using macro-level exposure indicators for future disaster ......

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Gizem Mestav Sarica, PhD Candidate Prof. Pan Tso-Chien, ED-ICRM Using Macro-Level Exposure Indicators for Future Disaster Risk Assessment in Megacities Background & Aim • Following the rapid urban growth in recent years, exposure could be considered as the most dynamic component in risk assessment processes. • Estimation of spatiotemporal change of exposure is a critical and intricate task especially for megacities which are complex systems with high loss potentials. • The conventional loss estimation approaches require a detailed inventory database of structures. Alternatively, macro-level socio-economic exposure indicators are used, relying on regularly updated data. • This study aims to project the natural disaster loss based on the spatiotemporal variability of exposure, assuming a direct relation between losses due to physical damages and business interruption, and the economic productivity of a region. Conclusions and Future Work • SLEUTH Urban Growth Model was used to assess the spatiotemporal change in built-up area at risk for selected megacities considering different types of natural disasters. • It was observed that each city is unique and shows different trends from past to future. However, the increase of built-up area in hazardous regions should be assessed carefully for disaster risk reduction. • Following the built-up area prediction for future, grid-based population and GDP are planned to be used for future loss estimation of selected megacities considering deterministic and probabilistic seismic hazard analysis approaches. Contact Us: Executive Director, ICRM ([email protected]) N1-B1b-07, 50 Nanyang Avenue, Singapore 639798 Tel: +65 6592 1866 Website: http://icrm.ntu.edu.sg www.ntu.edu.sg References: - Open data for resilience initiative field guide, GFDRR (2014) - Silva EA and Clarke KC 2002 Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal Computers, Environment and Urban Systems 26 525–552 - Wald DJ, Quintoriano V, Heaton TH and Kanamori H. 1999 Relationships Between Peak Ground Acceleration, Peak Ground Velocity, and Modified Mercalli Intensity in California Earthquake Spectra 15 557-564 What is Risk? Urban Growth Prediction - 2030 Built-up Area at Risk Methodology Urban Growth Modelling Built-up Area Hazard Built-up Area at Risk Aster GDEM Landsat USGS Slope Excluded Area Transportation (At least 2 snapshots) Urban Extent (At least 4 snapshots) Hillshade Test Mode Coarse Calibration Fine Calibration Final Calibration Prediction Mode Urban Growth Prediction for 2030 QGIS SLEUTH Calibration Mode Inputs Jakarta Metro Manila Istanbul Shenzhen Metro Manila Jakarta Istanbul Shenzhen As an initial step before the loss estimation, the change in built-up area at seismic risk and flood risk were obtained using the urban growth model projections for selected megacities, namely Istanbul, Jakarta, Metro Manila and Shenzhen. For this purpose, hazard maps obtained from different sources and built-up area from past, today and future are overlaid. Built-up Area at Seismic Risk was obtained for 10% Probability of Exceedance in 50 years for Jakarta, Metro Manila and Istanbul. Built-up Area at Flood Risk was obtained for Shenzhen. HAZARD The likelihood, probability, or chance of a potentially destructive phenomenon VULNERABILITY The likelihood that assets will be damaged or destroyed when exposed to a hazard event EXPOSURE The location, attributes, and values of assets that are important to communities RISK = HAZARD x VULNERABILITY x EXPOSURE The composite of the impacts of ALL potential events

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Page 1: Using Macro-Level Exposure Indicators for Future Disaster ... Sym/ICRM19/Documents/posters/Poster13.pdfDisaster Risk Assessment in Megacities Background & Aim • Following the rapid

Gizem Mestav Sarica, PhD CandidateProf. Pan Tso-Chien, ED-ICRM

Using Macro-Level Exposure Indicators for Future Disaster Risk Assessment in Megacities

Background & Aim• Following the rapid urban growth in recent years, exposure could be considered as themost dynamic

componentinriskassessmentprocesses.• Estimationofspatiotemporalchangeofexposureisacriticalandintricatetaskespeciallyformegacities

whicharecomplexsystemswithhighlosspotentials.• Theconventionallossestimationapproachesrequireadetailedinventorydatabaseofstructures.

