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www.unisdr.org

Establishing standardized National Disaster Loss Databases

IAP Meeting

06-08 September 2011

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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.

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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

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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

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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.

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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;

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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)

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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)

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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…

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What is the difference?

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DesInventar globally

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DesInventar in the region

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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)

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Reporting, Statistical Analysis and data exchangeInventories 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

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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

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Temporal Analysis (Trends): distribution of losses over time Behaviour of disaster losses is key in understanding trends and essential for monitoring the effectiveness of DRRNumber 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

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Spatial distribution of houses destroyed in Sri Lanka after Tsumani 2004

Spatial Analysis (patterns): distribution of losses over space

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Spatial distribution of Landslides (1970-2007)

Spatial Analysis (patterns): distribution of losses over space

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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

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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

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Composition of disasters

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Spatial distribution

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Spatial distribution

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Colombia

Hybrid loss exceedance curve

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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

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Interested in implementing DesInventar in your country?

UNISDR Asia Pacific Regional OfficeAttn. Abhilash Panda/Sujit Mohantyemail: pandaa@un.org/mohanty@un.org

OR

UNDP Regional Centre BangkokAttn. Rajesh Sharmaemail: rajesh.sharma@undp.org