Peru GIS data

geoBoundaries ADM1 boundaries for Peru: 26 units, representing 2008. Source: Wikimedia Commons.

uav imagery by Wikimedia Perú, acquired 2025-04-03 to 2025-04-03, 5.0 cm per pixel, published on OpenAerialMap.

geoBoundaries ADM0 boundaries for Peru: 1 units, representing 2008. Source: Wikimedia Commons.

uav imagery by Wikimedia Perú, acquired 2025-04-03 to 2025-04-03, 5.2 cm per pixel, published on OpenAerialMap.

uav imagery by Openstreetmap Perú, acquired 2025-04-14 to 2025-04-14, 5.3 cm per pixel, published on OpenAerialMap.

uav imagery by ASOAINTAM, acquired 2026-05-26 to 2026-05-26, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by COMPAÑIA INTERNACIONAL DEL CAFE SAC, acquired 2025-10-14 to 2025-10-14, 3.4 cm per pixel, published on OpenAerialMap.

uav imagery by Wikimedia Perú, acquired 2025-04-02 to 2025-04-02, 5.0 cm per pixel, published on OpenAerialMap.

satellite imagery by CONIDA, acquired 2025-08-05 to 2025-08-05, 70.0 cm per pixel, published on OpenAerialMap.

uav imagery by jjgarcia1906@gmail.com, acquired 2025-09-20 to 2025-09-20, 2.6 cm per pixel, published on OpenAerialMap.

uav imagery by ASOAINTAM, acquired 2026-05-26 to 2026-05-26, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by Openstreetmap Perú, acquired 2025-03-17 to 2025-03-17, 5.6 cm per pixel, published on OpenAerialMap.

uav imagery by Wikimedia Perú, acquired 2025-03-24 to 2025-03-24, 5.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Rodolfo Vargas Chile. GEÓGRAFO, acquired 2026-06-15 to 2026-06-21, 100 cm per pixel, published on OpenAerialMap.

uav imagery by Openstreetmap Perú, acquired 2025-03-22 to 2025-03-22, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by jjgarcia1906@gmail.com, acquired 2025-09-24 to 2025-09-24, 3.1 cm per pixel, published on OpenAerialMap.

Information collected from the Supervisory Agency for Private Investment in Telecommunications - OSIPTEL.

This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2. Produced and maintained since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database www.geoboundaries.org is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.

Archivo que contiene las construcciones mapeadas durante el mapatón Nacional de Perú CONIDA 2025.

Peru administrative level 0-3 boundaries (COD-AB) dataset version 01. This dataset is structured into 3 levels: - Admin 1: 25 - Admin 2: 196 - Admin 3: 1873 Dates associated with this dataset: - 30 October 2025: dataset reviewed for accuracy and completeness - 14 July 2020: valid for use by the humanitarian community - 24 July 2015: last edit to the dataset before publishing - 24 July 2015: boundaries created by the source Contributed by OCHA Latin America and the Caribbean (ROLAC). Quality assured, configured, and published by OCHA Field Information Services (FIS) and HDX. Part of the dataset: Global Subnational Administrative Boundaries

This dataset shows the list of operating health facilities. Attributes included: Name,Nature of Facility, Activities, Lat, Long

The International Best Track Archive for Climate Stewardship (IBTrACS) project is the most complete global collection of tropical cyclones available. It merges recent and historical tropical cyclone data from multiple agencies to create a unified, publicly available, best-track dataset that improves inter-agency comparisons. Fields available: SID: A unique storm identifier (SID) assigned by IBTrACS algorithm. ISO_TIME: Time of the observation in ISO format (YYYY-MM-DD hh:mm:ss) BASIN: Basin of the current storm position SUBBASIN: Sub-basin of the current storm position NATURE: Type of storm (a combination of the various types from the available sources) NUMBER: Number of the storm for the year (restarts at 1 for each year LAT: Mean position - latitude (a combination of the available positions) LON: Mean position - longitude (a combination of the available positions) WMO_WIND: Maximum sustained wind speed assigned by the responsible WMO agency WMO_PRES: Minimum central pressure assigned by the responsible WMO agency.

Financial services: banks, ATMs, post offices, money transfer agents, and microfinance branches tagged via `amenity`. Useful for financial-inclusion mapping, cash-distribution planning, and economic analysis. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity - Part of the country exports on HDX by HOT

Health facilities: hospitals, clinics, pharmacies, doctors, and dentists tagged via `amenity` or `healthcare`. Useful for service-access analysis, emergency response, and healthcare gap mapping. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity, healthcare - Part of the country exports on HDX by HOT

Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT

Cultural and historic places: museums, galleries, theatres, places of worship, monuments, and historic sites tagged via `tourism`, `amenity`, `historic`, or `heritage`. Useful for heritage protection, cultural mapping, and tourism context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: tourism, amenity, historic, heritage - Part of the country exports on HDX by HOT

Building footprints across the area: every feature tagged `building=*`, from residential homes to hospitals, schools, and places of worship. Useful for population estimation, damage assessment, and urban planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: building - Part of the country exports on HDX by HOT

Airports and aviation infrastructure: airports, heliports, helipads, runways, terminals, and emergency landing sites tagged via `aeroway`, `building`, or `emergency`. Useful for logistics, evacuation routing, and aerial-response planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: aeroway, building, emergency - Part of the country exports on HDX by HOT

Points of interest: public-facing amenities, shops, tourist attractions, and landmarks tagged via `amenity`, `shop`, `tourism`, or `man_made`. Useful for general POI reference, urban analysis, and basemap detail. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity, shop, tourism, man_made - Part of the country exports on HDX by HOT

Settlements and residential areas: named cities, towns, villages, suburbs, and residential land (`place=*` and `landuse=residential`). Useful for demographic context, settlement-level targeting, and population analysis. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: place, landuse - Part of the country exports on HDX by HOT

Railway lines and stations tagged `railway=*`: rail lines, tram tracks, and stations. Useful for transport accessibility analysis and basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: railway - Part of the country exports on HDX by HOT

Education facilities: schools, kindergartens, colleges, and universities tagged via `amenity` or `building`. Useful for school-access mapping, education planning, and resource allocation. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity, building - Part of the country exports on HDX by HOT

Road network across the area tagged `highway=*`: motorways, residential streets, service roads, footways, and trails. Useful for routing, accessibility analysis, and evacuation planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: highway - Part of the country exports on HDX by HOT

GLIDEnumbers are GLobal unique IDEntifiers for Disasters. Each disaster is registered in a record that contains a GLIDEnumber that uniquely identifies it and allows information to be interoperable across multiple disaster information sources, both structured and textual. Accessing disaster information can be a time consuming and laborious task. Not only is data scattered but frequently identification of the disaster can be confusing in countries with many disaster events and across borders. To address both of these issues, Asian Disaster Reduction Center (ADRC) proposed a globally common Unique ID code for disasters. Among the institutions using actively GLIDEnumbers are UN-OCHA (ReliefWeb, FSCC, HDX), UNDRR, UNDP, WMO, IFRC, FAO, the European Commission and the Centre for Research on the Epidemiology of Disasters (CRED), among many others. Country datasets are only produced for countries with at least one GLIDE event since 1 January 2022. The global dataset contains all events available from the GLIDE API, including those not assigned to a country.

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. Peru Provincia 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 Departamento Distrito

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. Peru Departamento 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 Distrito