www.jrc.ec.europa.eu
Serving society
Stimulating innovation
Supporting legislation
Current status and Best Practices for
Disaster Loss Data recording in EU
Member States
213 January 2015
Contributors
Country
1 Austria
2 Belgium
3 Bulgaria
4 Croatia
5 France
6 Germany
7 Greece
8 Italy
9 Netherlands
10 Portugal
11 Romania
12 Slovenia
13 Spain
14 Sweden
15
United
Kingdom
WHY DO WE NEED LOSS DATA ?
313 January 2015
27-28 July 2013
Hailstorm
Germany
Source: SIGMA 1/2014
Natural catastrophes and man-made disasters 2013
413 January 2015
APPLICATION AREAS
Compensation Accounting
Forensics Risk modeling
LOSS
DATA
Avoiding sovereign
insolvency
Balance prevention
budget and loss
compensation
Fair and efficient
solidarity
mechanism
and/or insurance
market
Evaluate
prevention
measures
Improve
prevention policy
Accurate risk
assessment based on
locally relevant loss
exceedance curves
513 January 2015
International
level
European Level
National level
Post-2015 Framework for
Disaster Risk Reduction
National process involving a
number of stakeholders:
decision makers, scientists,
practioners…
Strong legal basis: EUSF,
Green paper on Insurance,
Floods & INSPIRE Directives...
LOSS DATA SERVING SEVERAL PURPOSES
613 January 2015
AT THE NATIONAL LEVEL
713 January 2015
AT THE EUROPEAN LEVEL
STRONG LEGAL BASIS
• Solidarity clause of the European Treaty
• European Union Solidarity Fund
• Council conclusions: Further Developing
Risk Assessment for Disaster Management
• Revised Union civil protection legislation
• Floods and INSPIRE Directives
• Green Paper on Insurance of Natural and
Man-made Disasters
• EU Strategy on adaptation to climate
change
• ….
813 January 2015
MINIMUM REQUIREMENTS FOR
LOSS DATA SHARING
913 January 2015
ANALYSIS FRAMEWORK
Conceptual loss data model
10
13 January 2015
Event ID
Hazard event
identification
Affected
elements
Loss
indicators
Version
Metadata
Directly
affected
population
Direct
damages/
losses
Aggregated loss
data
Killed
Missing
Evacuated
Direct
economic
loss
Sector
Owner
Location
Population
Occupancy
Event
classification
Year
Location
Comparative analysis
1113 January 2015
Purpose of loss databases
Application areas
1213 January 2015
Comparative analysis
1313 January 2015
Methodology of recording
Comparative analysis
1413 January 2015
Main findings
• 12 out of 15 participating Member States have
established and maintained a loss database,
• Large differences in the processes of loss data collection
and recording,
• Lack of standards (e.g. for human and economic losses)
that prevent aggregation at EU or global levels,
• Differences in IT systems,
• Differences in terminologies for peril classification,
• Drivers for loss data recording mainly linked to:
i) (semi) public national compensation schemes, ii)
existing national and EU legislations and iii) for
improving prevention and response mechanisms.
Gaps and aspirations
13 January 2015
Need for national and European legal frameworks:
Austria, Belgium, Bulgaria, Romania, Slovenia, Spain and Sweden
have binding legislation.
Public Private Partnership (PPP) or Public Public
partnership (PuP)
Mission Risques Naturels in France is a PPP (and to a certain extent
a PuP) and an example of a good practice, reinforcing the insurance
strategic role in disaster loss recording and data sharing.
Standardization/Classification
1613 January 2015
Agreed Terminologies/Definitions
Family Main event Peril
Earthquake Ash Fall
Mass Movement Fire following EQ
Volcanic Activity Ground Movement
Landslide following EQ
Lahar
Lava Flow
Liquefaction
Pyroclastic Flow
Tsunami
Flood Avalanche: Snow, Debris
Landslide Coastal Flood
Wave Action Coastal Erosion
Debris/Mud Flow/Rockfall
Expansive Soil
Flash Flood
Ice Jam Flood
Riverine Flood
Rogue Wave
Seiche
Sinkhole
Convective Storm Cold Wave
Extratropical Storm Derecho
Extreme Temperature Frost/Freeze
Fog Hail
Tropical Cyclone Heat Wave
Lightning
Rain
Sandstorm/Dust storm
Snow/Ice
Storm Surge
Tornado
Wind
Winter Storm/Blizzard
Drought Forest Fire
Glacial Lake Outburst Land fire: Brush, Bush, Pasture
Wildfire Subsidence
