Venezuela Bolivarian Republic of GIS data

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\_us6000rcrj Magnitude 5.8 earthquake at 10.0 depth occurred on Sep 25 2025 26km NW of Sabana Grande. The epicentre of the earthquake was located at latitude 9.894 longitude -70.6699. It impacted 244499 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 Venezuela (Bolivarian Republic of) **Planet** Road Surface. The corresponding paper is available at: https://arxiv.org/abs/2512.04092 Road Surface Statistics Approximately 0.2997 million km of roads are mapped in OSM in this region. Based on AI-derived estimates: - Paved roads: 0.0451 million km (15.0369%) - Unpaved roads: 0.0687 million km (22.9079%) About 0.186 million km (62.0553%) of road surface information is missing in OSM. To reduce this gap, the Mapillary-derived road surface dataset provides an additional 0.0 million km (0.0229%) 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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Building footprints for the Caracas area of Venezuela (bounding box 67.09W-66.65W, 10.28N-10.64N), Sourced from Overture Maps (buildings theme: OpenStreetMap, Microsoft, Google, Esri). Event: M 7.5 Earthquake, west of Caracas. - Source: Overture Maps - Part of HOT disaster response exports on HDX by HOT

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Location of hazardous facilities in the affected areas of the earthquake of 24 June 2026 in Venezuela.

**UNOSAT code: EQ20260625VEN, GDACS ID: 1548377** This application provides geospatial information on satellite based-assessments related with the 7.2 & 7.5 magnitude earthquakes sequence in Venezuela of 24 June 2026. Important note: The boundaries and names shown, and the designations used on this map do not imply official endorsement or acceptance by the United Nations. The United Nations Satellite Centre -UNOSAT is not responsible for the misuse or misrepresentation of the map.

We have assessed primary and secondary roads for signs of road blockages in the *La Guaira, Districto Capital, Yaracuy and Carabobo* regions of Venezuela. The latest updated data, uses imagery dated **15th August 2026**. The data is held in a shapefile format using the WGS 84 EPSG: 4326 projection. You can find the Planetary Response Network Venezeulan Earthquake 2026 project we ran here. This is crowd sourced data.

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

Date of Image: Pre-Event: May 2026 (composite) Post-Event: June 26, 2026 Date of Next Image: Unknown Summary: These Black Marble High-Definition (BMHD) images were created by the NASA Black Marble Science team, with directed funding the NASA-Google Partnership program. The images map the impact of the major flooding in Rio Grande do Sul on electric grids in Porto Alegre. The baseline image (before the floods) was from May 2026, a cloud-free, moon-free composite, and the “after" image was from June 26, 2026. There is a layer to display where clouds are present in the "after" images. This comparison between the two images is meant as a visual assessment of outage impacts from the flooding to aid various partners who are working to deliver emergency aids to local communities. Power outage maps like these help disaster response efforts in the short-term as well as long-term monitoring during the crucial stages of disaster recovery. Suggested Use: NOTE: Black Marble HD images are downscaled from NASA’s Black Marble nighttime lights product (VNP46), and as such are a “modelled” or “best guess” estimate of how lights are distributed at a 30m resolution. These images should be used for visualization purposes, not for quantitative analysis. The image is in inferno color scale. Yellow represents presence of more light; dark blue less lights. Satellite/Sensor: The primary data source, NASA’s Black Marble nighttime lights product suite (VNP46), utilized to generate this product is derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP) along with high resolution base layers - Landsat derived normalized index products (NDVI and NDWI) and OpenStreetMap (OSM) derived road layer Resolution: Scaled resolution of 30 meters Credits: NASA Black Marble Science team Please cite the following two references when using this data: Román MO, Stokes EC, Shrestha R, Wang Z, Schultz L, Carlo EA, Sun Q, Bell J, Molthan A, Kalb V, Ji C. Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PloS one. 2019 Jun 28;14(6):e0218883. Román MO, Wang Z, Sun Q, Kalb V, Miller SD, Molthan A, Schultz L, Bell J, Stokes EC, Pandey B, Seto KC. NASA's Black Marble nighttime lights product suite. Remote Sensing of Environment. 2018 Jun 1;210:113-43. Point of Contact: Ranjay Shrestha NASA Goddard Space Flight Center E-mail: ranjay.m.shrestha@nasa.gov Additional Links: NASA’s Black Marble Product Suite Román, M.O. et al. (2019) Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PLoS One, 14 (6). Román, M.O. et al. (2018) NASA’s Black Marble nighttime lights product suite. Remote Sensing of Environment. 210, 113–143. Esri REST Endpoint: See URL section on right side of page. WMS Endpoint: https://gis.earthdata.nasa.gov/gis05/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_bmhd/ImageServer/WMSServer

