1. www.unisdr.org 1 Establishing standardized National Disaster Loss Databases IAP Meeting 06-08 September 2011

2. www.unisdr.org 2 HYOGO FRAMEWORK FOR ACTION A2 Develop, update periodically and widely disseminate risk maps and related information to decision- makers, the general public and communities at risk Develop systems of indicators of disaster risk and vulnerability at national and sub-national scales Record, analyse, summarize and disseminate statistical information on disaster occurrence, impacts and losses, on a regular bases through international, regional, national and local mechanisms.

3. www.unisdr.org 3 No systematic collection of disaster damage/loss data (in most countries)- What does it lead to? Loss of valuable information; Difficult to determine long-term impact on development; Difficult to understand risk change trends; Difficult to determine vulnerability of local structures, infrastructures, society; No way to learn from the past; Lack of critical information much needed for conducting hazard vulnerability risk assessment

4. www.unisdr.org 4 What is DesInventar A data collection methodology A set of analysis methodologies A set of Software Tools DesInventar Usage Contexts As a Historical Disaster database As a Post-disaster damage & loss data collection tool

5. www.unisdr.org 5 DesInventar Methodology: … essentially proposes the collection of homogeneous data about disasters of all scales. The information compiled and processed is entered in a scale of time and referenced to a relatively small geographic unit.

6. www.unisdr.org 6 Why DesInventar Increases USABILITY due to disaggregation of information to local/municipality level DesInventar databases collect a large number of Loss Indicators (EMDAT only 3: deaths, affected, $), that can be augmented by countries. DesInventar allows collection of data of disasters at ALL scales;

7. www.unisdr.org 7 Why DesInventar Allows HOMOGENEOUS data collected for all countries Uses STANDARDS to exchange information Has fully documented analytical methodologies It is the FIRST STEP towards a full Risk Assessment Ability to demonstrate usage in Probabilistic Risk Assessments (Hybrid Models)

8. www.unisdr.org 8 Why DesInventar Provides Out of the box Analytical and Mapping functions; Reduces development cost (Free Open Source) Web enabled – Intranet or Internet settings Fully documented Easily customized to fit specific needs Interface is easily translated (now 10 languages, including Eastern languages and alphabets) Fully tested software (over 15 years of development)

9. www.unisdr.org 9 Usage of Loss Database in Risk Assessments Provide historical vulnerability indexes Provide Empirical Loss Exceedance Curves (GAR) Historical data can help validating Risk Assessments Historical data can be use calibrating Risk Assessments Generate proxy indicators of Risk (for hard-to-model risks or when no data is available) Allow monitoring of DRR measures Provide a dynamic vision of historic risk evolution over time Provide evidence-based support to decision makers And many other…

10. www.unisdr.org 10 What is the difference?

11. www.unisdr.org 11 DesInventar globally

12. www.unisdr.org 12 DesInventar in the region

13. www.unisdr.org 13 Typical contents of a DesInventar Disaster database The actual screen for data capture. It can be customized by users. Standard Effects (killed, injured, affected, etc.) Extension (Sectorial detail information)

14. www.unisdr.org 14 Reporting, Statistical Analysis and data exchange Inventories allow the production and exchange of tabular aggregated and detailed tabular data Aggregates by event, Iran. Other statistical measures such as Variance, Std Dev, correlation, etc. can also obtained from Inventories Detailed report exported to Excel, Iran database

15. www.unisdr.org 15 Composition Analysis – what is causing what damage? Number of Deaths per disaster type Composition Analysis of disaster data in Tamil Nadu (India) Number of Houses destroyed per disaster type This type of analysis shows what types of disasters are affecting a region and compares the different types of events and specific types of effects (human life, housing, agriculture, etc.). Helps focusing the analysis

16. www.unisdr.org 16 Temporal Analysis (Trends): distribution of losses over time Behaviour of disaster losses is key in understanding trends and essential for monitoring the effectiveness of DRR Number of Deaths excluding Tsunami, Tamil Nadu (India) Number of reports of floods and people killed by epidemics in Orissa, India 11 years, showing a high correlation between floods and epidemics. Ovals show non-related epidemic events. Seasonal distribution of floods in Mexico

17. www.unisdr.org 17 PRODUCTS OF A NATIONAL DISASTER OBSERVATORY Spatial distribution of houses destroyed in Sri Lanka after Tsumani 2004 Spatial Analysis ( patterns): distribution of losses over space

18. www.unisdr.org 18 PRODUCTS OF A NATIONAL DISASTER OBSERVATORY Spatial distribution of Landslides (1970-2007) Spatial Analysis ( patterns): distribution of losses over space

19. www.unisdr.org 19 Historical data used to validate Risk/Hazard maps Direct Mortality due to Cyclone/Winds in Orissa Number of Reports of Cyclone/Winds Houses Damaged or Destroyed due to Cyclone, Winds Comparison of Cyclone/wind reports, deaths, damages and Hazard Atlas - ORISSA

20. www.unisdr.org 20 Direct Mortality due to Floods in Orissa Damaged and Destroyed houses due to Floods in Orissa Number of Flood Reports in Orissa Comparison of Flood reports, deaths, damages and Hazard Atlas - ORISSA Historical data used to validate Risk/Hazard maps

21. www.unisdr.org 21 Composition of disasters

22. www.unisdr.org 22 Temporal behaviour

23. www.unisdr.org 23 Spatial distribution

24. www.unisdr.org 24 Spatial distribution

25. www.unisdr.org 25 Colombia Hybrid loss exceedance curve

26. www.unisdr.org 26 DesInventar IMPLEMENTATION Process Identification of partners Finding an appropriate ‘home’ for the database Training workshops ( sensitization & Training of trainers) Historical Research phase (30 years data) Start of day by day collection Production of Analysis: –Preliminary –Extensive/Intensive –Risk-Poverty –Risk-Environment Continuous improvement and quality control Mainstreaming Analysis/Data into national DRR

27. www.unisdr.org 27 Interested in implementing DesInventar in your country? UNISDR Asia Pacific Regional Office Attn. Abhilash Panda/Sujit Mohanty email: pandaa@un.org/mohanty@un.org OR UNDP Regional Centre Bangkok Attn. Rajesh Sharma email: rajesh.sharma@undp.org