Venezuela Bolivarian Republic of GIS data

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.

**ADAM ID: **FL-20250627-VEN-01 A flood occurred on Jun 27 2025 in Venezuela. It affected an estimated 57003 people and 100038 ha of cropland. 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.

Open and free data for assessing the human presence on the planet. The Global Human Settlement Layer (GHSL) project produces global spatial information, evidence-based analytics, and knowledge describing the human presence on the planet. The GHSL relies on the design and implementation of spatial data processing technologies that allow automatic data analytics and information extraction from large amounts of heterogeneous geospatial data including global, fine-scale satellite image data streams, census data, and crowd sourced or volunteered geographic information sources. The JRC, together with the Directorate-General for Regional and Urban Policy (DG REGIO) and Directorate-General for Defence Industry and Space (DG DEFIS) are working towards a regular and operational monitoring of global built-up and population based on the processing of Sentinel Earth Observation data produced by European Copernicus space program. In addition, the EU Agency for the Space Programme (EUSPA) undertakes activities related to user uptake of data, information and services.

This dataset provides a rapid experimental Sentinel-1-based damage assessment product for the broader impacted area from the 24 June 2026 Venezuelan earthquakes. It includes both the entire analyzed area of the SAR analysis and the Overture Maps building footprints identified as likely damaged. This SAR product estimates 81,437 likely damaged buildings across the analyzed impacted area. This preliminary damage proxy product is intended to support rapid screening and prioritization, targeting of follow-up assessment, triangulation with VHR optical and radar images, and other damage assessments and products.

A rapid assessment of building damage from the 24 June 2026 Venezuela earthquake (M7.5 mainshock, M7.2 foreshock), centered near San Felipe and Yumare in north-central Venezuela, with strong shaking along the central coast and into greater Caracas. A preliminary version (v0) of this product was released on 27 June 2026 via the NASA Disaster Response and Coordination System. This second iteration (v1) expands area coverage: post-event Sentinel-1 acquisitions that were not available at the first release (v0) filled the coverage gaps within the Copernicus EMS / USGS ShakeMap Modified Mercalli Intensity ≥ VI (strong-shaking) area, raising coverage of that hazard-provenanced, damage-onset zone to 100% and increasing the number of Overture building footprints under monitoring by 26.5% (from 2,133,587 to 2,699,969, an increase of 566,382 footprints). We extended the Copernicus EMSR884 area of interest to a latitude of approximately 11.04°N to include all areas with strong shaking. Using Sentinel-1 satellite radar coherent change detection, we estimate **69,431 buildings were likely damaged or destroyed**, as of the most recent analyzed satellite pass on 1 July 2026 (10:16 UTC). The assessment covers the entire area activated under Copernicus EMS activation EMSR884 (USGS event us6000t7zp) and is a preliminary product. These data reflect abrupt surface change consistent with damage — a damage indicator, not a confirmation of damage for any individual building. Each building footprint carries a confidence tier (**possible / probable / high_confidence**) instead of the numeric damage probability score used in the previous delivery. The confidence tier **does not represent individual building-level damage severity**. Instead, it represents how anomalous the post-earthquake interferometric coherence was compared to roughly one year prior to the earthquake. This is described in more detail in the README and slide deck PDFs included below. ## Coverage and dates - **Post-event:** Sentinel-1 swaths from 24 June 2026 (22:49 UTC) to 1 July 2026 (10:16 UTC), spanning eight post-earthquake acquisitions. - **Pre-event:** 260 reference coherence images — per-scene matched-baseline stacks — from 24 April 2025 to 23 June 2026. - **Monitored universe:** 2,699,969 Overture Maps Foundation building footprints; post-earthquake acquisitions cover 100% of the USGS ShakeMap MMI ≥ VI area. ## What's in this dataset - `EMSR884_damage_confidence_20260701_v1.geojson` / `.gpkg` — confidence-tier quick-look layer: the 123,633 buildings flagged at any confidence tier, with `overture_id`, `damage_confidence` (possible 54,202 / probable 43,511 / high_confidence 25,920), and the binary `damage` flag (1 = probable or high_confidence; the 69,431 buildings with `damage` = 1). - `EMSR884_analyzed_area_20260701_v1.geojson` / `.gpkg` — outline of where usable satellite coverage existed, so unassessed ground is not mistaken for undamaged. - `EMSR884_adm2_damage_pct_20260701_v1.gpkg` — percent of assessed buildings damaged, by second-level administrative unit. All layers are EPSG:4326 (WGS84) and open in QGIS, ArcGIS, geopandas, or R. ## README and Presentation We have included a detailed README file and PowerPoint presentation in both English and Spanish below. - `EMSR884_damage_20260701_v1_README.pdf` — detailed README: data description, methods, and agreement analyses (English). - `EMSR884_damage_20260701_v1_README_ES.pdf` — the same README in Spanish. - `EMSR884_damage_20260701_v1_slide_deck.pdf` — 32-slide briefing deck (English). - `EMSR884_damage_20260701_v1_slide_deck_ES.pdf` — the same deck in Spanish. Additionally, we have recorded a video presentation available in our mirrored directory. ## Citation Cite as: Damage analysis of Copernicus Sentinel-1 data by Corey Scher and Jamon Van Den Hoek, Oregon State University. Overture Maps Foundation building footprints. ## Mirror https://oregonstate.app.box.com/folder/394695539753?s=yrgtsbwmpqpajuhzioq0k13ihfluuneg ## NASA Disasters Portal Interactive Map https://gis.earthdata.nasa.gov/portal/apps/mapviewer/index.html?webmap=0c3d77dd5aae46e4829d9a282477615c