Animal Incident Bacterial Disease
Disease Fungal Disease
Insect Infestation Parasitic Disease
Prion Disease
Viral Disease
Impact Airburst
Space Weather Collision
Energetic Particles
Geomagnetic Storm
Radio Disturbance
Shockwave
Climatological
Biological
Extraterrestrial
Geophysical
Hydrological
Meteorological
IRDR peril classification: unified terminology
- for events classification
- for operating loss databases
MAIN EVENT:
A minimum requirement for shared loss data
Gaps and aspirations
1713 January 2015
Data Collection/Recording Methodologies
• Systematic approach for recording loss data,
• Assessment forms tailored to the type of damage and customized
by sector,
• Staff training,
• Strict division of duties,
• Clear documentation,
• Use of new technologies for
damage assessments :
Remote Sensing data
mobile mapping
crowd-sourcing, etc.
(Ajmar et al., 2010)
Gaps and aspirations
1813 January 2015
Framework For Human Impact Loss Indicators
Need for clear and unambiguous definitions for human losses
Main fields Definitions
Killed
Missing
Injured/disease/in need of medical assistance
EARLY WARNING RESPONSE CAPACITY RECOVERY
Pre-event Sheltered by emergency services Permanently homeless
Post-event Sheltered by private arrangements Temporarily homeless
Relocated Not homeless
Without shelter
Isolated
Increasingpriorityofneeds
DIRECTLYAFFECTED
primarylevelbyECLAC
INDIRECTLY
AFFECTED
Evacuated
People that are removed from
a place of danger to a safer
place. Breaking down that field
is related to the management
of different disaster phases.
People that suffer physical damage of infrastructure which threatens their basic livelihood conditions (limited access
to water, food, electricity, ….) but they have not been evacuated
PEOPLEINNEED
Tertiary level - outside affected area (by ECLAC)
Fatalities
Victims
Secondary level - within affected area (by ECLAC)
Breaking down the fields
(general options: by gender, by age, by vulnerable groups, ...)
People that are in need of immediate medical assistance as a direct result of the disaster
People that suffer of a disaster's indirect effects (e.g., loss of flow, deficiencies in public service)
People that suffer physical damage of their property but are not in need
Total mortality
1. level 2. level 3. level
Similar to direct and
indirect losses
(ECLAC)
• Rule of priority of needs
• Temporal component
Specific requirements of
different disaster stages
… of disaggregation
Disaggregation/
summation
Gaps and aspirations
19
Framework For Damage/Economic Loss Indicators
Direct tangible losses in national currency
Tangible Intangible
Direct
loss/damage
Physical damage to property
converted to monetary value
People
directly affected
Cultural heritage
Natural environment
Indirect loss Loss of flow
People
indirectly affected
Loss of future usage
(agriculture, forestry, tourism, ...)
Total loss Economic loss Affected people
Economic loss/number-size of
assets
Common
denominator
Monetary value Number of persons -
ECLAC
Direct losses
Gaps and aspirations
Uncertainty Handling
0
1
2
3
4
5
Measurement
Disagreement
Human errorCrediblity 1
Crediblity 2
Average Pedigree
score = 3.6
For each step of the process:
1- Data collection methodology
2- Data recording methodology
DETAILS IN PRESENTATION:
Xavier Romão, Esmeralda Paupério
Gaps and aspirations
2113 January 2015
Guidelines
Loss data sharing among Member States and with the EU
• Publicly accessible and interoperable national loss databases are
encouraged to allow for easy data exchange and information
sharing between different systems (e.g. the Shared
Environmental Information System (SEIS), EU open data portal)
• For better understanding the trans-boundary effects of disasters
• For a better comparison of progress towards increased resilience
across countries
• For a common EU framework that allows monitoring of progress
in the Post-2015 Framework for DRR
2213 January 2015
Data model
Loss
accounting
Data-sharing
HFA-2
DesInventar
Hazard event identification
Geographical location
National unit (NUTS1)    
Subnational units (NUTS2)  To be
defined
by the
MS

