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
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