ICT-Asia 2015
25 – 26 May 2015, SEARCA, Los Banos Laguna, Philippines
Satellite Remote Sensing for Risk
Assessments of Volcanic and
Other Natural Hazards
Soo Chin Liew 1, Jean-Claude Thouret 2
[email protected]
1 Centre
for Remote Imaging, Sensing and Processing
National University of Singapore, Singapore
2 Laboratoire
Magmas et Volcans,
Université Blaise Pascal, Clermont-Ferrand, France
Introduction
 Our collaboration between CRISP, National University of
Singapore and LMV, Université Blaise Pascal started in
2007, established through a STIC Asia project 20092010.
 We focus on applying remote sensing techniques to the
assessment of volcanic eruptions, volcanic hazards and
risk, and other natural hazards in Southeast Asia, in
particular in Indonesia and nearby countries.
 Optical and radar satellite imagers are used for mapping
geology, landforms, and tracking deposits produced by
recent eruptions from active volcanoes in Indonesia.
 Very high resolution satellite images enable detail
mapping of volcanic features.
CRISP-NUS and LMV-UBP publications
EOS Trans AGU 2008: Liew S.C., Thouret J.-C., Gupta A.
“First satellite images of a moving pyroclastic flow at Merapi volcano, Java,
Indonesia”. 27 May 2008, vol 89, no.22, p. 2002.
EOS 3 April 2012 ‒ Meetings: Thouret J.-C., Liew S.C., Gupta A.,
“Remote Sensing Helps to Assess Natural Hazards and Environmental Changes in AsiaPacific Region” Conference on Remote Sensing, Natural Hazards, and
Environmental Change; Kent Ridge, Singapore, 28–29 July 2011
Proceedings published by the University Blaise Pascal Press, December 2011.
+ 5 published papers in top Journals:
- Remote Sensing Environment 2010
- Geomorphology 2012, 2014
- Bulletin of Volcanology 2013, 2014
International meetings: EGU 2010, AGSO-AGU 2011, IAG & IAVCEI 2013
EGU April 2014 and Cities On Volcanoes 8 (Indonesia) 2014:
Co-chaired session on ‘Remote Sensing and Active Volcanoes’, 9-13 September
2014, Yogyakarta.
Remote Sensing of Active Volcanoes: Outline
• Introduction
– Active volcanoes: hazards and eruption monitoring
• Examples: Applications of remote sensing images in
monitoring active volcanoes
1. Geologic mapping, a challenge at unapproachable
volcanoes
2. Identification and delineation of pyroclastic deposits
3. Assessment of lahar-prone areas and processes
4. VHR DEMs for computing aggradation & erosion of
volcanic deposits
5. Interferometric SAR techniques for mapping land
deformation
What are the principal and lethal volcano hazards?
14/02/2014
Yogyakarta
Ash
Cloud
Eruption-related fatalities
Surge
Tephra fall 200 km from Kelut
Confined
pyroclastic
flow 2010
Surge
Merapi, 2006
Valley
confined
PDC
Merapi, surge effect, 2010
Pyroclastic density currents, formed from explosive
eruptions, are fast-moving clouds of hot gas, rock
fragments and ash. They include flows and surges.
Semeru, 2008
Lahars: rapidly flowing mixture
of rock debris and water from a
volcano.
Sources of water : heavy rains,
crater lakes breakouts, and
ice/snow meltwater .
How can remote sensing contribute to the geologic
knowledge of active volcanoes?
1. Improve geologic maps at active, unapproachable volcanoes
 Identify volcanic structures
 Understand changes at the surface
2. Identify and delineate deposits , especially
pyroclastic deposits using HSR imagery
Merapi, 2006
after large or persistent eruptions
3. Assess lahar-prone areas and processes
4. Compute the extent and volume of
deposits : high res. DEMs/DSMs
 study of growth/denudation rates
at active, composite volcanoes
APPLICATIONS OF HSR IMAGERY TO INDONESIAN VOLCANOES
Why Indonesian volcanoes?