Subnational units (NUTS3)  
Lat/Lon (points, footprints)
Temporal information
Year    
Duration (in days)  
Month (beginning/ending) 
Event type specific attributes
Severity key data 
Reference to external
database
Hazard event ID   
Hazard event classification  
(Main
event)
 
Affected elements
Geographical location
Subnational units 
Data model
Loss
accounting
Data-sharing
HFA-2
DesInventar
Loss Indicators
Directly affected population
Killed    
Missing    
Evacuated    
Isolated
Victims 
Direct damage/loss
Physical damage   
Direct economic loss   
(Total
% of
GDP)

Sector  
(Total)

Owner (private, business,
public, etc.)
 
(Total)
Who bears the loss  
(Total)
Quality assurance
Sources  
Data collection
methodology
 
Data recording
methodology
 
Guidelines Minimum Requirements
Guidelines
2313 January 2015
Totals per ownership
Insurer
Individual
Business
NGO
Government
Totals over all sectors
 sectors
Social sector • Residential
• Education/research
• Culture/recreation
• Health sector
• Public administration
Infrastructure • Energy
• Drinking water and sanitation
• Transport
• Communication
Economic sector • Agriculture/forestry
• Trade/industry
• Tourism
Other • Clean-up costs
• Emergency relief costs
Possible divisions of sectors
Minimum requirements
For Loss data sharing
2413 January 2015
RECOMMENDATIONS
Data collection at Local level
• Engage municipalities and civil protection
Building a process at National level
• Considering the best practices in Member States and
the presented guidelines
Design of an advanced IT system
• Including a data model linked to other government
databases
• Expand with GIS platforms
2513 January 2015
RECOMMENDATIONS
Supporting legislation and active
involvement of local governments
• Political commitment
• Dedicated budget for loss databases
Encouraging PuP and PPP
• Ensure participation and ownership of all stakeholders
Information sharing
• Data-sharing of summary or aggregated statistics
• Open and interoperable databases

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Current status and Best Practices for Disaster Loss Data recording in EU Member States by Dr. Tom de Groeve

