10606-landslides-monitoring-zp-etal.pdf

LANDSLIDE IDENTIFICATION, MOVEMENT MONITORING
AND RISK ASSESSMENT OVER RUGGED MOUNTAIN
AREA USING ADVANCED EARTH OBSERVATION
TECHNIQUES
Project ID: 10606

10606
Monitoring landslides
movement over over rugged
mountain area area integrated
with with multiband SAR SAR and and
LIDAR
Joined proposals
+
10698
Spatio-temporal landslide
identification and and activity
assessment for for hazard
and and risk risk investigations in in
Longnan region,
Northwest China

Institutions:
1.
2.
3.
4.
5.
6.
7.
Team composition
Bai Shibiao Thomas Glade
Liu Guang Zbigniew Perski
Department of Geography and Regional Research
Institute of Geomatics and Analysis of Risk (IGAR)
Polish Geological Institute –National Research Institute ‐Carpathian Branch
Center for Earth Observation and Digital Earth, Chinese Academy of Sciences
Key Laboratory of Virtual Geographic Environment (Nanjing Normal University),
Department of Geomatics, School of Land Science and Technology, China University
China Aero Geophysical Survey & RS Center for Land and Resources

Team composition (2)
• Prof. Michel Jaboyedoff, Institute of Geomatics and Analysis of Risk (IGAR), Switzerland
• Prof. WANG Jian, Key Laboratory of Virtual Geographic Environments, China
• Prof. LV Guonian, Key Laboratory of Virtual Geographic Environments, China
• Prof. HUANG Jiazhu, Key Laboratory of Virtual Geographic Environments, China
• Dr. FAN Jinhui, China Aero Geophysical Survey and RS Center for Land and Resources, China
• Dr. Maria Papathoma‐Koehle, Department of Geography and Regional Research, Austria
• Dr. KANG Zhizhong, Department of Geomatics School of Land Science and Technology, China
University, China
• Dr. Rainer Bell, Department of Geography and Regional Research, Austria
• Dr. YANG Lin, Key Laboratory of Virtual Geographic Environments, China
• Dr. Tomasz Wojciechowski, Polish Geological Institute, National Research Institute ‐
Carpathian Branch, Poland
• Dr. Clement Michoud, Institute of Geomatics and Analysis of Risk (IGAR), Switzerland
• Dr. Marc‐Henri Derron, Institute of Geomatics and Analysis of Risk (IGAR), Switzerland
• Dr. Benni Thiebes, Key Laboratory of Virtual Geographic Environments, National Education
Administration, China
• Young scientists from China and Europe

Objectives
• To utilise a wide range of remote‐sensing
data to detect and map landslides, to
assess their activity and velocity,
• To determine the spatial‐temporal variation
of landslides and related consequences,
• To apply this in a subsequent hazard and
risk assessment to aid local and regional
decision makers;
• To improve the InSAR technique
towards to
high robustness for landslides movement
monitoring over rugged mountain area;
Source: geology.enr.state.nc.us

Research areas
Carpathian
Landslides in
Poland
Landslides in Wenchuan
earthquake area (LongMen
Mountain in Sichuan province)
+ Longnan area in South-East
of Gansu province
Three Georges
landslides
Hubei province

DRAGON 3
Workflow for landslides investigations
• Detection
• Characterization
• Monitoring
• Early Warning (Avelar et al 2011)
7
Regional mapping
(inventory, activity)
Site mapping
(geometry, volumes, types,
deformation, …)
Time evolution
Permanent real time
warning system

1.
Workflow for landslides investigations
Detection of instabilities
– Methods:
Airborne Laser Scanning
INSAR (PS, SBAS,…)
�Regional mapping
�State of activity of landslides
Main challenges:
• Increase the detection ability of InSAR
compared to classical inventories
8
Landslide inventory based on ALS
Zbyszyce landslide (Poland)

