establishing national disaster loss and damage databases: … · 2018-11-30 · un international...

EstablishingNationalDisasterLossandDamageDatabases:Lessonsand

ExperiencesfromAsiaUNInternationalConferenceonSpace-basedTechnologiesforDisasterRiskReduction

“EnhancingDisasterPreparednessforEffectiveEmergencyResponse”Beijing24-26October2018

RajeshSharmarajesh.sharma@undp.org

BureauforPolicyandProgramme SupportUNDPBangkokRegionalHub,Thailand

Whydisasterlossanddamagedatabases?(1)

• Inthepast,mainfocusonemergencyresponseandreliefwithnoeffortstosystematicallyunderstandtheimpactsandcausalfactors

• Nodataaboutdisastersbeingcollectedandanalyzedleadingtolackofunderstandingofdisaster-developmentlinkages

• Poorunderstandingofthedisaggregatedimpactsofdisastersonpopulationsandsectors

• Significanteffortsneededtocollect,record,andanalyzedisaggregateddatatounderstandtheimpactsandtargetactionsforidentifyingandreducingrisks

Whydisasterlossanddamagedatabases?(2)

• Risingtemperaturesandsealevelrisecausingextremeweatherevents

• Intensityandfrequencyoftyphoonsandfloodsincreasingcausingunprecedentedlosses(Japan,Kerala,LaoPDR)

• Significantthreats,todevelopmentinaregionalreadyknowntobethemostdisasterprone

• Livelihoodsofmorethan60%populationdependsonclimate-sensitivesectors(agriculture,forestry,fishing)

• 40cmsealevelrisewillput11%oflandunderwaterinBangladeshandcreate7-10millionclimaterefugees(IslandnationssuchasKiribatilikelytobecomeuninhabitable)

Whydisasterlossanddamagedatabases?(3)

Agenda2030forDevelopment

• SendaiFrameworkforDisasterRiskReduction(SFDRR)

• SustainableDevelopmentGoals(SDGs)

• ParisAgreementforClimateChange

• NewUrbanAgenda…

• EmphasisonDataforDevelopment

Whatisdisasterlossanddamagedatabase?

• Collectionofhomogeneousdataaboutdisastersofallscales

• Dataiscapturedoveraperiodoftimeandgeographicalunit

• Storage,retrievalandcompilationofdataandinformationinaneasilyaccessiblemanner

• Sharingofdataandinformationwithallstakeholdersinrealtime

• Analysisofdataovertimeandspacetounderstandpatternsandtrendsofpatternsandemergingrisks

Typesofdatacapturedbythedatabases

• Datacapturedathighresolution – sub-districtlevel

• Informationaboutoccurrencesandimpactsarecapturedoveralongperiodoftime(20-30years)

• Directimpactsofanevent• Eventdetails(date,location,intensity)• Populationaffected– genderdisaggr.(death,injured,affected,…)• Damagesandlossestosectors(education,road,health,etc.)

• Analysisundertakenatprovincial,districtandsub-districtlevelstoderiveemergingtrendsandpatternsofeventsandimpactstofeedintonationalandsub-nationalplanninganddisasterriskreduction

UNDPeffortsinsettingupnationaldisasterlossanddamagedatabases

• Tounderstandtheimpactsofdisasters,UNDPactivelystartedimplementingDesInventar methodologyin2002inOdishastateofIndia

• The2004tsunamidisasterbroughtforwardtheneedfordisaggregateddataforplanningrecoveryandriskreduction– Maldives,SriLanka,TamilNadu(India),ThailandandIndonesia

• UNDPhassupportedabout40countriesgloballyinsettingupnationaldisasterlossanddamagedatabases

AComparativeReviewofCountry-LevelandRegionalDisasterLossandDamageDatabases

Globally, UNDP has supported about 40 disaster databases

Analysisofdatabasesby

•Databasecharacteristics•Databasecontentprofile•Qualityassurance•Accessibility•Databaseuses

Disaster Databases in Asia

220,000 recordsFirsteventin1815AD16countries

DisasterdatabasesinAsia

InAsia,UNDPstartedsupportingpilotimplementationin2002inOdisha(India)

- SriLanka - Nepal - Bhutan

- Maldives - Pakistan - DPRK

- Iran - India - Timor-Leste

- PNG

- LaoPDR - Cambodia - Indonesia

- Myanmar - Vietnam - Philippines

ExperiencesfromEstablishingDisasterLossDatabasesfromAsia

Risk Knowledge Fundamentals: Guidelines and Lessons for Establishing and Institutionalizing Disaster Loss Databases

