EstablishingNationalDisasterLossandDamageDatabases:Lessonsand
ExperiencesfromAsiaUNInternationalConferenceonSpace-basedTechnologiesforDisasterRiskReduction
“EnhancingDisasterPreparednessforEffectiveEmergencyResponse”Beijing24-26October2018
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