Venezuela Bolivarian Republic of GIS data

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 La Guaira and Northeast of Valencia. 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.

satellite imagery by Vantor, acquired 2026-06-26 to 2026-06-26, 37.8 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-25 to 2026-06-25, 46.4 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-01-31 to 2026-01-31, 36.7 cm per pixel, published on OpenAerialMap.

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_202606_EARTHQUAKE_VENEZUELA/202611_blackmarble_brdf_cloud/ImageServer/WMSServer

uav imagery by WebODM, acquired 2025-06-12 to 2025-06-12, 5.3 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-03-19 to 2026-03-19, 40.4 cm per pixel, published on OpenAerialMap.

uav imagery by HOT, acquired 2026-04-29 to 2026-04-29, 5.1 cm per pixel, published on OpenAerialMap.

uav imagery by HOT, acquired 2026-04-29 to 2026-04-30, 5.1 cm per pixel, published on OpenAerialMap.

satellite imagery by HOT, acquired 2026-05-18 to 2026-05-18, 6.9 cm per pixel, published on OpenAerialMap.

satellite imagery by HOT, acquired 2026-05-27 to 2026-05-27, 5.5 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-25 to 2026-06-25, 46.3 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-25 to 2026-06-25, 35.8 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-26 to 2026-06-26, 34.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-27 to 2026-06-27, 34.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-28 to 2026-06-28, 59.7 cm per pixel, published on OpenAerialMap.

satellite imagery by Planet, acquired 2026-06-26 to 2026-06-26, 50.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-29 to 2026-06-29, 48.4 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-29 to 2026-06-29, 62.3 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-27 to 2026-06-27, 33.4 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-29 to 2026-06-29, 36.6 cm per pixel, published on OpenAerialMap.

Following the June 2026 earthquakes that struck the central coast of Venezuela, the Microsoft AI for Good Lab ran their building damage assessment AI models to map and classify the buildings affected by the earthquakes. The models were applied to satellite imagery captured on 25 and 26 June 2026, producing building footprints with predicted damage across the affected areas of Catia La Mar, La Guaira, and Caraballeda. For each assessed area, the collection provides a reference area map, a valid-area mask describing the extent of the analysis, and a GeoPackage of predicted building damage footprints. This collection mirrors the dataset published on the Humanitarian Data Exchange (HDX) by the Microsoft AI for Good Lab and made available under the Creative Commons Attribution 4.0 International (CC-BY-4.0) license. ## Methodology The Microsoft AI for Good Lab ran their damage assessment AI models on satellite images taken 25 and 26 June 2026 and have mapped out the affected buildings. ## Disclaimer This analysis represents a portion of the damage from the earthquake; other damage in the region is not included in this assessment. While these insights offer a valuable initial overview, they remain preliminary and require on-the-ground verification for a comprehensive understanding of the damage. ## Caveats Please note that the source imagery has orthorectification quality issues, which may cause building footprints to be misaligned with existing basemaps.

Dates of Image: 3 Pairs: 6/13/2026, 6/25/2026 6/17/2026, 6/29/2026 6/18/2026, 6/30/2026 Date of Next Image: Unknown Summary: Scientists working with Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory and California Institute of Technology, both in Pasadena, California, created this displacement map with measurements of the surface displacements, in the radar line-of-sight, caused by the recent major earthquake in Northern Venezuela (6/24/2026). The map was derived from synthetic aperture radar (SAR) images from the NASA-ISRO Synthetic Aperture Radar (NISAR) satellite. The team computed the interferometric difference (interferogram or interferometric SAR) between the post-event image acquired on 6/25/2026 a pre-event image acquired on 6/13/2026. The interferometric SAR (InSAR) measures the component of surface displacement in the line-of-sight (LOS) between the ground and the satellite, which is at an angle of about 40 degrees from the vertical and slightly south of due west. NOTE: The line-of-sight displacement (LOS) measurement is relative, and the dataset has not been calibrated to any ground location so there is a bias of the reference level, which is unknown. This data has not yet been validated. 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. Suggested Use: Unwrapped Interferogram (UNW): Red colors indicate increasing displacement towards the West, while the Blue areas indicate increasing displacement towards the East NOTE: Small vertical displacements have also occurred, but the primary surface displacements were in the horizontal plane. Satellite/Sensor: NASA-ISRO Synthetic Aperture Radar (NISAR) Resolution: 30 meters Credits: NASA-JPL/Caltech Team, NISAR Operations Science Team Esri REST Endpoint: https://gis.earthdata.nasa.gov/portal/rest/services/DISASTERS_202606_EARTHQUAKE_VENEZUELA/202611_nisar_LOSDisplacement/ImageServer WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202606_EARTHQUAKE_VENEZUELA/202611_nisar_LOSDisplacement/ImageServer/WMSServer

satellite imagery by Vantor, acquired 2026-06-27 to 2026-06-27, 86.3 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-03-11 to 2026-03-11, 35.9 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-04-07 to 2026-04-07, 42.2 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-25 to 2026-06-25, 34.8 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-25 to 2026-06-25, 41.8 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-27 to 2026-06-27, 78.2 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-26 to 2026-06-26, 35.8 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-30 to 2026-06-30, 56.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-27 to 2026-06-27, 63.4 cm per pixel, published on OpenAerialMap.