GEOEYE
CRISP
Merapi and Semeru in densely populated areas
SEMERU
>90 000 people live in the ‘red zone’
>100 000 people in the “red zone”
~ 1 million on the ring plain
MERAPI, Nov 2013
1. Persisting eruptive
activity
SPOT5
15/11/2013
Merapi,
15 nov 2010
Large volume (70 x 106 m3)
and a broad range of
pyroclastic deposits
2. Rainfall 2 - 3.5 m/yr :
CRISP
Ikonos 2009
SEMERU, 2012
Lahars (debris flows) are
recurrent and destructive
1. Geologic Mapping
HSR satellite images help MAP and examine the STRUCTURAL
EVOLUTION of Semeru Volcano
Surveillance
DEM draped with IKONOS
Geologic map of Semeru
(multi images & MODVOLC)
Summit evolution
Jonggring Seloko vent and scar
Solikhin et al, 2009, 2012
Tectonic setting
Evolution of the summit after the Merapi 2010 eruption
GEOEYE 4 September 2011 (2 m)
PLEIADES, 29 September 2012 0.5 m
CRISP
Inferred
fault
Head of scar and
subsiding block
CNES
Evolution of the Merapi summit 2008 - 2012
Solikhin, Thouret
et al., 2014, BV
2. Identification and delineation of
pyroclastic deposits
First Satellite Image of a moving Pyroclastic Flow!
EOS Trans, AGU, May 2008 (Liew, Gupta and Thouret)
Remote Sensing of Environment, 2010 (Thouret et al.)
IKONOS
16 june 2006
Merapi
dome
Kaliadem
Kali
Gendol
HSR images are extremely
useful for mapping and
interpreting freshly erupted
volcanic deposits.
The IKONOS images document
the source, extent, lateral
Thouret et al., 2010, RSE
variations, and effects of the June
LMV-CRISP, Stic Asia
2006 block-and-ash flows of
Merapi.
Pyroclastic deposits of the Merapi eruption, 26 Oct – 6 Nov 2010
GEOEYE
Merapi,
15 nov 2010
South flank,
Gendol-Opak catchment and
deposit ‘segments’
Identify and delineate pyroclastic deposits - 2010 Merapi VEI 4
The 2010 Merapi eruption emplaced a variety of pyroclastic deposits
to longer distances than expected (16 km).
PDC deposits have included:
1. Valley-confined block-and-ash flows BAFs,
2. Pyroclastic flows that spilled over
the valley channel banks: overbank
OPFs,
3. And two types of pyroclastic surges:
3.1. High-energy surges --- upstream
3.2. Ash-cloud surges along the valley channels
and on the margins
Pictures: J-C. Thouret
3. Assessment of lahar-prone areas
and processes
Geologic map of 2010 Merapi pyroclastic and lahar deposits
Manual classification
GEOEYE
15 NOV 2010
CRISP
Semi-automatic classification
using supervised and decision tree.
HRS imagery help track lahar activity 2010 2012
Gendol-Opak
down valley
Temporal evolution:
Lahars remobilized PDCs
in 2011
Morphometric characteristics
taken into account for lahar
overbank and avulsion:
- Channel capacity / cross
sectional area
- Longitudinal change in
channel confinement
- Channel sinuosity
4. computing aggradation & erosion of
volcanic deposits
Aggradation and erosion at persistently active volcanoes
Follow up the evolution of a catchment conveying lahars based on HSR imagery, lowaltitude photographs and DEMs/DSMs
Objectives: to measure spatial (catchment 109 km2) and
temporal (1981-2011) evolution of aggradation and erosion
of pyroclastic deposits and lahar deposits.
To study the response of two rivers to the steady sediment
input from daily tephra fall and episodic pyroclastic flows.