Workflow for landslides investigations
2. Characterization of instabilities
– Methods: Airborne and Terrestrial
Laser Scanning
INSAR (PS, SBAS,…)
�Site mapping: geometry, type, …
�Types of movement (deformation)
Main challenges:
• Using displacement time series to
define sliding mechanisms
9
Very long range TLS system
Czchow (Poland) 2012

Landslide mapping and inventory
(from ALS data)

Methods
• Conventional differential SAR interferometry (InSAR) with L ,C ,X
bands data
• Multitemporal InSAR methods: PSI SBAS
• Landslide Inventory based on change detection with optical images
including hyperspectral
• Change detection based on alternate polarisation data (ASAR)
• Aiborne and terrestrial laser scanning (ALS and TLS) to obtain detailed
elevation data
Improvements & new developments:
• The improved SAR image coregistration methods suitable for mountain area
including external DEM assisted and based on local optimum criteria
• operational algorithm and methodology for monitoring using persistent
scatterers interferometry (PSI) and corner reflector (CR‐InSAR) technique on
time‐series of SAR data
• multi criteria point target select method,
• DEM based network construction method,
• precise CR positionig method and CR peak extracting method,

Data provided by ESA and NRSCC

Other Data
• Maps and previous studies (geology,
hydrogeology, geological engineering
reports)
• Available measurements (geodetic
measurements, data from monitoring
sensors e.g. inclinometers, piezometers)
• Meteorological data
• LiDAR
data (terrestrial and airborne) for
detailed DEM
• Other satellite data: Terrasar‐X
Reading data from piezometer
and inclinometer Cieszyn
(Poland) 2012

Landslides in China
• In China approximate 2/3 areas are the
mountainous areas
• 56% of Chinese population lived in mountainous
areas

Longnan
2010 Gansu Zhouqu mudslide (Yin, 2010)
+ Wenchuan areas

Longnan
+ Wenchuan areas (2)
← Suoertu landslide
←Xieliupo landslide
Landslides in widely
distributed thick
loess and easy
weather rocks
16

Shuping landslide
Three Georges area

Trihedral + GPS
Three Georges area
trihedral bihedral
Corner Reflectors mounted on Shuping landslide

ASAR Data
Three Georges area
3m Desc
1m Desc
1m Asc
TerraSAR‐X Data:
StripMap
Spotlight descending
Spotlight ascending
Data processing: China Aero Geophysical Survey and RS Center
for Land and Resources

Landslides in Carpathians
Location of landslides according to the prelliminary recordong
1968 – 2000. (Polish Geological Institute – Carpathian Branch
•65% of all landslides in Poland are located in Carpathians
(6% of the territory)
•Total number of lanslides:
> 23.0000
•Average landslide density:
1 landslide / 1 sq. km

Klodne landslide

Aerial photo 2006
Aerial photo 02.07.2010 r
Klodne landslide
HORIZONTAL DISPLACEMENTS

Klodne landslide
SAR interferometry with TerraSAR-X (StripMap)
Full phase cycle equals to LoS
displacement of 15.5 mm

Miedzybrodzie landslide
Envisat ASAR desc + asc PS & SBAS

Expected results
• The creation of detailed multi‐temporal landslide inventory maps which
describe landslide distribution, process types and their state of activity for
the test areas.
• An attempt to creation of local and regional landslide susceptibility,
hazard, vulnerability, risk maps and management strategies
• Forecasts of future landslide risks with respect to Global Change (and
land‐use changes)
• Improved SAR image coregistration algorithm will be designed and
implemented, this will solve the problem of conventional polynomial
method
• Baseline re‐estimation algorithm based ground GCPs, this will improve the
surface land movement accuracy
• Multi‐criteria stable point select method and LiDAR DEM based network
construction method
• Corner reflectors InSAR data processing flow

Thanks for your
attention!
Presentation prepaired by:
Liu Guang
Zbigniew Perski
Mark-Henri Derron
Shibiao Bai