Date of Images: Post-Event: 6/26/2026, 6/27/2026 Pre-Event: May 2026 Summary: These Black Marble Day-Night Band (BRDF-Corrected) images were created by the NASA Black Marble Science team. The images are corrected for atmospheric, terrain, lunar BRDF, and straylight effects, and directly measures light intensity on the ground in units of nanowatts/(steradian centimeter squared). The images are scaled from 0 - 30. The baseline image is from September 2025, generated from all daily atmospheric and lunar-corrected data from that month. There is a layer to display where clouds are present. This comparison between the images is meant as a visual assessment of outage impacts to aid various partners who are working to deliver emergency aids to local communities. Power outage maps like these help disaster response efforts in the short-term as well as long-term monitoring during the crucial stages of disaster recovery. Suggested Use: NASA's Black Marble Nighttime Light product suite is a state-of-the-art daily global collection of standard products for monitoring nighttime lights (NTL). Utilizing the Visible Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) aboard the Suomi-NPP, NOAA-20, and NOAA-21 satellites. The image is in inferno color scale. Yellow represents presence of more light; dark blue less lights. Observations may be obscured by total or partial cloud cover. Other factors such as snow reflectance, moon phase, wildfires, and wildfire smoke may distort light radiance and require further analysis when assessing power outages. Satellite/Sensor: Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP), NOAA-20, and NOAA-21 Resolution: 15 arc-seconds (~500 meters) Credits: NASA Black Marble Science team Please cite the following two references when using this data: Román MO, Stokes EC, Shrestha R, Wang Z, Schultz L, Carlo EA, Sun Q, Bell J, Molthan A, Kalb V, Ji C. Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PloS one. 2019 Jun 28;14(6):e0218883. Román MO, Wang Z, Sun Q, Kalb V, Miller SD, Molthan A, Schultz L, Bell J, Stokes EC, Pandey B, Seto KC. NASA's Black Marble nighttime lights product suite. Remote Sensing of Environment. 2018 Jun 1;210:113-43. Point of Contact: Ranjay Shrestha NASA Goddard Space Flight Center E-mail: ranjay.m.shrestha@nasa.gov Additional Links: NASA’s Black Marble Product Suite Román, M.O. et al. (2019) Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PLoS One, 14 (6). Román, M.O. et al. (2018) NASA’s Black Marble nighttime lights product suite. Remote Sensing of Environment. 210, 113–143. Service URL: https://gis.earthdata.nasa.gov/portal/rest/services/DISASTERS_202606_EARTHQUAKE_VENEZUELA/202611_brdf/ImageServer WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202606_EARTHQUAKE_VENEZUELA/202611_brdf/ImageServer/WMSServer

Note: users may need to zoom into the area of interest to more clearly see the data as it is high resolution. The areas of coverage include west of Caracas. Dates of Images: Post-Event: 6/25/2026 Summary: Legion is a high-resolution satellite constellation operated by Vantor and allows for multiple viewing opportunities of any location on Earth daily. Legion collects 8-band imagery which allows for multiple derived products to be produced. The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument. Resolution: ~0.4 m Credits: NASA Disasters Program, Processing from MSFC, Vantor. For derived products: “Includes copyrighted material of Vantor. All rights reserved.” This work utilized data made available through the NASA Commercial Satellite Data Acquisition (CSDA) program. REST Endpoint: See URL Section on right side of page WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202606_EARTHQUAKE_VENEZUELA/202611_VANTOR_CARACAS/ImageServer/WMSServer