  • 1. www.jrc.ec.europa.eu Serving society Stimulating innovation Supporting legislation Current status and Best Practices for Disaster Loss Data recording in EU Member States
  • 2. 213 January 2015 Contributors Country 1 Austria 2 Belgium 3 Bulgaria 4 Croatia 5 France 6 Germany 7 Greece 8 Italy 9 Netherlands 10 Portugal 11 Romania 12 Slovenia 13 Spain 14 Sweden 15 United Kingdom
  • 3. WHY DO WE NEED LOSS DATA ? 313 January 2015 27-28 July 2013 Hailstorm Germany Source: SIGMA 1/2014 Natural catastrophes and man-made disasters 2013
  • 4. 413 January 2015 APPLICATION AREAS Compensation Accounting Forensics Risk modeling LOSS DATA Avoiding sovereign insolvency Balance prevention budget and loss compensation Fair and efficient solidarity mechanism and/or insurance market Evaluate prevention measures Improve prevention policy Accurate risk assessment based on locally relevant loss exceedance curves
  • 5. 513 January 2015 International level European Level National level Post-2015 Framework for Disaster Risk Reduction National process involving a number of stakeholders: decision makers, scientists, practioners… Strong legal basis: EUSF, Green paper on Insurance, Floods & INSPIRE Directives... LOSS DATA SERVING SEVERAL PURPOSES
  • 6. 613 January 2015 AT THE NATIONAL LEVEL
  • 7. 713 January 2015 AT THE EUROPEAN LEVEL STRONG LEGAL BASIS • Solidarity clause of the European Treaty • European Union Solidarity Fund • Council conclusions: Further Developing Risk Assessment for Disaster Management • Revised Union civil protection legislation • Floods and INSPIRE Directives • Green Paper on Insurance of Natural and Man-made Disasters • EU Strategy on adaptation to climate change • ….
  • 8. 813 January 2015 MINIMUM REQUIREMENTS FOR LOSS DATA SHARING
  • 10. Conceptual loss data model 10 13 January 2015 Event ID Hazard event identification Affected elements Loss indicators Version Metadata Directly affected population Direct damages/ losses Aggregated loss data Killed Missing Evacuated Direct economic loss Sector Owner Location Population Occupancy Event classification Year Location
  • 11. Comparative analysis 1113 January 2015 Purpose of loss databases
  • 12. Application areas 1213 January 2015 Comparative analysis
  • 13. 1313 January 2015 Methodology of recording Comparative analysis
  • 14. 1413 January 2015 Main findings • 12 out of 15 participating Member States have established and maintained a loss database, • Large differences in the processes of loss data collection and recording, • Lack of standards (e.g. for human and economic losses) that prevent aggregation at EU or global levels, • Differences in IT systems, • Differences in terminologies for peril classification, • Drivers for loss data recording mainly linked to: i) (semi) public national compensation schemes, ii) existing national and EU legislations and iii) for improving prevention and response mechanisms.
  • 15. Gaps and aspirations 13 January 2015 Need for national and European legal frameworks: Austria, Belgium, Bulgaria, Romania, Slovenia, Spain and Sweden have binding legislation. Public Private Partnership (PPP) or Public Public partnership (PuP) Mission Risques Naturels in France is a PPP (and to a certain extent a PuP) and an example of a good practice, reinforcing the insurance strategic role in disaster loss recording and data sharing.
  • 16. Standardization/Classification 1613 January 2015 Agreed Terminologies/Definitions Family Main event Peril Earthquake Ash Fall Mass Movement Fire following EQ Volcanic Activity Ground Movement Landslide following EQ Lahar Lava Flow Liquefaction Pyroclastic Flow Tsunami Flood Avalanche: Snow, Debris Landslide Coastal Flood Wave Action Coastal Erosion Debris/Mud Flow/Rockfall Expansive Soil Flash Flood Ice Jam Flood Riverine Flood Rogue Wave Seiche Sinkhole Convective Storm Cold Wave Extratropical Storm Derecho Extreme Temperature Frost/Freeze Fog Hail Tropical Cyclone Heat Wave Lightning Rain Sandstorm/Dust storm Snow/Ice Storm Surge Tornado Wind Winter Storm/Blizzard Drought Forest Fire Glacial Lake Outburst Land fire: Brush, Bush, Pasture Wildfire Subsidence Animal Incident Bacterial Disease Disease Fungal Disease Insect Infestation Parasitic Disease Prion Disease Viral Disease Impact Airburst Space Weather Collision Energetic Particles Geomagnetic Storm Radio Disturbance Shockwave Climatological Biological Extraterrestrial Geophysical Hydrological Meteorological IRDR peril classification: unified terminology - for events classification - for operating loss databases MAIN EVENT: A minimum requirement for shared loss data Gaps and aspirations
  • 17. 1713 January 2015 Data Collection/Recording Methodologies • Systematic approach for recording loss data, • Assessment forms tailored to the type of damage and customized by sector, • Staff training, • Strict division of duties, • Clear documentation, • Use of new technologies for damage assessments : Remote Sensing data mobile mapping crowd-sourcing, etc. (Ajmar et al., 2010) Gaps and aspirations
