The Global IMWG Data Sub-group and OCHA-FIS will be working in 2018-2019 to further develop the guidance on country-specific CODs. Please contact FIS if you have suggestions, material or questions.
Potential CODs for Natural Disasters
The following is a list of potential country-specific CODs for three types of natural disasters. The list was created with the support of the Coordinated Data Scramble (Global Level IMWG), the analytical framework – part of MIRA), OCHA Needs Assessment and Analysis Section, two COD workshops (Berlin, April 2017 (OCHA-IMO) and Geneva, June 2017 (Global IMWG Data Sub-group) based on data required in past emergencies.
Not all of the datasets listed below are CODs!! It is up to the IM network in the country to identify what datasets are required as a common reference when preparing or responding to an emergency.
To identify CODs, use the Identifying a COD Tool if the IM network cannot decide if a dataset is a COD. Even if a dataset is not considered to be a COD it should still be shared on HDX as it could prove valuable to others. The Data Prioritization Tool can help when there are too many datasets identified as CODs and the IM network needs to identify priorities.
Cyclone, Typhoon, Hurricane
Pre-crisis dataset theme | Rational as COD |
Administrative boundaries | good for an initial estimate of people affected, PiN, used for Operational Presence (3W) and framework for analysis. It should include as many levels as possible and not only be thought of in terms of the 3W. More information here: COD-AB |
Population statistics (census) | Should be SADD (Sex and Age Disaggregated Data), should include as many admin levels as possible (the lower the better). More information here: COD-PS |
Vulnerable populations | Identification of datasets that provide information about vulnerable populations that exist prior to an emergency (e.g. pregnant/lactating women, people with disabilities, etc) These datasets are a subset of the COD-PS. |
Settlements | This is where people live. This will be required for operational purposes and it is even better if population numbers are attached. The IMWG needs to be ‘comfortable’ with the data and accept that it may not be complete or perfect. It should have an independent p-code system to the administrative boundary p-codes to allow for changes to take place with fewer repercussions. |
Transportation: Roads, bridges, ports, airports, helipads, ferry crossings | Baseline data related to access and logistics |
Elevation | To identify potential landslides, hard to access/remote villages |
Hydrology: Rivers, lakes, wetlands | Baseline data to see where flooding may occur or to identify hard to reach locations. If bridges are not available, they could be identified using hydrology layer. Flood forecasting Global Flood Awareness System and crop monitoring FEWSNET |
Water basins | Could help identify/refines areas that have the potential of being affected when dealing with floods – (TBC with hydrologist) |
Dams | Potential hazard during flooding |
Hydro lines | Related to access, if they cross over roads this impacts access to locations - people |
Education Facilities | Location of schools for potential operational purposes (evacuation centers, shelter purposes, distribution, collection, etc) and immediate recovery |
Health Facilities | Health zones can sometimes be more important than the COD-AB in health-related responses and should be identified by the IMWG. |
| Post-event dataset theme | Rational as COD and source if possible |
| Storm path | All should be using the same source, should use the same source as government |
| Wind buffer | All should be using the same source, should use the same source as government |
| Storm surge | All should be using the same source, should use the same source as government |
| Flood area | Initial and for 2-3 weeks after initial flooding. All should be using the same source and should use the same source as government. Consider that you may want cumulative data. Potential data sources include: UNOSAT Flood Portal, NRT Global Flood Mapping (for more information about Recommended Practice: Flood Mapping and Damage Assessment using Sentinel-2 Optical Data |
| Road access | Identification of road accessibility post-disaster to identify operational routes and constraints. Spatial data is provided by WFP for primary and secondary roads. It is available on WFPs GeoNode instance and via HDX and stored on OSM. |
Floods
| Pre-crisis dataset theme | Rational as COD |
| Administrative boundaries | good for an initial estimate of people affected, PiN, used for Operational Presence (3W) and framework for analysis. It should include as many levels as possible and not only be thought of in terms of the 3W. More information here: COD-AB |
| Population statistics (census) | Should be SADD (Sex and Age Disaggregated Data), should include as many admin levels as possible (the lower the better). More information here: COD-PS |
| Vulnerable populations | Identification of datasets that provide information about vulnerable populations that exist prior to an emergency (e.g. pregnant/lactating women, people with disabilities, etc) These datasets are a subset of the COD-PS. |
| Settlements | This is where people live. This will be required for operational purposes and it is even better if population numbers are attached. The IMWG needs to be ‘comfortable’ with the data and accept that it may not be complete or perfect. Should have an independent p-code system to the administrative boundary p-codes to allow for changes to take place with fewer repercussions. |
| Transportation: Roads, bridges, ports, airports, helipads, ferry crossings | Baseline data related to access and logistics |
| Elevation | To identify potential landslides, hard to access/remote villages |
