Satellite and ground-based remote sensing for rapid seismic vulnerability assessment M. Wieland, M. Pittore

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1 Satellite and ground-based remote sensing for rapid seismic vulnerability assessment M. Wieland, M. Pittore Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences Centre for Early Warning Systems

2 Challenge and Motivation Risk Hazard Seismic risk megacities 2020 Exposure Vulnerability Earthquake Flood Landslide, Volcano Buildings People Economic activities Physical Social Economical pubs.usgs.gov buildingsurveyors.com GSHAP (1999) Kathmandu Valley 1883 Kathmandu Valley 2011 J.C. White (1883) M. Nüsser (2011) M. Pittore, M. Wieland, K. Fleming, Perspectives of a global dynamic exposure model: from remote sensing to crowd-sourcing, Natural Hazards (under review). 2

3 Challenge and Motivation Bishkek urban growth ( ) Urban extent (km²) Year out of date Bishkek f0 highly aggregated spatially fragmented local amplification effects M. Pittore, D. Bindi, S. Tyagunov, M. Wieland, M. Pilz, M. Picozzi, S. Ullah, S. Parolai, J. Zschau, Seismic hazard and risk in Central Asia, Scientific Technical Report, STR 11/14 (2012), DOI: /GFZ.b

4 Objectives Mapping exposure over large areas at multiple scales for rapid vulnerability assessment MR multi-spectral satellite images Ground-based omnidirectional images HR multi-spectral satellite images digitalglobe.com Coupling remote sensing with in-situ imaging can be optimized over broad areas. Requirements Transferable and scalable methods. Low-cost and gobally available data. Free and open-source software. Standardized and adaptable content. Remote rapid visual survey (RRVS) allows for a reasonable assessment. M. Wieland, M. Pittore, S. Parolai, J. Zschau, B. Moldobekov, U. Begaliev, Estimating building inventory for rapid seismic vulnerability assessment based on multi-source imaging, SDEE, 36 (2012)

5 The approach M. Wieland, M. Pittore, S. Parolai, J. Zschau, B. Moldobekov, U. Begaliev, Estimating building inventory for rapid seismic vulnerability assessment based on multi-source imaging, SDEE, 36 (2012)

6 The technology EO tools Prioritization tool Vulnerability assessment satellite images aerial images Rapid environmental mapping focus map sample and route use of proxies probabilistic information integration image archive rapid-per-building 6

7 Earth observation tools EO tools Source Code QGIS Plugin Rapid large area building inventory assessment 7

8 Earth observation tools Pre-processing Segmentation Classification Time-series analysis Multi-spectral satellite data Graph-based segmentation Data Mining, Machine Learning Post-Classification Comparison a before 1975 Image pixel Image segments Pre-dominant building types Construction date periods a Urban structure types extracted from Landsat (30m). Backgroun: Google Sat. (~1m) M. Wieland, M. Pittore, S. Parolai, J. Zschau, Exposure estimation from multi-resolution optical satellite imagery for seismic risk assessment, ISPRS International Journal of Geo-information, 1 (2012)

9 Earth observation tools Pre-processing Analysis I Analysis II Analysis III Multi-spectral satellite data Segmentation, Clusteranalysis Data Mining, Machine Learning Shadowanalysis Image pixel Building footprints, location, counts Roof structure and color (-material) Building height Building density M. Wieland, M. Pittore, S. Parolai, J. Zschau, Exposure estimation from multi-resolution optical satellite imagery for seismic risk assessment, ISPRS International Journal of Geo-information, 1 (2012)

10 Prioritization and optimization of in-situ surveys Prioritization tool Focus map Sampling framework Focus maps Sampling and routing

11 Prioritization and optimization of in-situ surveys Indicator D1 Building density Indicator D2 Inundation areas Other restrictions Street-network, costs + +? In-situ observations Specific flooding-relevant building attributes (material, entrance, etc.) Pittore, M. Wieland, M. Errize, C. Kariptas, I. Güngör, Improving post-earthquake insurance claim management: a novel approach to prioritized geospatial data collection, ISPRS International Journal of Geo-information, (under review). 11