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

Displacement maps from Sentinel-1 ascending track 033, acquired on 2026/06/25 Dates of Images: June 24, 2026; June 25, 2026 Summary: EARTHQUAKE OVERVIEW (Source: USGS): On June 24, 2026, northwestern and central Venezuela was struck by two large strike-slip earthquakes occurring just 39 seconds apart: Foreshock: Magnitude 7.2 at 22:04:33 (UTC), located 23 km SE of Yumare, Venezuela Mainshock: Magnitude 7.5 at 22:05:11 (UTC), located 28 km SE of Yumare, Venezuela (10.435°N, 68.472°W) Scientists working with the Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory and California Institute of Technology, both in Pasadena, California, created these displacement maps with measurements of surface displacements caused by the earthquake sequence. The maps were derived from synthetic aperture radar (SAR) images from the Copernicus Sentinel-1 satellites, operated by the European Space Agency (ESA). The team computed the phase difference between a post-event image acquired on June 25, 2026 (reference scene) with a pre-event image acquired on June 18, 2026 (secondary scene), on Sentinel-1 ascending (satellite moving north) track 033. Interferometric Synthetic Aperture Radar (InSAR) measures ground movement toward or away from the satellite. Sentinel-1 views the ground from the side at about 40° from vertical. On ascending passes, it travels slightly west of north (heading ≈ 348° or −12°) and looks to the east. On descending passes, it travels slightly southwest (heading ≈ 192°) and looks to the west. The full dataset covers an area centered on the earthquake epicenter. Each pixel measures approximately 30 meters across. Suggested Use: Line-of-Sight Displacement (Venezuela_S1_A033_20260618_20260625_UNW.tif): Unwrapped phase data converted to metric displacement along the radar line-of-sight. Positive values (blue) indicate ground movement towards from the satellite (uplift and/or westward motion), while negative values (red) indicate movement away from the satellite (subsidence and/or eastward motion). Units: meters. The dataset has been re-referenced to a stable point at coordinates (-68.5435°, 10.9696°). Areas of low coherence and water bodies have been masked. Wrapped Phase (Venezuela_S1_A033_20260618_20260625_WRP.tif): Wrapped phase map showing relative ground deformation where each "fringe" or complete color cycle represents approximately 2.8 cm of displacement along the line-of-sight (half the Sentinel-1 C-band wavelength of 5.56 cm). The color progression from (outward to inward) red, orange, yellow, green, and blue indicates ground is moving away from the satellite, blue, green,yellow, orange, and red means ground is moving towards the satellite. This visualization is useful for identifying the spatial pattern and magnitude of deformation. Range Offset (Venezuela_S1_A033_20260618_20260625_RNG.tif): Across-track (range direction) pixel offsets measured through amplitude cross-correlation. This represents ground displacement perpendicular to the satellite flight path, predominantly capturing east-west motion. Positive values (blue) indicate westward movement, negative values (red) indicate eastward movement. Units: meters. Water bodies and areas outside the valid data frame have been masked. Interferometric Coherence (Venezuela_S1_A033_20260618_20260625_COH.tif): Measures the similarity of the radar phase between the two SAR acquisitions, indicating the reliability of the interferometric phase used to estimate ground displacement. Values range from 0 (decorrelated, unreliable) to 1 (highly correlated, reliable). Data Sources and Satellite Specifications: Water masking: ESA World Cover 2021 land cover dataset was used to mask permanent water bodies Orbit direction: Ascending (A) - satellite moving north Track number: 033 Wavelength: 5.56 cm (C-band) Spatial resolution: 30 meters Reference point: -68.5435°E, 10.9696°N Temporal baseline: 7 days (June 18-25, 2026) Caveats: The InSAR ground displacement results posted here are preliminary results, primarily intended to aid field response and provide rapid assessment of earthquake-induced surface deformation. These preliminary products may or may not be suitable for detailed scientific analysis without further validation. This displacement map should be used as guidance to identify areas of significant ground displacement, and may be less reliable over snow-covered and vegetated areas, steep terrain, or regions that experienced surface changes between acquisitions. The Sentinel-1 data products contain modified Copernicus Sentinel data (2026), processed by the European Space Agency and analyzed at the NASA Jet Propulsion Laboratory. For more information about ARIA, visit: http://aria.jpl.nasa.gov Credits: Sentinel-1 data were accessed through the Copernicus Open Hub and the Alaska Satellite Facility server. The product contains modified Copernicus Sentinel data (2026), processed by the European Space Agency and analyzed by the NASA-JPL/Caltech ARIA and OPERA team. The products are produced as part of the OPERA project, which is funded by NASA to address remote sensing needs identified by the Satellite Needs Working Group, and managed by NASA's Jet Propulsion Laboratory. Grace Bato, Cole Speed, Eric Fielding Esri REST Endpoint: See URL to the right

Dates of Images Post-Event: 6/26/2026, 6/27/2026, 2/29/2026 Summary Skysat is a high-resolution satellite constellation operated by Planet and allows for multiple viewing opportunities of any location on Earth daily. Skysat collects 4-band imagery which allows for multiple derived products to be produced. The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument. The Color Infrared composite is created using the near-infrared, red, and green channels. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue. Resolution ~1 m Credits NASA Disasters Program, Processing from MSFC, Planet. For derived products: “Includes copyrighted material of Skysat. All rights reserved.” This work utilized data made available through the NASA Commercial Satellite Data Acquisition (CSDA) program.