Venezuela (Bolivarian Republic of) administrative level 0-3 boundaries (COD-AB) dataset version 01. This dataset is structured into 3 levels: - Admin 1: 25 State - Admin 2: 336 Municipality - Admin 3: 1135 Parish (estados, municipios, parroquias) Dates associated with this dataset: - 17 January 2025: dataset reviewed for accuracy and completeness - 23 February 2021: valid for use by the humanitarian community - 07 August 2026: last edit to the dataset before publishing - 02 May 2018: boundaries created by the source Contributed by OCHA Venezuela. 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

Forward-looking analysis representing the most likely food security outcomes for the near term (April 2023 - May 2023) and medium term (June 2023 - September 2023) periods.

# Venezuela Earthquake Caracas: Damage Proxy Maps, Jun 2026 The **Earth Observatory of Singapore – Remote Sensing Lab (EOS-RS)** produced these damage proxy maps for Venezuela Earthquake Caracas (Jun 2026) from synthetic aperture radar (SAR) satellite images. Each map is a separate ZIP below with its GeoTIFF, a KMZ for Google Earth, the PNG figures and a text file describing how it was made and how to read it. ## Maps in this dataset - **EOS-RS Damage Proxy Map: La Guaira, Venezuela, Earthquakes, 25 June 2026, v0.8 ** - **EOS-RS Damage Proxy Map: Yuracuy Region, Venezuela, Earthquakes, 25 June 2026, v0.8 ** **More map details and files:** **Legal Disclaimer:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2026)

This dataset contains annual, 100m-resolution above ground biomass (AGB) estimates from CTrees, a NASA-affiliated forest-carbon monitoring organization, clipped to this country's boundary from CTrees' global AGB raster. Pixel values are stored as int16, scaled x10 relative to the true value in megagrams per hectare (Mg/ha) -- divide by 10 to get Mg/ha. See the caveats field and resource description for details on how this scale factor is recorded and why it isn't applied automatically by most tools.

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

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

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

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

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

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

Sea ports, harbours and ferry terminals. Useful for maritime logistics, supply-chain analysis, and coastal access 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: industrial=port, harbour, port, amenity=ferry_terminal, building=ferry_terminal - 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

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

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

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.

Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is a biophysical dimensionless quantity (its values range from 0/no absorption to 1/total absorption) used to assess the greenness and health of vegetation. FAPAR anomalies can be used as an indicator to detect and monitor the impacts of agricultural drought on the growth and productivity of vegetation. The data is presented in 10-day time composite of the Visible Infrared Imaging Radiometer Suite (VIIRS).

geoBoundaries ADM2 boundaries for Venezuela (Bolivarian Republic of): 335 units, representing 2015. Source: Efrain Porto Tapiquen Geografia, SIG y Estudios Ambientales. Municipios de Venezuela. Descargado desde tapiquen-sig.jimdo.com. Carlos Efrain Porto Tapiquen. Orogenesis Soluciones Geograficas. Porlamar Venezuela 2015. Distribucion Gratuita.

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. Venezuela Country Boundary 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. They are sourced from 'Municipios de Venezuela'. Descargado desde https://tapiquen-sig.jimdo.com, Carlos Efraín Porto Tapiquén. Orogénesis Soluciones Geográficas. Porlamar, Venezuela 2015. These were published in October 2022. A new layer will be published in 18 months. Other administrative boundaries for this country are also available: Estado

Microsoft AI for Good Lab ran their damage assessment AI models for the La Guiara Coastline - 26,142.

uav imagery by WebODM, acquired 2025-06-15 to 2025-06-15, 5.7 cm per pixel, published on OpenAerialMap.

202611_bmhd_cloud

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. Venezuela Estado 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. They are sourced from 'Municipios de Venezuela'. Descargado desde https://tapiquen-sig.jimdo.com, Carlos Efraín Porto Tapiquén. Orogénesis Soluciones Geográficas. Porlamar, Venezuela 2015. 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

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.

Microsoft AI for Good Lab ran their damage assessment AI models in East Catia La Mar covering 24,732 buildings.

Microsoft AI for Good Lab ran their damage assessment AI models in Catia La Mar.

uav imagery by WebODM, acquired 2025-06-06 to 2025-06-06, 5.0 cm per pixel, published on OpenAerialMap.

Microsoft AI for Good Lab ran their damage assessment AI models in La Guaria.

Venezuela - Shapefile

This spatial dataset provides the populated places in Venezuela.