Disaster Inventories Workshop
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Transcript of Disaster Inventories Workshop
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Maputo, Mozambique, August 18-23 of 2008
Disaster Inventories Workshop
* UNDRO (1979), Natural Disasters and Vulnerability Analysis in Report of Expert Group Meeting
Risk = Physical Exposure x Vulnerability
Risk = Hazard x Element exposed x Vulnerability*
Degree of population or infrastructure “fragility”
Population living in the exposed area, infrastructure
Frequency & Magnitude (or intensity of hazard
Number of expected people killed, other losses
EQUATION OF RISK
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Maputo, Mozambique, August 18-23 of 2008
Disaster Inventories Workshop
The Risk Triangle:
RISK
Exposure
VulnerabilityH
azard
Risk is a combination of the interaction of hazard, exposure, and vulnerability, which can be represented by the three sides of a triangle.
If any one of these sides increases, the area of the triangle increases, hence the amount of risk also increases.
If any one of the sides reduces, the risk reduces.
If we can eliminate one side there is no risk.
Reliable &
Accurate
Data
Reliable & Accurate
Data
Rel
iabl
e &
Acc
urat
e
Dat
a
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Maputo, Mozambique, August 18-23 of 2008
• Hazard: a natural or social-technological phenomena that produces damages to human lives, economic/social infrastructure and environment (earthquakes, floods, droughts, etc.)
• Vulnerability: Degree of population or infrastructure “fragility” to hazards.
• Risk: the probability of a certain level of loss to occur.
Disaster Inventories Workshop
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Maputo, Mozambique, August 18-23 of 2008
Disaster Inventories Workshop
Event
Response
Recovery
Preparedness
Mitigation
Prevention
RISKMANAGEMENT
DISASTER RISK MANAGEMENT CYCLE
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Prevention, Preparedness, Mitigation, Risk Reduction….
“Effective early warning and preparedness, land use planning and appropriate construction, risk assessment in projects and planning, community based risk management, insurance (financial and social) and asset protection through social safety nets among others dramatically reduce human exposure to hazard and susceptibility to harm. Action to reduce risks from natural disasters must be at the centre of development policy”
DFID Policy Briefing, Disaster risk reduction: a development concern, 2004.
Disaster Inventories Workshop
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Maputo, Mozambique, August 18-23 of 2008
Disaster Inventories Workshop
– Emergency: “The phase immediately after impact is characterized by the intense and serious disturbance […] and the minimum conditions necessary for the survival and functioning of the affected social unit are not satisfied
– Recovery: Process of re-establishing acceptable and sustainable living conditions through the rehabilitation, repair and reconstruction of destroyed, interrupted or deteriorated infrastructure, goods and services and the reactivation or promotion of economic and social development in affected areas
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Disaster Inventories Workshop
• UNDAC: mainly for response purposes(United Nations Disaster Assessment and Coordination). Being replaced by a series of more specialized assessments (UNOSAT, EC-IRA, WHO-RHA, etc.)
• ECLAC: adopted for measuring direct and indirect economic and social impacts, divided by economical sectors(Economic Commission for Latin America and the Caribbean)
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• Are targeted to specific hazards• Require large amounts of information• Involve complex modeling• May change over time• Urban or regional
Disaster Inventories Workshop
RISK ASSESSMENTS
“Risk assessment is the determination of quantitative or qualitative value of risk related to a concrete situation, location and a specific
threat.”
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Maputo, Mozambique, August 18-23 of 2008
Disaster Inventories Workshop
Hazard probability (frequency)
Exposed population
Simple Risk Index
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Disaster Inventories Workshop
– Identification of Priority areas (Hotspots)– Evaluation of urgency of action– Support for Preparedness, Risk Mitigation, EWS
plans – Support for Policies/Regulations and investments – Strategic advantage for negotiation– Other applications
Some Applications of Risk Assessments
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Disaster Inventories Workshop
Mitigation actions Specifics
Engineering, constructing measures
Map. Inventory of non-engineered buildings; Design standards, building codes; potential incentives (reduced insurance cost, land title, etc…)
Physical planning measures Land–use and zoning regulations; map/inventory of lifelines facilities; location of population concentration; design of supply and transport networks
Economic measures Unemployment, income distribution, poverty levels; degree of diversification; taxation and incentive policies; access to insurance
Management and institutional measures
Political will to implement mitigation measures; Government structures established to plan; prioritization of planning; responsibility assignments
Social measures Commitment on public education; Participation of communities in decisions
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• Some of the Hypothesis that inspired the project Disasters are a problem of Development Natural disasters are not so “natural” Impact of Disasters is growing Small and medium disasters impact is
extremely high Small and medium disasters occurrence
patterns can show vulnerability
DesInventar: The Project
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What is DesInventar
• A data collection methodology• A preliminary analysis methodology• A set of Software Tools
DesInventar 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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Concepts Definitions Glossary of Events and Effects Recommendations & How to’s
DesInventar Data CollectionMethodology:
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Concepts:
Hazard
Vulnerability
Risk
Geography
DesInventar Methodology:
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Definition:
“Event” is defined as any social-natural phenomena that can be considered as a threat to life, properties, infrastructure and environment.