Mt. Semeru
Lengkong
Rain induced lahars
Debris flows (φ>60%)
-Hyperconcentrated flows
(20%<φ<60%)
SE flank of Semeru
Drainage network of
Kobokan and Lengkong,
2005-2008 migration of
a sediment wave
Thouret et al., 2014
Combination of methods:
 Mapping, SPOT4 & 5,
airphotos : extent and in situ
thicknesses
 DEMs based on GNSS-D & TLS:
Comparison of annual mass
balance
 Linear aggradation/ablation
(m3/m)
 Areal denudation rate &
sediment yield (m3/km2/an)
Computing the extent and volume of deposits : space and ground
calibration for high resolution DEMs/DSMs
Merapi Volcano
TOPODEM
2008 & 2010 IKONOS images
CRISP
DSM IKONOS
DEM ‘ULM’
2010
ULM= low-altitude photographs
TOPODEM based on 1:25,000 scale topo maps
Basurkotanal & A. Solikhin, 2012
Two new (but preliminary) HSR DEMs/DSMs of Merapi Volcano
MERAPI PRIOR to
the 2010 eruption
TOPODEM
(JF Oehler, JC Thouret, 2014
Stereo-photogrammetry)
DSM Pléiades
2012 @ 5 m
MERAPI DEM/DSM (2 m)
POST - 2010 eruption
(JF Oehler, JC Thouret, 2014)
Stereo-photogrammetry
based on Pléiades 20122014
DSM Pléiades
2012 @ 2 m
Improving calculations of sediment budgets based on HSR DEMs/DSMs
Difference between DEM (‘UGM’
2011) and DSM (‘ULM’) 2010
Coordinates
UTM49S/WGS84
DEM ‘ULM 2010’
50 cm= soil + cover
Budget 1 year:
DSM ‘UGM 2011’
Lidar 1 m
Cut Volume – Fill volume
746017.6 m3 - 1056637.5 m3
Net Volume (Cut-Fill) :-310619.9 m3
Linear rate 1 yr: Channel length: ~2400 m
Annual linear rate: ~64.7 m3/m
Annual budget (1 year):
Norm. to channel ~0,36 km2 :
~ 4.3 x105 m3/km2
Annual areal budget / catchment ~3,30 km2 : ~ 4.7 x104 m3/km2
5. InSAR techniques for mapping land
deformation
Ka Ming CHUA 1, Qing WAN 1, Jean-Claude THOURET 2 and Soo
Chin LIEW 1
1
Centre for Remote Imaging, Sensing and Processing (CRISP), National
University of Singapore (NUS)
2 Laboratoire Magmas et Volcans, Université Blaise Pascal
Interferometric SAR (InSAR)
Slave
Master
0
ALOS PALSAR images © METI & JAXA
Differential InSAR (DInSAR)
Phase simulated from DEM
Digital Elevation Model
1500m
SRTM DEM by NASA JPL
0
Example: Merapi Eruption 2010
ALOS PALSAR images © METI & JAXA
Persistent Scatterer InSAR (PS-InSAR)
Satellite S1
Satellite S2
Different acquisition geometry
Δ
Acquisition at t0
Acquisition at t0+Δt
Persistent Scatterer Interferometry
(PS-InSAR)
• Persistent Scatterers
–
–
–
–
(a)
Dominant sub-pixel scatterers
Large Radar Cross Section (Intensity)
Stable over repeated acquisitions (Coherence)
Large dataset (usually >15 repeat pass radar data)
(b)
(c)
(a) Trihedral corner reflectors can be installed as a persistent scatterer. (b) Urban buildings can act as persistent scatterers.
(c) For vegetated regions, longer wavelength such as L-band penetrates through the canopy, resulting in higher coherence.
Persistent Scatterer Interferometry
(PS-InSAR)
•
Errors estimated and removed from PS-InSAR
Removed using external DEM (D-InSAR)
Mount Merapi, Central Java,
Indonesia
Mount Merapi, Central Java,
Indonesia
• Mount Merapi 2010 Eruption
–
–
–
–
26 October 2010 – 15 November 2010
Highly explosive eruption (VEI 4)
<400 casualties
>10,000 displaced
– SAR data provides valuable
information during eruption
• This study observes the inter-eruption
period using ALOS-PALSAR data with
PS-InSAR technique
ALOS PALSAR Images of Merapi
before (above, 16 Sep 2010) and after
(below, 01 Feb 2011) the eruption,
showing the change in crater
ALOS PALSAR Data Set
Methodology
• Software:
– Delft Objectoriented Radar
Interferometric
Software
(DORIS)
– Stanford Method
for Persistent
Scatterers
(StaMPS)
Results
Range
Satellite
flight
direction
(a) Linearly averaged rate of deformation of persistent scatterers in the
line of sight (LOS) of the satellite near the summit of Mt. Merapi from
June 2007 to February 2011, overlain on the intensity of the master
image in slant range. Clear subsidence in red is seen around the crater
while an uplift (cyan to blue) is observed on the south to southwest of
the summit, likely due to the magma ascent prior to the eruption.
Results
periodic cycles of small
uplift and subsidence
from 2007 to 2008
(b) A time series analysis of
the rate of displacement in
mm/day scatterers located at
point A in Figure (a). The rate
of displacement is assumed
to be linear between
acquisitions. We omitted the
data from 20090613 as the
number of days between
acquisitions is too big to
assume linear change.
• PS-InSAR results consistent with ground measurements
and other literature for Merapi
• All four phases of the 2010 eruption of Mount Merapi can
be monitored using SAR
• PS-InSAR has the potential to be applied to monitor
other active volcanoes