Argentina GIS data
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Retirement Notice: This item is in mature support as of September 2025 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. Argentina Locality Boundaries provides a 2021 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online. The 2021 boundaries are provided by Michael Bauer Research GmbH. These were published in October 2022. A new layer will be published in 18 months. Other administrative boundaries for this country are also available: Country Provincia Departamento
Argentina administrative level 0-2 boundaries (COD-AB) dataset. The date that these administrative boundaries were established is unknown. This COD-AB has NOT been reviewed for accuracy and necessary changes in the last 12 months. Sourced from Instituto Geografico Nacional and UNHCR Vetting by Information Technology Outreach Services (ITOS) with funding from USAID. This COD-AB is suitable for database or GIS linkage to the Argentina COD-PS. No edge-matched (COD-EM) version of this COD-AB has yet been prepared. Please see the COD Portal. Administrative level 1 contains 24 feature(s). The normal administrative level 1 feature type is 'province'. Administrative level 2 contains 525 feature(s). The normal administrative level 2 feature type is 'department (partidos in Buenos Aries province, commun in Buenos Aries city)'. Recommended cartographic projection: South America Albers Equal Area Conic This metadata was last updated on January 17, 2025.
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.
**ADAM ID: **sm\_us6000si4j Magnitude 5.6 earthquake at 192.58 depth occurred on Mar 21 2026 68 km WNW of San Antonio de los Cobres, Argentina. The epicentre of the earthquake was located at latitude -24.0759 longitude -66.977. It impacted 911 people within 50km. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.
**ADAM ID: **sm\_us6000recz Magnitude 5.7 earthquake at 571.146 depth occurred on Oct 02 2025 29 km W of El Hoyo, Argentina. The epicentre of the earthquake was located at latitude -27.0636 longitude -63.5228. It impacted 7706 people within 50km. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.
**ADAM ID: **sm\_us7000qtpj Magnitude 5.9 earthquake at 176.483 depth occurred on Sep 04 2025 91 km WSW of San Antonio de los Cobres, Argentina. The epicentre of the earthquake was located at latitude -24.3833 longitude -67.2005. It impacted 675 people within 50km. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.
This dataset provides detailed information on road surfaces from OpenStreetMap (OSM), distinguishing between **paved** and **unpaved** roads across the region. Surface classification is derived using a hybrid deep learning approach. For methodological details, see: http://arxiv.org/abs/2410.19874 Recently, we also published a new country-level dataset based on PlanetScope satellite imagery with near-complete coverage of all arterial roads. It is available on HDX under the name Argentina **Planet** Road Surface. The corresponding paper is available at: https://arxiv.org/abs/2512.04092 Road Surface Statistics Approximately 1.3146 million km of roads are mapped in OSM in this region. Based on AI-derived estimates: - Paved roads: 0.2025 million km (15.4029%) - Unpaved roads: 0.6423 million km (48.8612%) About 0.4698 million km (35.7359%) of road surface information is missing in OSM. To reduce this gap, the Mapillary-derived road surface dataset provides an additional 0.0011 million km (0.2367%) of the missing surface information. Intended Use This dataset supports transportation planning, infrastructure analysis, climate emissions assessment, and GIS applications. AI Features - **pred_class**: Model-predicted surface class ("paved" or "unpaved") - **pred_label**: Binary label (0 = paved, 1 = unpaved) - **osm_surface_class**: Surface classification derived from OSM tags - **combined_surface_osm_priority**: Combined classification prioritizing OSM - **combined_surface_DL_priority**: Combined classification prioritizing DL prediction - **n_of_predictions_used**: Number of predictions used for estimation - **predicted_length**: Predicted length based on DL estimation (meters) - **DL_mean_timestamp**: Mean timestamp of predictions used OSM Attributes - **name** - **name:en** - **name:* (local language)** - **highway** - **surface** - **smoothness** - **width** - **lanes** - **oneway** - **bridge** - **layer** - **source** Urban Classification Attributes - **continent** - **country_iso_a2** - **urban** (0 = rural, 1 = urban) - **urban_area** - **osm_id** - **osm_type** Data Sources The dataset originates from OpenStreetMap (OSM) and is augmented with deep learning predictions based on Mapillary street-level imagery, combined with the GHSU Global Human Settlement Urban Layer 2019 and AFRICAPOLIS 2020 urban layer. More HeiGIT datasets: https://data.humdata.org/organization/heidelberg-institute-for-geoinformation-technology More information: https://heigit.org/ Contact: communications@heigit.org
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**ADAM ID: **sm\_us7000t36n Magnitude 5.4 earthquake at 197.18 depth occurred on Jul 24 2026 47 km WNW of San Antonio de los Cobres, Argentina. The epicentre of the earthquake was located at latitude -24.0121 longitude -66.7282. It impacted 1938 people within 50km. WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.
The Soil and Terrain database for Argentina primary data (version 1.0), at scale 1:1 million (SOTER_Argentina), was compiled of enhanced soil information within the framework of the FAO's program Land Degradation Assessment in Drylands (LADA). Primary soil and terrain data for Argentina were obtained from the SOTERLAC database (ver. 2) at scale 1:5 million. This update includes considerable changes in the GIS file, based on the SRTM-DEM derived surface information and on INTA's digital soil map (Instituto de Suelos), and only few changes of the attributes database. SOTER forms a part of the ongoing activities of ISRIC, FAO and UNEP to update the world's baseline information on natural resources.The project involved collaboration with national soil institutes from the countries in the region as well as individual experts.
AI-derived building footprint polygons for Argentina from Microsoft's Global ML Building Footprints, in 663 quadkey tiles of line-delimited GeoJSON, uploaded 2026-02-23.