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انسجام معلوماتی وپروگرام ماین پاکی. iMMAP. Information Management for Disaster Risk Reduction. Because Information Matters به خاطرکه به اطلاعات اهمیت می دهیم. Peppino S Disperati Senior Information Management Officer. iMMAP – www.immap.org . VISION
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انسجام معلوماتی وپروگرام ماین پاکی iMMAP Information Management for Disaster Risk Reduction Because Information Matters به خاطرکه به اطلاعات اهمیت می دهیم Peppino S Disperati Senior Information Management Officer
iMMAP – www.immap.org VISION To be a leading international resource for relief, development and host government agencies in humanitarian information management and supporting services. MISSION iMMAP’smission is to alleviate the pain and suffering of those in need. iMMAP accomplishes this mission by providing decision makers at all levels with reliable, relevant and timely information upon which to act. • Humanitarian Information Management • Lebanon, Iraq, Afghanistan, Horn of Africa, Liberia, Tanzania, Laos, Thailand, Sudan, Nicaragua, Sri Lanka, Indonesia, Myanmar, Colombia, Haiti, Ethiopia, Pakistan; Surveys Kosovo, Chad, Thailand, Afghanistan, Vietnam, Iraq, Lebanon, Liberia, Armenia, Democratic Republic of Congo, Georgia, Myanmar, Haiti, Pakistan; Training Survey and Assessment, Quality Assurance, IMSMA, HIM. Present work in Afghanistan Environment DRR Database Security Incidents Education IM Bilateral support Government
DRR: approach and activities INFORMATION INFORMATION INFORMATION INFORMATION Flood analysis Common Operating Picture RAF database and maps ERM NGOs Base maps Government
Disaster data interoperability ERM hazard maps can contribute to the creation of a Common Operating Picture for Disasters Risk Reduction Overall hazards reported in ERM hazard maps Data collected by ERM help to bridge the distance between risk scenarios obtained by hazard models and real disaster events Match between flood data in ERM match NATO Flood model Breakdown of ERM flood hazards March between hazard data in ERM and IOM reports ERM Flood hazards match at 70% with another flood data source on flood risk (eg NATO Flood Model)
Identification of disaster-prone areas Information provided with the ERM hazard maps fills existing gaps on contingency plans to identify disasters-prone areas 1,066 records on community-based disasters for the seven provinces targeted • Information on hazards can be overlaid on: • Landcover • Rivers • Settlements • DEM / Slopes • Health infrastructures • Education infrastructures • Roads network • Security incidents • Population High accuracy of settlements selected validated with high resolution satellite imagery
Identification of disaster-prone areas Intensively irrigated cultivated land Rainfed cultivated land Intensively irrigated cultivated land Rainfed cultivated land Intensively irrigated cultivated land Rainfed cultivated land
Indicators of community resilience to disasters ERM targets village/communty level which is a fundamental indicator ofcommunity-based resilience The data structure of the ERM allows the combination of disaster-related data with single settlement and with most used community coping mechanisms
iMMAP Activities on Disaster IM Common Operating Picture for Disaster Risk Reduction and Resilience • Provincial Atlas with high resolution satellite imageries • Disaster data • Population: • CSO • Landscan • Estimates of population at risk • Livelihoods • Landcover • Estimates of livelihoods at risk
Problems and challenges faced in DRR projects • Information life cycle: • Data standardization and interoperability • Data collection • Information dissemination • Information usage
Solutions used to solve natural disaster risks • Develop country level risk scenarios and simulation • Participative mapping • Training for data collection, gps use • OASIS for database, synchronization and sharing
Special or unique experience Networking, campaigning Information Management Expertise Unique tool for database, sharing and synchronization Information Management applied to DRR with a cross-cutting approach to Food Security, IDPs, Education, Health and Nutrition Capacity building for data collection, data entry, database consolidation
Thank you ! any question