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This dataset contains areas by degree of urbanisation (revised definition, 2018). The degree of urbanisation classifies local administrative units (LAU in Europe into three categories: thinly (rural), intermediate (towns and suburbs or small urban) and densely populated (cities or large urban) areas. The classification is based on a population distribution grid with raster cells of 1 sqkm size. Data are available for EU countries, Norway, Switzerland, Serbia and Iceland. The data is available at 1:100 000 resolution for internal commission users and a generalised 1:1 000 000 resolution is available to the public via the GISCO Dedicated Section on the Eurostat website. Classification based on method described in manual on Territitorial typologies in consulation with Member states.
Nomenclature of Territorial Units for Statistics (NUTS) - Statistical Units - Data sets (2003 - 2021)
The Nomenclature of Territorial Units for Statistics (NUTS) is a hierarchical classification of statistical regions and subdivides the EU economic territory into regions of four different levels (NUTS 0, 1, 2 and 3, moving respectively from larger to smaller territorial units). NUTS 1 is the most aggregated level. An additional Country level (NUTS 0) is also available for countries where the the nation at statistical level does not coincide with the administrative boundaries. For example Mt Athos in Greece and Mellum and Minsener Ogg in Germany. The NUTS classification has been officially established through Regulation (EC) No 2016/2066 of the European Parliament and of the Council and its amendments. A non-official NUTS-like classification has been defined for the EFTA countries and candidate countries. An introduction to the NUTS classification is available here: http://ec.europa.eu/eurostat/web/nuts/overview. The datasets are based on: EuroBoundaryMap (EBM) from EuroGeographics (scale of 1:100.000), Global Administrative Unit Layer (GAUL) country data from UN/FAO, data from the National Statistical Institute of Turkey (TurkStat) (might vary for different years). The different scale levels were derived by generalisation of the 100K scale. The public datasets are available under the Download link indicated below. Available scales are: 100k, 1M, 3M, 10M, 20M, 60M. Date of the NUTS regions are currently available for the years 2003, 2006, 2010, 2013, 2016 and 2021. The full datasets are available via the EC restricted download link. Here six scale ranges (100K, 1M, 3M, 10M and 20M, 60M) are available. Coverage is the economic territory of the EU, EFTA countries and candidate countries as in the respective year.
Global Healthsites Mapping Project - building an open data commons of health facility data with OpenStreetMap
When a natural disaster or disease outbreak occurs there is a rush to establish accurate health care location data that can be used to support people on the ground. This has been demonstrated by events such as the Haiti earthquake and the Ebola epidemic in West Africa. As a result valuable time is wasted establishing accurate and accessible baseline data. Healthsites.io establishes this data and the tools necessary to upload, manage and make the data easily accessible. Global scope The Global Healthsites Mapping Project is an initiative to create an online map of every health facility in the world and make the details of each location easily accessible. Open data collaboration Through collaborations with users, trusted partners and OpenStreetMap the Global Healthsites Mapping Project will capture and validate the location and contact details of every facility and make this data freely available under an Open Data License (ODBL). Accessible The Global Healthsites Mapping Project will make the data accessible over the Internet through an API and other formats such as GeoJSON, Shapefile, KML, CSV. Focus on health care location data The Global Healthsites Mapping Project's design philosophy is the long term curation and validation of health care location data. The healthsites.io map will enable users to discover what healthcare facilities exist at any global location and the associated services and resources.