DesInventar Methodology:
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Definition:
“Disaster” is defined as the set of adverse effects caused by social-natural and natural phenomena on human life, properties, infrastructure and environment (an “Event”) within a specific geographic unit during a given period of time.
DesInventar Methodology:
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• Geography: – multi-layered area units– Hierarchical structure (currently limited to three levels)
– Usually Administrative boundaries – Challenge: Selecting the maximum resolution
DesInventar Methodology:
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DesInventar Methodology:
ACCIDENT HAILSTORM
FLASH FLOOD (ALLUVION) HEAT WAVE
AVALANCHE LANDSLIDE
BIOLOGICAL DISASTER LEAK
COASTLINE EROSION LIQUEFACTION
DROUGHT TSUNAMI
EARTHQUAKE PLAGUE
ELECTRIC STORM POLLUTION
EPIDEMIC RAINS
VOLCANIC ERUPTION SEDIMENTATION
EXPLOSION SNOWSTORM
FAILURE SPATE
FIRE STORM
FLOOD WINDSTORM
FOREST FIRE STRUCTURE
FROST SURGE
GLOSARY OF TERMS: EVENTS
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DesInventar Methodology:
DEFINITIONS OF EFFECTS
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• Recommendations & How to’s: Selection of Boundaries Choosing the maximum resolution Selecting Codes (and names) The Period of the research Selection of sources
DesInventar Methodology:
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• Recommendations & How to’s: When disaggregated data is unavailable Discrepancies among sources “Chained” events When geographical units are split Long duration events
DesInventar Methodology:
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Preliminary Analysis Methodology:
Preliminary analysis is a set of SIMPLE operations that can be routinely applied to a DesInventar database that can provide very quickly with proxy indicators of Risk and help identifying patterns and trends.
Is called “Preliminary” because it doesn’t correlate the data with other possible sources of data such as demography, topography, land use, etc. It is a “self-contained” analysis.
Deeper analysis should be done after to further prove conclusions and establish causes.
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Composition of disasters (type and effects)
Temporal analysis (trends and patterns)
Spatial distribution analysis (spatial patterns)
Cause-effect analysis Statistical Analysis (mean, max, deviation, variance)
Preliminary Analysis Methodology:
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Composition Analysis:
Shows what types of disasters are affecting a region
Compares the effect of different types of events
Analysis is done on specific types of effects (human life, housing, agriculture, etc.)
Can be done for the entire area or specific sub-regions
Preliminary Analysis Methodology:
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Use of Composition Analysis:
Provides initial figures aggregated in time and space showing the total impact of disasters.
Helps focusing the rest of the analysis by identifying critical types of events
Preliminary Analysis Methodology:
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Examples of Preliminary Analysis With Tamil Nadu Disaster Data
• Kanyakumari District
Composition of Disasters: Number of Reports
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• Kanyakumari District
Composition of Disasters: Number of Deaths
Examples of Preliminary Analysis With Tamil Nadu Disaster Data
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Maputo, Mozambique, August 18-23 of 2008
Examples of Preliminary Analysis With Tamil Nadu Disaster Data
• Kanyakumari District
Composition of Disasters: Number of houses damaged or destroyed
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Examples of Preliminary Analysis With Tamil Nadu Disaster Data
• State level figures (incomplete)Composition of Disasters: Number of Reports
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Examples of Preliminary Analysis With Tamil Nadu Disaster Data
• State level figures (incomplete)Composition of Disasters: Number of Deaths
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Maputo, Mozambique, August 18-23 of 2008
Examples of Preliminary Analysis With Tamil Nadu Disaster Data
• State level figures (incomplete)Composition of Disasters: Number of Houses Damaged or Destroyed
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Maputo, Mozambique, August 18-23 of 2008
Examples of Preliminary Analysis With Tamil Nadu Disaster Data
Temporal Analysis:
This type of analysis shows patterns of occurrence of disasters along time (for example the seasonality of atmospheric events) and trends of the occurrence and impact of disasters, calculated in terms of different effect variables, such as Number of deaths, Number of destroyed houses, number of reports etc.
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Examples of Preliminary Analysis With Tamil Nadu Disaster Data
Use of Temporal Analysis:
- Provides input for time aspects of contingency plans, DRM, etc.