Summary: The product maps urban areas and building footprints in Caracas and La Guaira, Venezuela, that show substantial post-event spectral change. The damage likelihood combines increased visible brightness and increased SWIR1 reflectance, which may be associated with exposed concrete, rubble, dust, debris, roof disturbance, or collapsed structures. Approximately 46,000 buildings were identified as having a high damage likelihood based on Sentinel-2 observations and building-level screening. These estimates are intended for rapid situational awareness and should be validated using higher-resolution imagery or ground observations. For each building footprint, damage-score statistics were calculated using a 20 m scale:Mean damage score  Maximum damage score  75th percentile  90th percentile  Valid Sentinel-2 pixel count Dates of Images and Input Data:Sentinel-2 pre-event composite: 1 January 2026 – 23 June 2026 Sentinel-2 post-event composite: 24 June 2026 – 30 June 2026 Sentinel-2 collection: COPERNICUS/S2_SR_HARMONIZED ESA WorldCover: v200, built-up class 50 Building footprints: Google Open Buildings v3, confidence ≥ 0.75 Summary: This experimental product provides a rapid assessment of approximately 46,000 potentially damaged buildings following the June 2026 Venezuela earthquake using Sentinel-2 imagery and Google Open Buildings footprints. It is designed to support emergency response, situational awareness, and prioritization of areas for further investigation. Suggested Use:Rapid earthquake response and situational awareness Screening of possible building damage hotspots Prioritization of high-resolution optical or SAR image tasking Regional-scale validation against commercial imagery Emergency management planning support Product Description: Approximately 46,000 buildings were identified as having a high damage likelihood based on the experimental Sentinel-2 assessment. The product was generated from pre- and post-event Sentinel-2 median composites using cloud- and shadow-masked surface reflectance data. A damage score combining visible brightness and SWIR1 changes was computed and restricted to urban areas using ESA WorldCover. Google Open Buildings footprints were used to identify structures with elevated damage likelihood following the June 2026 Venezuela earthquake. The product is intended for rapid screening and emergency response applications.Symbology: building_damage_likelihood.tif  Damage Likelihood Color Recommended Label -0.05 Blue/white Low Probability 0.05 Yellow Moderate Probability 0.15 Red High Probability Satellite/Sensor/Resolution:• Satellite: Sentinel-2A / Sentinel-2B• Sensor: MultiSpectral Instrument (MSI)• Processing level: Level-2A Surface Reflectance• Bands used: B2, B3, B4, B11• Visible bands resolution: 10 m• SWIR1 resolution: 20 m• Building-summary scale: 20 m• Temporal Baseline: 5 days Caveats and Limitations:Sentinel-2 cannot reliably confirm individual building damage at 10–20 m resolution. Building polygons are used only to summarize damage-score signals, not to directly observe structural collapse. Spectral changes may be caused by rubble, dust, exposed soil, roof material change, shadow, moisture, cloud contamination, or other non-damage factors. ESA WorldCover urban masking reduces but does not eliminate false positives. Google Open Buildings may contain missing, outdated, or inaccurate footprints. This product should be treated as an experimental damage-likelihood layer, not a definitive building damage inventory. Validation using high-resolution commercial optical imagery, SAR coherence/backscatter products, or ground reports is strongly recommended. File names: high_damage_buildings.kml — building polygons with high possible damage  building_footprints.kml — Buildings footprints intersecting the study area  building_damage_likelihood.tif — Sentinel-2 optical damage likelihood raster S2_Pre_RGB.tif — pre-event Sentinel-2 RGB composite S2_Post_RGB.tif — post-event Sentinel-2 RGB composite Esri REST Endpoint: See Layers below. Credits Khuong Tran (Khuong.tran@nasa.gov)

satellite imagery by Vantor, acquired 2026-06-27 to 2026-06-27, 43.4 cm per pixel, published on OpenAerialMap.

uav imagery by Amilcar Araujo, acquired 2026-04-30 to 2026-04-30, 5.1 cm per pixel, published on OpenAerialMap.

Date(s) of Images: Post-Event: 6/26/2026 Summary: Satellogic’s operates a commercial constellation of satellites and sensors that offers 4 band (R,G, B and NIR) acquisitions. Normalized Differential Vegetation Index (NDVI) maps are produced by converting pixel values to NDVI = (Red – NIR)/(Red + NIR), NIR indicates the near infrared band. The dynamically generated Normalized Difference Vegetation Index (NDVI) layer is an index for quantifying green vegetation. It reflects the state of vegetation health based on how vegetation reflects light at certain wavelengths. Dark green colors are areas with a lot of green leaf growth which indicates the presence of chlorophyll. Chlorophyll reflects more infrared light and less visible light. Areas with some green leaf growth are in light greens, and areas with little to no vegetation growth are even lighter greens. Resolution: 0.5 m to 1 m depending on generation of sensor used and viewing angle. Credits: NASA Disasters Program, Satellogic. For derived products: “Includes copyrighted material of Satellogic. All rights reserved.” This work utilized data made available through the NASA Commercial Satellite Data Acquisition (CSDA) program."