Venezuela Earthquakes: Damage Assessment using Sentinel-1 radar data

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)

This dataset provides a rapid damage screening assessment for the 26 August 2026 Nepal flash flood and debris-flow event using 10-m Sentinel-1 Synthetic Aperture Radar (SAR) data. A post-event radar acquisition acquired on 28 August 2026 was compared with a one-year pre-event Sentinel-1 baseline to identify unusually strong changes in radar backscatter. The resulting damage proxy was spatially averaged using a 50 m neighbourhood and restricted to a built-environment search domain (residential and non-residential) defined from pre-event Overture building footprints and a 30 m surrounding buffer. A conservative operational threshold (K50 absolute z-score ≥ 1.60) was used to identify high-confidence likely-damage/change areas. The resulting layer was visually reviewed at post-processing level to remove identified artefacts. Across the assessed area, approximately 245.13 ha of high-confidence change were identified within approximately 4755 ha of assessed built-environment domain across 58,557 ha of assessed AOI. Admin-3 summary statistics are provided for 16 municipalities intersecting the analysis area. The product is a likely-damage / unusual-change proxy and not proof of structural or building-level damage. It is intended to support rapid geographic prioritisation, complementary imagery review and field assessment.

# 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)

# EOS-RS Damage Proxy Map: Ecuador, Earthquake, 19-26 Mar 2023, v0.8 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Damage Proxy Map (DPM) depicting areas that are likely damaged in southern Ecuador and northern Peru due to the M6.8 earthquake that occurred on 18 Mar 2023. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellite operated by the European Space Agency (ESA) before (7 Nov 2022 to 14 Mar 2023) and after (19-26 Mar 2023) the event. The image covers an area indicated by the large white polygon. Each pixel measures about 30 meters across. The colour variation from yellow to red indicates increasingly more significant surface change. Preliminary validation was done by comparing with media reports. This map could be used as a guidance to identify damaged areas, and may be less reliable over vegetated areas. Scattered pixels over vegetated areas may be false positives, and a lack of colored pixels over vegetated areas may not mean no damage. Some pixels may be due to changes in vegetation cover. The product contains modified Copernicus Sentinel data (2022-2023), processed by ESA and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS). **More map details and files:** **More map details and files:** **Credits:** Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), Contains modified Copernicus Sentinel data (2022-2023).

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.

satellite imagery by Vantor, acquired 2026-06-25 to 2026-06-26, 32.4 cm per pixel, published on OpenAerialMap.