Annex B. Geospatial data available for land use and infrastructure analysis
Copy link to Annex B. Geospatial data available for land use and infrastructure analysisTable B.1. Housing data
Copy link to Table B.1. Housing data|
Indicators |
Description |
Data source |
Notes |
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Housing quality |
Average number of rooms per inhabitant (ratio) |
OECD Regional Statistics > Regional social and environmental indicators > Housing indicators |
TL2, 2000~2022 *The dwelling's floor area is another proxy for quality |
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Share of housing cost |
Share of housing cost (in % of household disposable income) |
OECD Regional Statistics > Regional social and environmental indicators > Housing indicators |
TL2, 2000~2022 *Too many missing values |
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Average building height |
Calculate average building heights at granular scale using height data for individual buildings (Bing Maps, Microsoft product) |
*Could be useful as a measure of density. *Potential issues with using data from private sources |
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Calculate average building heights at granular scale using average height and volume data at the grid level (100m2, 2018) |
*Aggregated to grid level, so less detailed than Bing data, but from public source (JRC) |
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Residential built-up area per capita |
(Residential built-up area) / (total population) |
*Could be interesting to measure residential built-up area changes vis-à-vis population changes. Could also work as an environment indicator |
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House prices, house price change |
Percentage change of house prices on the same period of the previous year *House prices respond to demographic change, determine wealth of local populations and are typically important for subnational government revenue *"Relying on transacted prices (and the number of transactions) rather than rents or survey responses ensures that the data reflects long-term commitments of housing choices rather than transitory ones." |
Available in OECD dotstat: Residential Property Prices Indices (RPPIs) |
TL2 from 2018 Q1 to 2021 Q4 for 21 countries TL3 from 2018 Q4 to 2022 Q3 for 12 countries *RPPIs are index numbers measuring the rate at which the prices of residential properties (flats, detached houses, terraced houses, etc.) purchased by households are changing over time. Both new and existing dwellings are covered if available, independently of their final use and their previous owners. *Only market prices are considered. They include the price of the land on which residential buildings are located. |
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Housing vacancies |
Percentage of vacant houses as a share of total housing stock *Use of granular geospatial population data and population change data, combined with residential building data, could provide an indication were housing is being abandoned. |
*Data available at the national level only for a limited number of countries, but not comparable. Would be very interesting (and important) if we could estimate this at the subnational level, if possible. |
Table B.2. Infrastructure data
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Indicators |
Description |
Data source |
Notes |
|---|---|---|---|
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Internet broadband access |
Share of households with internet broadband access (in % of total households) |
OECD Regional Statistics > Regional social and environmental indicators > Internet broadband access |
TL2, 2000~2022 *We also have internet speed for regions, probably more pertinent. |
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Share of households with internet broadband access |
Eurostat > Science, technology, digital society > Digital economy and society > ICT usage in households and by individuals > Regional ICT statistics |
NUTS1(&2), 2006~2021 |
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Internet speed |
Global fixed broadband and mobile (cellular) network performance |
Speedtest by Ookla Global Fixed and Mobile Network Performance Maps – Registry of Open Data on AWS |
zoom level 16 web mercator tiles (approximately 610.8 meters by 610.8 meters at the equator), quarterly updated |
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Network of public infrastructures |
Network of public infrastructures and human settlements |
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Access to infrastructure |
Number of facilities reachable by mode of transport (car, bike, walk) within a specific amount of time |
*Using OpenStreetMap data, can calculate isochrones. *Also can obtain point data on facilities using OpenStreetMap, or can obtain them from statistical offices (if they have this data in GIS form) |
Table B.3. Environment data
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Indicators |
Description |
Data source |
Notes |
|---|---|---|---|
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Air pollution |
Air pollution, level of PM2.5 (average level in µg/m³ experienced by the population) |
OECD Regional Statistics > Regional social and environmental indicators > Environmental indicators in regions |
TL2, 2000~2022 |
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Change in built-up area and built-up area per capita |
Using GHSL data to calculate ourselves |
*Would need to check comparability with the dotstat data that is provided by ENV if we were to calculate our own indicators |
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available both in absolute terms and percent of total land area |
Available in OECD dotstat |
TL2, TL3 and FUA level 1975, 1990, 2000, 2014 |
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GHG emissions |