Dates of Images: Post-Event: 06/25/2026 Pre-Event: 04/07/2026-06/13/2026 (8 images total) Summary: The NASA GSFC landslides team produced this landslide proxy heatmap from Sentinel-1 imagery. Potential landslides were detected by calculating the change in the backscatter coefficient before and after the triggering event using the log ratio approach (Iratio). The Iratio is generated by subtracting median pre- and post-event Radiometrically Terrain Corrected (RTC) gamma0 backscatter in decibel scale at 10 m resolution obtained from the Alaska Sar Facility’s Hybrid Pluggable Processing Pipeline (HyP3). The likely landslide pixels are identified using 99th percentile Iratio threshold considering areas greater than 10-degree in slope and not affected by radar shadow and layover effects. A heatmap is generated using identified landslide pixels for visualization ease. Pre-event imagery = median imagery generated using images from 04/07/2026-06/13/2026 (8 images total) Post-event imagery = 06/25/2026 This map should be used as a guide to identify areas likely affected by landslides. This is a rapid response product. We have not done any form of manual verification or corrections to remove false positives. Suggested Use: The red and yellow areas indicate potential zones of dense landsliding. False positives related to natural and human-made ground surface change, including but not limited to deformation from mining, construction, deforestation, agriculture, flooding, snow cover, and changes in reservoir water levels can also be within the red and yellow areas. Satellite/Sensor/Resolution: Synthetic Aperture Radar on European Space Agency's (ESA) Copernicus Sentinel-1 satellite, 10 meters Credits: NASA GSFC landslides team, Copernicus Sentinel-1 data Citation: Handwerger AL, Huang M-H, Jones SY, Amatya P, Kerner HR, Kirschbaum DB. 2022. Generating landslide density heatmaps for rapid detection using open-access satellite radar data in Google Earth Engine. Nat. Hazards Earth Syst. Sci. Copernicus Publications, 22(3): 753–773. https://doi.org/10.5194/nhess-22-753-2022. Esri REST Endpoint: See URL to the right. WMS Endpoint: See Sublayers.

Vantor imagery of Caracas, Venezuela. Published by gwlayne.

Date of Images: Post-Event: 6/26/2026, 6/27/2026 Pre-Event: May 2026 Summary: These Black Marble Day-Night Band (BRDF-Corrected) images were created by the NASA Black Marble Science team. The images are corrected for atmospheric, terrain, lunar BRDF, and straylight effects, and directly measures light intensity on the ground in units of nanowatts/(steradian centimeter squared). The images are scaled from 0 - 30. The baseline image is from September 2025, generated from all daily atmospheric and lunar-corrected data from that month. There is a layer to display where clouds are present. This comparison between the images is meant as a visual assessment of outage impacts to aid various partners who are working to deliver emergency aids to local communities. Power outage maps like these help disaster response efforts in the short-term as well as long-term monitoring during the crucial stages of disaster recovery. Suggested Use: NASA's Black Marble Nighttime Light product suite is a state-of-the-art daily global collection of standard products for monitoring nighttime lights (NTL). Utilizing the Visible Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) aboard the Suomi-NPP, NOAA-20, and NOAA-21 satellites. The image is in inferno color scale. Yellow represents presence of more light; dark blue less lights. Observations may be obscured by total or partial cloud cover. Other factors such as snow reflectance, moon phase, wildfires, and wildfire smoke may distort light radiance and require further analysis when assessing power outages. Satellite/Sensor: Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP), NOAA-20, and NOAA-21 Resolution: 15 arc-seconds (~500 meters) Credits: NASA Black Marble Science team Please cite the following two references when using this data: Román MO, Stokes EC, Shrestha R, Wang Z, Schultz L, Carlo EA, Sun Q, Bell J, Molthan A, Kalb V, Ji C. Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PloS one. 2019 Jun 28;14(6):e0218883. Román MO, Wang Z, Sun Q, Kalb V, Miller SD, Molthan A, Schultz L, Bell J, Stokes EC, Pandey B, Seto KC. NASA's Black Marble nighttime lights product suite. Remote Sensing of Environment. 2018 Jun 1;210:113-43. Point of Contact: Ranjay Shrestha NASA Goddard Space Flight Center E-mail: ranjay.m.shrestha@nasa.gov Additional Links: NASA’s Black Marble Product Suite Román, M.O. et al. (2019) Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PLoS One, 14 (6). Román, M.O. et al. (2018) NASA’s Black Marble nighttime lights product suite. Remote Sensing of Environment. 210, 113–143. Service URL: See REST Endpoint on the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2601_201809_HURRICANE_FLORENCE/ex2601_blackmarble_brdf/ImageServer/WMSServer