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
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