Availableonlineat:http://www.snap-undp.org/elibrary/Publications/DLDGuidelines.pdf

Cambodia:AnalysisReportAvailableonlineat:

http://camdi.ncdm.gov.kh/DesInventar/Attached/Eng_CamDi_Analysis_Report_Final_LowRes.pdf

DisasterLossDatabaseforCambodia- CamDi

DisasterLossDatabaseforCambodia- CamDi

Flood

Fire

Storm Drought

Lightening

Flood

LighteningFire

DisaggregationofmortalitydatainCambodia

GovernmentowneddisasterlossanddamagedatabasesinAsia

Indonesia(DIBI)http://dibi.bnpb.go.id

Cambodia(CAMDI)http://camdi.ncdm.gov.kh

Myanmar(MDLD)http://mdld-rrd.gov.mm

UNDP’sApproachtoNationalDisasterLossandDamageDatabasestosupport‘Risk-InformedDevelopment’

GuidingPrinciples

• Institutionalandlegalcontextfordisasterriskreductionprovidesnecessaryframeworkfortheestablishmentofdisasterlossanddamagedatabaseinacountry

• Thenationaldatabaseisguidedbytheneedsandprioritiesofthecountry

• Buildonnationallyledprocessestocreateownershipandsustainabilityofthedatabase

GuidingPrinciples(2)

• Increasetheusefulnessandrelevanceofthedatabasetonationalandsub-nationalcontexts

• Dataanalysistoprovideinputstoplanninganddecision-makingprocessesinthecountry

• Hostingofthedatabaseinpublicdomaintosharethedatatoimproveunderstandingofrisksandtowarrantactionsfromallstakeholders

KeyLessons

1. Governmentownership2. Customizationandlocaladaptation3. Capacityofimplementingpartner4. Datasources,collectionandvalidation5. Dataanalysisforsupportingplanning6. In-countrytechnicalsupportandstaffing7. Regionaltechnicalsupport&backstopping8. Trainingoftechnicalstaff9. Needfortools/manuals

Challengesandgapsfordatacollection

• Lackofdatacollectionformat• SOPsfordatacollection• Cleardefinitions• Trainingofstaffcollectingdata• Qualitycontrolmechanismstobefurtherstrengthened• Technicaltermsinvariouslanguages• Notusingtechnologyeffectivelytocollectandvalidatedata• Lackofintegrationwithsectors

Applicationsatglobalandnationallevels

- GlobalAssessmentReports(GAR)onDRR– 2009,2011,2013,2015

- Extensiveintensiveriskanalysis

- Disasterriskandpovertyanalysis

- Povertymonitoring

- Allocationoffundsbasedoflevelsofrisks

- Localdisastermanagementplans

- InaRisk (Indonesia)

- Settinguplossreductiontargets

- Validationofriskassessmentmodels

- MonitoringofindicatorsofSFDRRandSDGs

DataEcosystemforResilientDevelopment

INFORMATION

COLLABORATION

Data Ecosystem(Structured/Non)

Participation

Per formance

Global Centre for Disaster Statistics (GCDS)

Programme concept

Athreeyearprogramme tosupporttheStrategicVision,institutionallyanchoredinUNDPBRH.

Programme Outcome

• TheachievementoftheSDGsandtheSFDRRsupportedthrougharobust,completeandsustainablenationalandglobalsystemofdisasterstatistics.

Programme Outputs

• MonitoringandreportingforSendaiFrameworkandSDGs• PartnershipwithUNOSATforprocurementofimageries• In-depthandtimelyanalysisoftheimpactofdisasters• Insightsintoimpactsofdisastersinkeysectors– agriculture,transport,health,education,andothers• UseofAIandmachinelearningforassessingtheimpactsofdisasters(PDNA)• Useofsocialmediaandearthobservationdata(inadditionofofficialstatistics)toanalysistheprogressonSendaiFrameworkandSDGs

UseofEarthObservationData

TheGCDSProgrammeisapartnershipwhichbuildsontherespectivestrengthsofUNDP,UNISDR,IRIDeS,andFujitsu.

• Corepartners:UNDP,UNISDR,IRiDeS,Fujitsu,nationalgovernments.• Regionaltechnicalpartners:OSSO,CIMA,UNDPRegionalHubsandCountryOffices• UNpartners:RegionalEconomicCommissions• Specialpartners:IDMC,RIMESandothers

Partnerships