12 Prioritization and optimization of in-situ surveys Focus map Sampling points Route navigation Building density Inundation areas Street network Pittore, M. Wieland, M. Errize, C. Kariptas, I. Güngör, Improving post-earthquake insurance claim management: a novel approach to prioritized geospatial data collection, ISPRS International Journal of Geo-information, (under review). 12

13 Prioritization and optimization of in-situ surveys Process schema Focus map Route optimization Data acquisition Information integration & Model updating Yes Improvement? No Focus map Routing path 13 Pittore, M. Wieland, M. Errize, C. Kariptas, I. Güngör, Improving post-earthquake insurance claim management: a novel approach to prioritized geospatial data collection, ISPRS International Journal of Geo-information, (under review). 13

14 Rapid Environmental Mapping Rapid environmental mapping GFZ-MOMA RRVS-tool Image data archive Rapid, detailed building inventory

15 Mobile Mapping System (GFZ-MOMA) Navigation unit 30 kg weight. Simple mounting and usage. Up to 30 frames per second acquisition. Autonomous battery power (up to 6h). Real-time GPS-tracking und routing. M. Wieland, M. Pittore, S. Parolai, J. Zschau, Remote sensing and omnidirectional imaging for efficient building inventory data-capturing, IGARSS 2012, Munich. Car mounting system 15

16 Mobile Mapping System (GFZ-MOMA) Omnidirectional image data acquisition, Cologne 2012 M. Wieland, M. Pittore, S. Parolai, J. Zschau, Remote sensing and omnidirectional imaging for efficient building inventory data-capturing, IGARSS 2012, Munich. 16

17 3D facade reconstruction Estimated height: 31m Reference height:: 30m background image: earth.google.com M. Wieland, M. Pittore, S. Parolai, J. Zschau, Remote sensing and omnidirectional imaging for efficient building inventory data-capturing, IGARSS 2012, Munich. 17

18 Remote Rapid Visual Screening (RRVS) RRVS data analysis RRVS data entry International taxonomy standards: GEM Taxonomy earthquake relevant building attributes. Extension for flooding relevant building attributes. Spatio-temporal database Brzev, S., C. Scawthorn, A. W. Charleson, and K. Jaiswal, GEM Basic Building Taxonomy, Version 2.0, GEM Ontology and Taxonomy Global Component project (2013),

19 Demonstration: Remote Rapid Visual Screening (RRVS) M. Pittore, M. Wieland, Towards a rapid probabilistic seismic vulnerability assessment using satellite and ground-based remote sensing, Natural Hazards (2012), DOI: /s z. 19

20 Information integration and risk assessment Bayesian network (Earthquake) Satellite Const. date Type C T US T S In-situ H Height (Omni) No. of storeys UST type: 7-9 storeys, concrete, panel, residential Const. date: Height (Omni): 29 m No. of storeys: 9 WHE type: 6 Vulnerability (EMS-98): E T W HE Type (WHE) background image: earth.google.com V Vulnerability (EMS-98) A B C D E F posterior probability (EMS-98) From proxies to vulnerability classification. From deterministic to probabilistic vulnerability. Adaptable to multiple hazard types. B: Buildings P: Population M. Pittore, M. Wieland, Towards a rapid probabilistic seismic vulnerability assessment using satellite and ground-based remote sensing, Natural Hazards (2012), DOI: /s z. 20

21 Iterative uncertainty aware refinement and model updating Process schema Data collection Spatial distribution of available information Information integration Model updating Multi-res Model Probabilistic vulnerability model Uncertainty estimation Refinement? Yes No Focus map M. Pittore, M. Wieland, Towards a rapid probabilistic seismic vulnerability assessment using satellite and ground-based remote sensing, Natural Hazards (2012), DOI: /s z. Model uncertainty 21

22 Conclusions and next steps Exposure estimation from remote sensing and omnidirectional imaging Approach, methods and algorithms are transferable, scalable and cost-/time-efficient; Free and open-source software development; Standardized data acquisition(taxonomies). Information integration and vulnerability assessment From deterministic to probabilistic vulnerability estimation; Towards a continuous spatio-temporal monitoring framework. 22

23 Thank you for your attention... Traditional wood frame construction (yurta), Kyrgyzstan 23