august 25, 2005
DESCRIPTION
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 PresentationTRANSCRIPT
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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
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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
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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
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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
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Research Area: Shihmen Reservoir
Research Area: Shihmen ReservoirIntroductionIntroduction
SPOT image flight path (CSRSR)
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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
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Shihmen ReservoirShihmen ReservoirIntroductionIntroduction
DEM
slope
forest typeSoil map
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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
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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
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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
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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
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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
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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
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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
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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
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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)
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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
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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
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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
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Comparison with Existing Landslides in GIS databasealso with Cadastral Informations
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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.
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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.
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Thanks for your attention