirIntroductionIntroduction

SPOT image flight path (CSRSR)

Shihmen ReservoirShihmen Reservoir

• Purpose of the Reservoir

– General water supply

– Irrigation

– High-tech industry

• Watershed Area:764 KM2

• Capacity: 2.5 x 108 M3

• Terrain Variation : 252M~3,500 M

• Average Rain Fall : 2,500 mm/yr

• Land-Use Type

– Coniferous Tree, Deciduous Tree

– Orchard, Rice, Village, Farming, Foresting

– Bare Soil, River, Mixed-Forest, Bamboo, Grass Land

– Mixed Coniferous-Deciduous Tree, Others.

Land-Use CoverageLand-Use Coverage

IntroductionIntroduction

Shihmen ReservoirShihmen ReservoirIntroductionIntroduction

DEM

slope

forest typeSoil map

Disaster – Typhoon AEREDisaster – Typhoon AERE

• Duration :

– Aug. 23 ~ Aug. 25, 2004

• Maximum total accumulative rain fall -1,600 mm

• Maximum rain fall

– 146 mm / hr

Contour of Total Accumulative Rain Fall

2004-08-24-09:23 2004-08-25-09:23

IntroductionIntroduction

CWB

Water Quality after TyphoonWater Quality after TyphoonIntroductionIntroduction

2004/8/26 FORMOSAT-22004/8/26 FORMOSAT-2

Satellite IR Typhoon Road of AERE

High turbidity

Satellite Radar

NSPO

NSPO

CWB

2. Landslides Detection

SPOT-5 2004/08/16Resolution: 10m

SPOT5 2005/03/16Resolution: 2.5m & 10m

Formosa-II 2005/04/04Resolution: 2m & 8m

Data AcquisitionData Acquisition

Disaster Estimation & Analysis ProcessesDisaster Estimation & Analysis Processes

Disaster Estimation

Disaster Areas

DTM + Image(3D Visualization)

Overlay Analysis

Day-1 Image Day-2 Image

NDVI/CVA NDVI/CVA

Change Detection

Landslide Coverage

Change ?YES

NOStop

On-Site Photography

Landslides Detection

Classification

overlay

Various Types of Landcover and LandusesVarious Types of Landcover and LandusesLandslides Detection

(a)River-bank landslides (b)Slope landslides (c)Upstream landslides (d) snow on tops

(e)Grass lands (f)Excavated lands (g)Cultivated lands (h)Mountain village

(i)Plain villages (j) Cemetery (k)Roads (l)Rivers

SPOT-5 data acquisition(before & after AERE)

LandslidesSpatial

resolutionTotal No. Area (ha)

Before typhoon (2004/08/16)

215 225.85 10m*10m

Afetr typhoon (2005/03/16) 379 629.25 10m*10m

3. Results of landslide interpretation

ResultsLandslide interpreted from SPOT5 10m & 2.5m

Acquisition dateLandslide

Spatial resolutionTotal No. Area (ha)

SPOT5(2005/03/16)379 629.25 10m*10m

477 693.33 2.5m*2.5m

Spatial resolution : 10m Spatial resolution : 2.5m

ResultsLandslide interpreted from formosat2 8m & 2m

Acquisition dateLandslide

Spatial resolutionTotal No. Area (ha)

Formosat-2(2005/04/04)424 689.56 8m*8m

473 723.74 2m*2m

Spatial resolution : 8m Spatial resolution : 2m

Statistical analysisResults

Total No. and area of landslide interpretation

0

100

200

300

400

500

600

700

800

total No. Area (ha)

SPOT-5(2004/08/06,10m)

SPOT-5(2005/03/16,10m)

SPOT-5(2005/03/16, 2.5m)

formosat-2(2005/04/04,8m)

formosat-2(2005/04/04,2m)

3D Visualization of Detected Landslides3D Visualization of Detected Landslides

Red regions denote the detected landslides of Formosat-2 test data.

Landslide induced by typhoon AERELandslide induced by typhoon AERE

Results

SPOT-5(2004/08/16) SPOT-5(2005/03/16)

On-Site Photography

SPOT-5(2004/08/16)

SPOT-5(2005/03/16) On-Site Photograp

hy

CSRSR

CSRSRCSRSR

SPOT-5(2004/08/16) SPOT-5(2005/03/16)

On-Site Photography

SPOT-5(2004/08/16) SPOT-5(2005/03/16)

Helicopter Photography

Landslide induced by typhoon AERELandslide induced by typhoon AEREResults

CSRSR

CSRSR

Formosat-2 imageFormosat-2 imageSPOT image

Flight Simulation after NERE Typhoon Flight Simulation after NERE Typhoon

2004/8/31 (NSPO)2004/8/31 (NSPO)After typhoon NEREAfter typhoon NERE

2003/11/14 2003/11/14 Before typhoon NEREBefore typhoon NERE

Comparison with Existing Landslides in GIS databasealso with Cadastral Informations

ConclusionsConclusions• Requirements of A Monitoring and Early Warning System

– Bottleneck--Data Acquisition• High frequency data acquisition of remote sensing.

• Near Real-time Dynamic Monitoring…

• Typhoon AERE– Statistics

• 477 & 473 places, total areas of 693.33 & 723.74 hectares of landslides were detected using SPOT-5 and Formosat-2 fusion data

• The reliability of landslide detection is high when comparing with on-site photography.

ConclusionsConclusions

– With Formosat-2, A Possibility of Near real-time disaster estimation

• Provide disaster information in a short time.

• Historical data collection is important. A comparison can be made by GIS database.

• Construction of GIS database infrastructure is critical for post-disaster analysis.

Thanks for your attention