French Southern and Antarctic Territories

Food Prices for French Southern Territories. Contains data from the FAOSTAT bulk data service.

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes: - macroregion (admin-1 including region) - region (admin-2 including state, province, department, governorate) - macrocounty (admin-3 including arrondissement) - county (admin-4 including prefecture, sub-prefecture, regency, canton, commune) - localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb) The dataset also contains human settlement points and polygons for: - localities (city, town, and village) - neighbourhoods (borough, macrohood, neighbourhood, microhood) The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the README.md file for complete data source metadata. Refer to our blog post for explanation of field names. Data corrections can be proposed using Write Field, an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['amenity'] IN ('mobile_money_agent','bureau_de_change','bank','microfinance','atm','sacco','money_transfer','post_office') Features may have these attributes: name name:en amenity operator network addr:full addr:city source name:fr This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['waterway'] IS NOT NULL OR tags['water'] IS NOT NULL OR tags['natural'] IN ('water','wetland','bay') Features may have these attributes: name name:en waterway covered width depth layer blockage tunnel natural water source name:fr This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['railway'] IN ('rail','station') Features may have these attributes: name name:en railway ele operator:type layer addr:full addr:city source name:fr This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

OpenStreetMap contains roughly 539 km of roads in this region. Based on AI-mapped estimates, this is approximately 100 % of the total road length in the dataset region. The average age of data for the region is 4 years ( Last edited 19 days ago ) and 8% of roads were added or updated in the last 6 months. Read about what this summary means : indicators , metrics OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['highway'] IS NOT NULL Features may have these attributes: name name:en highway surface smoothness width lanes oneway bridge layer source name:fr This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

OpenStreetMap contains roughly 410 buildings in this region. Based on AI-mapped estimates, this is approximately 100% of the total buildings.The average age of data for this region is 4 years ( Last edited 19 days ago ) and 6% buildings were added or updated in the last 6 months. Read about what this summary means : indicators , metrics OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['building'] IS NOT NULL Features may have these attributes: name name:en building building:levels building:materials addr:full addr:housenumber addr:street addr:city office source name:fr This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['aeroway'] IS NOT NULL OR tags['building'] = 'aerodrome' OR tags['emergency:helipad'] IS NOT NULL OR tags['emergency'] = 'landing_site' Features may have these attributes: name name:en aeroway building emergency emergency:helipad operator:type capacity:persons addr:full addr:city source name:fr This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['amenity'] = 'ferry_terminal' OR tags['building'] = 'ferry_terminal' OR tags['port'] IS NOT NULL Features may have these attributes: name name:en amenity building port operator:type addr:full addr:city source name:fr This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['amenity'] IN ('kindergarten', 'school', 'college', 'university') OR tags['building'] IN ('kindergarten', 'school', 'college', 'university') Features may have these attributes: name name:en amenity building operator:type capacity:persons addr:full addr:city source name:fr This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['healthcare'] IS NOT NULL OR tags['amenity'] IN ('doctors', 'dentist', 'clinic', 'hospital', 'pharmacy') Features may have these attributes: name name:en amenity building healthcare healthcare:speciality operator:type capacity:persons addr:full addr:city source name:fr This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['amenity'] IS NOT NULL OR tags['man_made'] IS NOT NULL OR tags['shop'] IS NOT NULL OR tags['tourism'] IS NOT NULL Features may have these attributes: name name:en amenity man_made shop tourism opening_hours beds rooms addr:full addr:housenumber addr:street addr:city source name:fr This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['place'] IN ('isolated_dwelling', 'town', 'village', 'hamlet', 'city') Features may have these attributes: name name:en place population is_in source name:fr This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

Resource has no data rows! No conflict and disaster population movement (flows) data recorded for French Southern Territories in the last 180 days. Internally displaced persons are defined according to the 1998 Guiding Principles (https://www.internal-displacement.org/publications/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. The IDMC's Event data, sourced from the Internal Displacement Updates (IDU), offers initial assessments of internal displacements reported within the last 180 days. This dataset provides provisional information that is continually updated on a daily basis, reflecting the availability of data on new displacements arising from conflicts and disasters. The finalized, carefully curated, and validated estimates are then made accessible through the Global Internal Displacement Database (GIDD), accessible at https://www.internal-displacement.org/database/displacement-data. The IDU dataset comprises preliminary estimates aggregated from various publishers or sources.

French Southern and Antarctic Territories population density for 400m H3 hexagons. Built from Kontur Population: Global Population Density for 400m H3 Hexagons Vector H3 hexagons with population counts at 400m resolution. Fixed up fusion of GHSL, Facebook, Microsoft Buildings, Copernicus Global Land Service Land Cover, Land Information New Zealand, and OpenStreetMap data.

Food Prices for French Southern and Antarctic Territories. Contains data from the FAOSTAT bulk data service.

French Southern Territories administrative division with aggregated population. Built from Kontur Population: Global Population Density for 400m H3 Hexagons on top of OpenStreetMap administrative boundaries data. Enriched with HASC codes for regions taken from Wikidata. Global version of boundaries dataset: Kontur Boundaries: Global administrative division with aggregated population

Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. "People Displaced" refers to the number of people living in displacement as of the end of each year. "New Displacement" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once. Contains data from IDMC's Global Internal Displacement Database.

List of airports in the French Southern Territories, with latitude and longitude. Unverified community data from ourairports.com.

Live list of active aid activities for French Southern and Antarctic Territories shared via the International Aid Transparency Initiative (IATI). Includes both humanitarian and development activities. More information on each activity (including financial data) is available from http://www.d-portal.org

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below. These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. They can also be visualised and explored through the woprVision App. The remaining datasets in the links below are produced using the "top-down" method, with either the unconstrained or constrained top-down disaggregation method used. Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively): - Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019) -Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019). -Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets. -Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020. -Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national population estimates (UN 2019). Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645