National disaster loss and damage databases structure for disaster statistics
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1 National disaster loss and damage databases structure for disaster statistics Presented by Rajesh Sharma Crisis Prevention and Recovery Asia Pacific Regional Centre Bangkok 2 December Presentation Outline Disaster loss and damage databases Disaster loss and damage database structure Disaster databases in Asia Guiding principles for disaster loss databases 2 1
2 Why disaster loss and damage databases? Losses and damages from disasters are not systemically recorded Poor understanding of emerging patterns and trends of disaster risks resulting in lack of targeted action Climate change and variability posing threats to development Intensities and frequencies of disasters changing 3 Disaster loss and damage database? Collection of data about occurrence and impacts of disasters Data capture over a period of time and geographical unit Storage, retrieval and compilation of data and information Sharing of data and information to all stakeholders in real time Analysis of data over a period of time and space to understand patterns and trends of risks 4 2
3 Types of data captured by the databases Data captured at high resolution sub district level Information about occurrences and impacts are captured over a long period of time (20 30 years) Direct impacts are captured (event, population, sectors) 5 Types of data captured by the databases (2) Direct impacts of an event Event details (date, location,intensity) intensity) Population affected (death, injured, affected, ) Damages and losses to sectors (houses, road, health, etc.) Analysis undertaken at provincial, district and sub district levels to derive emerging trends and patterns of events and impacts to feed into national and sub national planning 6 3
4 Types of data captured by the databases (3) Pre configured list of disaster events, definitions of events and impacts About 250 additional configurable data fields available for adding more indicators Pre defined set of analysis to create various maps, charts, tables, reports, statistical for different administrative levels (districts, ) 7 Disaster Loss Database for Cambodia (example) 8 4
5 Disaster Loss Database for Cambodia (example) 9 Disaster Loss Database for Cambodia (example) 10 5
6 Disaster databases in Asia In Asia, UNDP started supporting pilot implementation in 2002 in the Orissa state of India SiL Sri Lanka Nepal Iran Indonesia (more than 10 provinces) India (Orissa, Tamil Nadu and other States) Lao PDR Timor Leste Cambodia Several ongoing databases Vietnam, Myanmar, Philippines, Pakistan and Bhutan Database highly configurable to country specific needs 11 Status of the implementation of Disaster Inventories in Asia (2013) Institutionalized Under development Iran Pakistan Nepal Bhutan Orissa Myanmar Laos Andhra Pradesh Tamil Nadu Kerala Thailand Puduchery Cambodia Brunei Vietnam Philippines Maldives Sri Lanka Indonesia Timor-Leste 202,000 records First event in 1815AD 15 countries 12 6
7 Experiences of establishing disaster loss databases from Asia Risk Knowledge Fundamentals: Guidelines and Lessons for Establishing and Institutionalizing Disaster Loss Databases Available online at: undp.org/elibrary/publications/dldguidelines.pdf 13 A comparative review of Country level and regional disaster loss and damage databases Analysis of databases by Database characteristics Database content profile Quality assurance Accessibility Database uses 14 7
8 Applications GAR 2009, 2011 and 2013 Extensive intensive i risk analysis Disaster risk and poverty analysis Poverty monitoring Allocation of funds based of levels of risks Local disaster management plans 15 Guiding principles for disaster loss databases Developing national capacities Establishing and sustaining nationally led processes to create ownership and relevance Establishment of database is guided by institutional and legal context The database should address the needs and priorities of the country Sharingof database and analysis with all stakeholders 16 8
9 Empowered lives. Resilient nations. Thank you very much Rajesh Sharma 9
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