GHG emissions per capita by sector |
Already available at NUTS2 level, more granular estimates possible. |
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Land cover and land use data |
Artificial cover, tree cover, semi-vegetated land cover; land use for forest, agriculture, residential and commercial use, etc. |
*To identify inefficient land cover and land use trends. |
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Land cover: tree; grassland; wetland; shrubland; sparse vegetation; cropland; artificial surfaces; bare area; inland water |
TL2 and TL3 1992, 2004, 2015, 2018, 2019 |
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land use (in absolute terms and %): arable land and permanent crop; permanent meadows and pastures; forest; other areas |
National level only, 2010-2021 |
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Climate-related natural hazards |
Temperature (1979 to present) *health, especially in the context of ageing |
Copernicus Climate Data Store (CDS) ERA5 hourly data on single levels |
All from the OECD Environment Working Papers No.201 'Monitoring exposure to climate-related hazards: Indicator methodology and key results' (p.15) |
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Thermal comfort indices derived from ERA5 reanalysis ERA5-HEAT |
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Precipitation (1979 to present) |
Copernicus CDS ERA5 hourly data on single levels |
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Drought (1950 to present) |
Copernicus CDS ERA5 Land monthly averaged data |
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Wildfire (1997 to 2021) *impacts on infrastructure, including transport and energy infrastructure, livelihoods, homes |
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Wind (1979 to present) |
Cyclone wind hazard maps (GAR 2015) |
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Copernicus CDS ERA5 hourly data on single levels |
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River flooding (no time coverage) |
JRC flood hazard maps at European and global scale |
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Coastal flooding (no time coverage) |
Global coastal flood hazard maps |
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Environmental hotspots (carbon sink potential; biodiversity) |
Areas of global significance for conservation, biodiversity, and biomass carbon density distribution |
10km grid cell |
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IIASA Global Hotspots Explorer *Water (water stress index, non-renewable groundwater stress index, drought intensity, peak flows risk, seasonality, inter-annual variability); *Energy (lack of access to clean cooking, heat event exposure, cooling demand, hydroclimate risk to power production); *Land (crop yield change, agricultural water stress index, habitat degradation, nitrogen leaching) |
2010, 2020, 2030, 2040, 2050, 2060, 2070, 2080, 2090, 2100 *Global Hotspots Explorer (hotspots-explorer.org) provides projections based on climate change (1.5, 2.0, 3.0 degrees Celsius) scenarios and socioeconomic (SSP1, SSP2, SSP3) scenarios |
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Local vulnerability to environmental hazards, including from climate change |
National level only, 1961-2021 |
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Global Forest Resources Assessment 2020 |
National level only, 1990-2020 |
Table B.4. Service facility data
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Indicators |
Description |
Data source |
Notes |
|---|---|---|---|
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Health care facilities |
The number of active physicians for 1000 pop. |
OECD Regional Statistics > Regional Social and Environmental indicators > Health access |
TL2/TL3, 2008-2022 |
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The number of hospital beds for 1000 pop. |
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The number of hospital beds |
https://ec.europa.eu/eurostat/databrowser/view/HLTH_RS_BDSRG/default/table?lang=en |
NUTS2, 1993-2016 |
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Locations of hospitals, doctors, and pharmacies |
OECD postgis database |
*Using the points data we can calculate accessibility *We also have cinemas, retail shops, banks, and airports |
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Education facilities |
Locations of schools and universities |
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Share of population 25 to 64 year-olds by educational attainment (Below upper secondary education; Upper secondary and post-secondary non-tertiary education; Short-cycle tertiary education; Bachelor or equivalent; Master or equivalent; Doctoral or equivalent) |
OECD Regional Statistics > Regional Education > Educational attainment of the population, by age group |
TL2 -2016-2022 *Educational attainment is defined as the highest grade completed within the most advanced level attended in the educational system of the country *We also have the same data for the population group of 25 to 34 year-olds |
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Locations of kindergarten, Library, School, University, College |
*Using the points data we can calculate accessibility *Getting data from national/regional statistics offices would be more desirable |
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Transport |
Locations of bus station, EV charging stations, Gas/petrol/marine fuel station |
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Financial service facilities |
Locations of ATM, Bank |
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Entertainment facilities |
Locations of cinema, Theatre |
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Emergency facilities |
Locations of fire station, Police station, Ambulance station |