  • 18. 1813 January 2015 Framework For Human Impact Loss Indicators Need for clear and unambiguous definitions for human losses Main fields Definitions Killed Missing Injured/disease/in need of medical assistance EARLY WARNING RESPONSE CAPACITY RECOVERY Pre-event Sheltered by emergency services Permanently homeless Post-event Sheltered by private arrangements Temporarily homeless Relocated Not homeless Without shelter Isolated Increasingpriorityofneeds DIRECTLYAFFECTED primarylevelbyECLAC INDIRECTLY AFFECTED Evacuated People that are removed from a place of danger to a safer place. Breaking down that field is related to the management of different disaster phases. People that suffer physical damage of infrastructure which threatens their basic livelihood conditions (limited access to water, food, electricity, ….) but they have not been evacuated PEOPLEINNEED Tertiary level - outside affected area (by ECLAC) Fatalities Victims Secondary level - within affected area (by ECLAC) Breaking down the fields (general options: by gender, by age, by vulnerable groups, ...) People that are in need of immediate medical assistance as a direct result of the disaster People that suffer of a disaster's indirect effects (e.g., loss of flow, deficiencies in public service) People that suffer physical damage of their property but are not in need Total mortality 1. level 2. level 3. level Similar to direct and indirect losses (ECLAC) • Rule of priority of needs • Temporal component Specific requirements of different disaster stages … of disaggregation Disaggregation/ summation Gaps and aspirations
  • 19. 19 Framework For Damage/Economic Loss Indicators Direct tangible losses in national currency Tangible Intangible Direct loss/damage Physical damage to property converted to monetary value People directly affected Cultural heritage Natural environment Indirect loss Loss of flow People indirectly affected Loss of future usage (agriculture, forestry, tourism, ...) Total loss Economic loss Affected people Economic loss/number-size of assets Common denominator Monetary value Number of persons - ECLAC Direct losses Gaps and aspirations
  • 20. Uncertainty Handling 0 1 2 3 4 5 Measurement Disagreement Human errorCrediblity 1 Crediblity 2 Average Pedigree score = 3.6 For each step of the process: 1- Data collection methodology 2- Data recording methodology DETAILS IN PRESENTATION: Xavier Romão, Esmeralda Paupério Gaps and aspirations
  • 21. 2113 January 2015 Guidelines Loss data sharing among Member States and with the EU • Publicly accessible and interoperable national loss databases are encouraged to allow for easy data exchange and information sharing between different systems (e.g. the Shared Environmental Information System (SEIS), EU open data portal) • For better understanding the trans-boundary effects of disasters • For a better comparison of progress towards increased resilience across countries • For a common EU framework that allows monitoring of progress in the Post-2015 Framework for DRR
  • 22. 2213 January 2015 Data model Loss accounting Data-sharing HFA-2 DesInventar Hazard event identification Geographical location National unit (NUTS1)     Subnational units (NUTS2)  To be defined by the MS  Subnational units (NUTS3)   Lat/Lon (points, footprints) Temporal information Year     Duration (in days)   Month (beginning/ending)  Event type specific attributes Severity key data  Reference to external database Hazard event ID    Hazard event classification   (Main event)   Affected elements Geographical location Subnational units  Data model Loss accounting Data-sharing HFA-2 DesInventar Loss Indicators Directly affected population Killed     Missing     Evacuated     Isolated Victims  Direct damage/loss Physical damage    Direct economic loss    (Total % of GDP)  Sector   (Total)  Owner (private, business, public, etc.)   (Total) Who bears the loss   (Total) Quality assurance Sources   Data collection methodology   Data recording methodology   Guidelines Minimum Requirements
  • 23. Guidelines 2313 January 2015 Totals per ownership Insurer Individual Business NGO Government Totals over all sectors  sectors Social sector • Residential • Education/research • Culture/recreation • Health sector • Public administration Infrastructure • Energy • Drinking water and sanitation • Transport • Communication Economic sector • Agriculture/forestry • Trade/industry • Tourism Other • Clean-up costs • Emergency relief costs Possible divisions of sectors Minimum requirements For Loss data sharing
  • 24. 2413 January 2015 RECOMMENDATIONS Data collection at Local level • Engage municipalities and civil protection Building a process at National level • Considering the best practices in Member States and the presented guidelines Design of an advanced IT system • Including a data model linked to other government databases • Expand with GIS platforms
  • 25. 2513 January 2015 RECOMMENDATIONS Supporting legislation and active involvement of local governments • Political commitment • Dedicated budget for loss databases Encouraging PuP and PPP • Ensure participation and ownership of all stakeholders Information sharing • Data-sharing of summary or aggregated statistics • Open and interoperable databases