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World Congres on Disaster Management New Delhi
 

World Congres on Disaster Management New Delhi

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This is a presentation on Disaster Inventory, presented during the World Congress on Disaster Management in New Delhi

This is a presentation on Disaster Inventory, presented during the World Congress on Disaster Management in New Delhi

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    World Congres on Disaster Management New Delhi World Congres on Disaster Management New Delhi Presentation Transcript

    • Generation of Historical Vulnerability Indices using a DesInventar Database Sujit Mohanty Manager-Disaster Information Systems World Congress on Disaster Management New Delhi
    • Introduction
      • Concept
      • The InDisData project
      • Methodology and Tool - DesInventar
      • The Orissa Experience
      • Qualitative results
    • in·dex (în¹dèks´) noun
      • plural in·dex·es or in·di·ces (-dî-sêz´)
        • a. Something that serves to guide, point out, or
        • otherwise facilitate reference…
      • b. A number derived from a formula, used
      • to characterize a set of data…
        • Excerpted from The American Heritage« Dictionary of the English Language, Third Edition ® 1996 by Houghton Mifflin Company ..
    • Historical Vulnerability
      • Patterns : repeated periodic occurrence of losses
      • Trends : increasing magnitude of losses
      • Impact : high losses being caused by low magnitude events
      Will be defined and calculated based on:
    • The InDisData Project
      • A database of disasters to understand trends and patterns.
      • A systematic geo-referenced inventory of small, medium and large-scale disasters for past 30 years.
      • To rationalize decision making for disaster preparedness, as well as providing an objective base for vulnerability assessment and priority setting.
      • To support planning & policy decisions for disaster preparedness and mitigation.
    • Orissa Pilot Process
      • Data collected for 30 districts and 314 blocks from newspapers over a period of 32 years.
      • Data collected from media is compared with Government records.
      • Institutionalization with Government for sustainability.
      • Interpretation and analysis of the data shows new dimensions of risk & vulnerabilities of the State.
      • Orissa ‘Vulnerability Analysis Report’ is being prepared in association with ‘Center for Development Studies’.
    • DesInventar
      • A methodology
      • A tool
      • The previous experience in Latin America
      • http://www.desinventar.org
    • DesInventar
      • Methodology
      • Disaggregation of the effects
      • Geo-referenced data
      • Inclusion of Small and Medium Disasters
    • DesInventar The Software Tools Stand-alone and Web-enabled version
    • Preliminary Findings
      • Epidemics and cyclones are the greatest causes of deaths
      • Epidemics are highly associated with floods, but also occur as independent incidents.
      • Fire is the greatest cause of household destruction, comparable to Cyclone.
      • Floods affect people more than any other type of disaster.
    • Impact on Life Number of people killed in disasters in Orisa Epidemics (19,963 ) Cyclone (20,449)
    • Impact on Property Number of Houses Destroyed in Disasters Orissa Fire (436,212) Cyclone (376,285) Floods (135485)
    • Impact on Livelihood Number of people affected Flood ( 31’395,654) Cyclone(11’633,140) Drought(3’408,999) Rains (3’776,359)
    • Patterns: floods Total number of Victims and Affected by Floods in Orissa
    • Pattern: Epidemics People Killed by Epidemics in Orissa
    • Spatial Distribution of Disasters
    • Relation Floods-Epidemics Number of reports of floods and people killed by epidemics, 11 years, with apparently non-flood related epidemics.
    • Spatial Distribution of Floods and Epidemics
    • Relation Floods-Epidemics Number of reports in floods and people killed by epidemics, 11 years, in 5 less-flood prone districts. Districts of Koraput, Kandhamal, Kalahand, Rayadada and Gajapat
    • Trend: Epidemics Ascending trend of the effects of epidemics in Orissa.
    • Trend: Fire effects on Housing
    • Pattern: Fire Seasonal Seasonal Variation in Fire Pattern
    • Way forward:
      • Definition of a methodology to generate a numeric index based on trends, patterns and impact
      • Calculation of these indices for Orissa
      • Comparison of these indices against other vulnerability index
      • Fine tuning of the whole process
      • Use of the indices in Risk Assessment
    • InDisData is supported by: Ministry of Home Affairs National Institute of Disaster Management NIDM United Nations Development Programme UNDP The Network for Social Studies on Disaster Prevention in Latin America
    • THANK YOU