| Hydrology: Rivers, lakes, wetlands | Baseline data to see where flooding may occur or to identify hard to reach locations. If bridges are not available, they could be identified using hydrology layer. |
| Water basins | Could help identify/refines areas that have the potential of being affected when dealing with floods – (TBC with hydrologist) |
| Dams | Potential hazard during flooding |
| Hydro lines | Related to access, if they cross over roads this impacts access to locations - people |
| Education Facilities | Location of schools for potential operational purposes (evacuation centers, shelter purposes, distribution, collection, etc) and immediate recovery |
| Health Facilities | Location of health facilities for ….Health zones can sometimes be more important than the COD-AB and should be identified. |
| Post-event dataset theme | Rational as COD and source if possible |
| Flood area | All should be using the same source, should use the same source as government |
| Precipitation forecast | All should be using the same source, should use the same source as government |
| Flood water detection data | Initial and for 2-3 weeks after initial flooding. All should be using the same source and should use the same source as government. Consider that you may want cumulative data. Potential data sources include: UNOSAT Flood Portal, NRT Global Flood Mapping (for more information about Recommended Practice: Flood Mapping and Damage Assessment using Sentinel-2 Optical Data. Flood forecasting Global Flood Awareness System and crop monitoring FEWSNET |
| Storm path | All should be using the same source, should use the same source as government |
| Road access | Identification of road accessibility post-disaster to identify operational routes and constraints. Spatial data is provided by WFP for primary and secondary roads. It is available on WFPs GeoNode instance and via HDX and stored on OSM. |
Earthquake
| Pre-crisis dataset theme | Rational as COD |
| Administrative boundaries | good for an initial estimate of people affected, PiN, used for Operational Presence (3W) and framework for analysis. It should include as many levels as possible and not only be thought of in terms of the 3W. More information here: COD-AB |
| Population statistics (census) | Should be SADD (Sex and Age Disaggregated Data), should include as many admin levels as possible (the lower the better). More information here: COD-PS |
| Vulnerable populations | Identification of datasets that provide information about vulnerable populations that exist prior to an emergency (e.g. pregnant/lactating women, people with disabilities, etc) These datasets are a subset of the COD-PS. |
| Settlements | This is where people live. This will be required for operational purposes and it is even better if population numbers are attached. The IMWG needs to be ‘comfortable’ with the data and accept that it may not be complete or perfect. Should have an independent p-code system to the administrative boundary p-codes to allow for changes to take place with fewer repercussions. |
| Transportation: Roads, bridges, ports, airports, helipads, ferry crossings | Baseline data related to access and logistics |
| Elevation | To identify potential landslides, hard to access/remote villages |
| Hydrology: Rivers, lakes, wetlands | Baseline data to see where flooding may occur or to identify hard to reach locations. If bridges are not available, they could be identified using hydrology layer. |
| Water basins | Could help identify/refines areas that have the potential of being affected when dealing with floods – (TBC with hydrologist) |
| Dams | Potential hazard during flooding |
| Hydro lines | Related to access, if they cross over roads this impacts access to locations - people |
| Education Facilities | Location of schools for potential operational purposes (evacuation centers, shelter purposes, distribution, collection, etc) and immediate recovery |
| Health Facilities | Location of health facilities for ….Health zones can sometimes be more important than the COD-AB and should be identified. |
| Post-event dataset theme | Rational as COD and source if possible |
| Modified Mercalli Intensity Scale (MMI) | All should be using the same source, should use the same source as government |
| Precipitation forecast | |
| Road access | Identification of road accessibility post-disaster to identify operational routes and constraints. Spatial data is provided by WFP for primary and secondary roads. It is available on WFPs GeoNode instance and via HDX and stored on OSM. |
Other possible CODs
The following could be considered CODs but even if not if used by partners for their purposes, they ideally should be shared.Theme | Dataset |
|---|---|
| Infrastructure | Land use/cover (geology) |
| Infrastructure | Building/housing type |
| Infrastructure | Telecommunication locations (e.g. towers) |
| Infrastructure | Oil Refineries (if relevant) |
| Infrastructure | Sports center (potential shelters/evacuation centers) |
| Infrastructure | Energy (power, gas, nuclear, oil, etc.) |
| Infrastructure | Waste collection sites |
| Infrastructure | Water treatment site |
| Infrastructure | Clean water access points |
| Infrastructure | Markets |
| Population | Disease profile |
| Population | Multidimensional Poverty Index |
| Population | Socioeconomic profiles |
| Population | Refugees/IDP camps ( if relevant) |
Resources
- Identifying a COD flowchart A flowchart that asks questions to help identify id a dataset is a COD
- Data Prioritization Tool A tool that can help prioritize dataset work when there are too many to work on (very helpful at the beginning of a disaster)
- Data lists from Coordinated Data Scramble
- Data sources, resources and possible ideas from MapAction
- Disaster Summary Sheets that lists datasets and their use from ACAPS