Alternatively,macro-levelsocio-economicexposureindicatorsareused,relyingonregularlyupdateddata.• Thisstudyaimstoprojectthenaturaldisasterlossbasedonthespatiotemporalvariabilityofexposure,

assumingadirect relationbetween lossesdue tophysicaldamagesandbusiness interruption,and theeconomicproductivityofaregion.

Conclusions and Future Work• SLEUTHUrbanGrowthModelwasusedtoassessthespatiotemporalchangeinbuilt-upareaatrisk

forselectedmegacitiesconsideringdifferenttypesofnaturaldisasters.• Itwasobservedthateachcityisuniqueandshowsdifferenttrendsfrompasttofuture.However,the

increaseofbuilt-upareainhazardousregionsshouldbeassessedcarefullyfordisasterriskreduction.• Followingthebuilt-upareapredictionforfuture,grid-basedpopulationandGDPareplannedtobe

usedforfuturelossestimationofselectedmegacitiesconsideringdeterministicandprobabilisticseismichazardanalysisapproaches.

Contact Us: ExecutiveDirector,ICRM([email protected])N1-B1b-07,50NanyangAvenue,Singapore639798Tel:+6565921866Website:http://icrm.ntu.edu.sg

www.ntu.edu.sg

References:-Opendataforresilienceinitiativefieldguide,GFDRR(2014)-SilvaEAandClarkeKC2002CalibrationoftheSLEUTHurbangrowthmodelforLisbonandPorto,PortugalComputers,EnvironmentandUrbanSystems26525–552-WaldDJ,QuintorianoV,HeatonTHandKanamoriH.1999RelationshipsBetweenPeakGroundAcceleration,PeakGroundVelocity,andModifiedMercalliIntensityinCaliforniaEarthquakeSpectra15557-564

What is Risk?

Urban Growth Prediction - 2030 Built-up Area at Risk

Methodology

Urban Growth Modelling

HAZARDThe likelihood, probability, or chance of a potentially destructive phenomenon

VULNERABILITYThe likelihood that assets will be damaged or destroyed when exposed to a hazard event

EXPOSUREThe location, attributes, and values of assets that are important to communities

RISK = HAZARD x VULNERABILITY x EXPOSUREThe composite of the impacts of ALL potential events

Built-upArea

Hazard

Built-up Area at

Risk

• As an initial step before the loss estimation, the change in built-up area at seismic risk and flood risk were obtained using the urban growth model projections for selected megacities, namely Istanbul, Jakarta, Metro Manila and Shenzhen.

• For this purpose, hazard maps obtained from different sources and built-up area from past, today and future are overlaid.

Aster GDEM Landsat

US

GS

Slope

Excluded Area

Transportation(At least 2 snapshots)

Urban Extent(At least 4 snapshots)

Hillshade

Test Mode

Coarse Calibration

Fine Calibration

Final Calibration

Prediction Mode

Urban Growth Prediction for 2030

QG

ISS

LEU

TH

Cal

ibra

tion

Mod

e Inputs

Jakarta

Metro Manila Istanbul Shenzhen

• Built-up Area at Seismic Risk was obtained for 10% Probability of Exceedance in 50 years for Jakarta, Metro Manila and Istanbul.

• Built-up Area at Flood Risk was obtained for Shenzhen.

Met

ro M

anila

Jaka

rta

Istanbul

Shenzhen

• Asaninitialstepbeforethelossestimation,thechangeinbuilt-upareaatseismicriskandfloodriskwereobtainedusingtheurbangrowthmodelprojectionsforselectedmegacities,namelyIstanbul,Jakarta,Metro Manila and Shenzhen.

• Forthispurpose,hazardmapsobtainedfromdifferentsources andbuilt-up area frompast, today and futureareoverlaid.

• Built-up Area at Seismic Risk wasobtained for 10% Probability ofExceedancein50yearsforJakarta,MetroManilaandIstanbul.

• Built-up Area at Flood Risk wasobtainedforShenzhen.

HAZARDThelikelihood,probability,orchanceofapotentiallydestructivephenomenon

VULNERABILITYThelikelihoodthatassetswillbedamagedordestroyedwhenexposedtoahazardevent

EXPOSUREThelocation,attributes,andvaluesofassetsthatareimportanttocommunities

RISK = HAZARD x VULNERABILITY x EXPOSUREThecompositeoftheimpactsofALLpotentialevents