- Follow up of effectiveness of Risk Mitigation Plans
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Examples of Preliminary Analysis With Tamil Nadu Disaster Data
• Kanyakumari DistrictOccurrence of Disasters: Number of Reports
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Maputo, Mozambique, August 18-23 of 2008
Examples of Preliminary Analysis With Tamil Nadu Disaster Data
• Kanyakumari District
Seasonality of Disasters: Number of Deaths
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Examples of Preliminary Analysis With Tamil Nadu Disaster Data
State level figures (incomplete)Occurrence of Disasters: Number of Reports
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Examples of Preliminary Analysis With Tamil Nadu Disaster Data
State level figures (incomplete)Trends in Disasters: Number of Deaths EXCLUDING TSUNAMI
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Examples of Preliminary Analysis With Tamil Nadu Disaster Data
Spatial Analysis:
This type of analysis shows patterns of occurrence of disasters over space, displayed as colored areas in terms of the number of reports and different effect variables, such as Number of deaths, Number of destroyed houses, etc.
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Examples of Preliminary Analysis With Tamil Nadu Disaster Data
Spatial Analysis:- Riskier and/or Vulnerable areas may be
identified by isolated areas or clusters of areas with higher than average level of impact
- It usually shows patterns of higher than average impact associated to geography elements (rivers, hill areas, etc)
- Can be combined with temporary analysis to provide seasonal occurrence maps
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Examples of Preliminary Analysis With Tamil Nadu Disaster Data
Use of Spatial Analysis:
- Provides Maps of proxy indicators of Risk (“proxy risk maps”) in absence of much higher cost, long term risk maps
- Should be used as input layer to modelled risk maps- Can be used to validate and complement risk maps
- DOES NOT REPLACE OTHER MODELLING-BASED RISK ASSESMENT MAPS or GIS SYSTEMS
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Maputo, Mozambique, August 18-23 of 2008
Examples of Preliminary Analysis With Tamil Nadu Disaster Data
• Kanyakumari District
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Examples of Preliminary Analysis With Tamil Nadu Disaster Data
• State level figures (Incomplete)
Patterns in Disasters:
Multi- Hazard Map of Number of Deaths
EXCLUDING TSUNAMI
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Maputo, Mozambique, August 18-23 of 2008
Examples of Preliminary Analysis With Tamil Nadu Disaster Data
• State level figures (Incomplete)
Patterns in Disasters: Multi-hazard Map of Number of Reports EXCLUDING TSUNAMI
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Maputo, Mozambique, August 18-23 of 2008
Examples of Preliminary Analysis With Tamil Nadu Disaster Data
• State level figures (Incomplete)
Patterns in Disasters:
Multi-Hazard Map of Number of Houses affected EXCLUDING TSUNAMI
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Maputo, Mozambique, August 18-23 of 2008
Examples of Preliminary Analysis With Tamil Nadu Disaster Data
• State level figures (Incomplete)
Patterns in Disasters: FLOODS Number of Reports
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Maputo, Mozambique, August 18-23 of 2008
Examples of Preliminary Analysis With Tamil Nadu Disaster Data
• State level figures (Incomplete)
Patterns in Disasters: FLOODS Number of Houses affected
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Maputo, Mozambique, August 18-23 of 2008
Examples of Preliminary Analysis With Tamil Nadu Disaster Data
• State level figures (Incomplete)
Patterns in Disasters: FLOODS Number of deaths
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Examples of Preliminary Analysis With Tamil Nadu Disaster Data
Statistical Analysis:- Provides Tabular form of data to support
other types of analysis- Provides aggregates of data by multiple
criteria with simple pivoting operations- Provides basic statistical measures (mean,
variance, std. deviation, maximums, etc)- Provides information to be further processed
by other systems (export of aggregated data)
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Examples of Preliminary Analysis With Tamil Nadu Disaster Data
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Discutir como sera implementado o Observatorio de Desastres em Mocambique. Como e quem o vai operar?
Quem serao os usuarios dos produtos do Observatorio. Como esses produtos serao acessados e disseminados?
Como sera realizado o processo de analise e sua relacao com a avaliacao do risco?
Discutir como sera implementado o processo de investigacao historica?
Outros pontos adicionais/sugestoes
Potential Use of DesInventar
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Input as vulnerability layer for Risk assessment models (‘proxy’ indicators)
Support for plans (Preparedness, Risk Mitigation, etc) Follow-up of efficiency of these plans Validation of Risk & Hazard Maps Support for Policies/Regulations and investments Strategic advantage for negotiation Damage Assessment System in major disasters Other applications
Potential Use of DesInventar
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DesInventar