Imagery and land cover data

This Collection provides Sentinel-5P Level-2 CO products, which contains high-resolution imagery of carbon monoxide concentrations.

The Sentinel-6 P4 Level 2 Non Time Critical (NTC) product delivers the highest quality ocean surface measurements, including sea surface height, wind speed, and wave height, designed for climate research and long-term monitoring. The data are processed using the most up-to-date algorithms and auxiliary information, organized by full satellite passes, and delivered within 60 days of acquisition. The product is provided in NetCDF format and is subject to regular reprocessing to maintain consistency with evolving processing standards.

The Sentinel-6 P4 Level 1B Short Time Critical (STC) product provides intermediate-latency ocean surface data, including sea surface height, wind speed, and wave height. It is tailored for oceanographic modeling and data assimilation purposes. Data are organized by full satellite passes (pole-to-pole) and are typically delivered within 36 hours of acquisition. The product is provided in NetCDF format and ensures consistent quality for near-operational applications.

satellite imagery by Planet, acquired 2026-08-25 to 2026-08-25, 300 cm per pixel, published on OpenAerialMap.

The Sentinel-6 P4 Level 1B Near Real-Time (NRT) product provides low-latency, operational-quality ocean surface data, including sea surface height, wind speed, and wave height. The data are segmented into 10-minute granules per ground station pass and delivered within three hours of acquisition. The product is provided in NetCDF and BUFR formats.

uav imagery by WebODM, acquired 2026-01-10 to 2026-01-10, 5.6 cm per pixel, published on OpenAerialMap.

This Collection provides Sentinel-5P Level-2 NP BD3 products, which contains information on cloud and scene homogeneity.

This Collection provides Sentinel-5P Level-2 NP BD3 products, which contains information on cloud and scene homogeneity.

uav imagery by Luka Koena, acquired 2026-01-24 to 2026-01-25, 1.0 cm per pixel, published on OpenAerialMap.

uav imagery by NYenvironcom, acquired 2026-02-22 to 2026-02-22, 3.7 cm per pixel, published on OpenAerialMap.

uav imagery by evd, acquired 2025-05-27 to 2025-05-28, 5.3 cm per pixel, published on OpenAerialMap.

uav imagery by Aleksander Gołaszewski, acquired 2026-06-22 to 2026-06-22, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by GisBudva, acquired 2026-06-11 to 2026-06-11, 2.0 cm per pixel, published on OpenAerialMap.

uav imagery by Geo-Planning for Advanced Development (GPAD), acquired 2026-06-02 to 2026-06-03, 3.5 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2025-11-30 to 2025-11-30, 30.5 cm per pixel, published on OpenAerialMap.

uav imagery by Beautify Boracay, acquired 2026-04-10 to 2026-04-11, 2.0 cm per pixel, published on OpenAerialMap.

uav imagery by Help.NGO, acquired 2025-07-13 to 2025-07-14, 4.9 cm per pixel, published on OpenAerialMap.

uav imagery by HOT, acquired 2025-06-04 to 2025-06-08, 8.5 cm per pixel, published on OpenAerialMap.

ArcGIS Image ServiceTime Interval: Full Climatology With Hourly Timesteps Version: 1 Spatial Resolution: 3 km Time Extent: 2004 to 2024 (With 24 Hours) Projection: GCS WGS84 Extent: Regional | Europe Other Formats: OGC WMS, OGC WCS, REST CollectionThis collection contains European Anvil Cloud Days per Year detection climatological diurnal statistics averaged over 2004-2024 Satellite Mapping and Analysis of Severe Hailstorms (SMASH) ProjectThis Hailstorm research project seeks to address knowledge gaps in the severe hail climatology using regional to global scale satellite observations and provides mechanisms to explore related datasets. For questions/issues please contact: kristopher.m.bedka@nasa.gov

uav imagery by name, acquired 2026-05-16 to 2026-05-17, 1.7 cm per pixel, published on OpenAerialMap.

uav imagery by Nikolay Nowitsky, acquired 2025-06-24 to 2025-06-25, 4.5 cm per pixel, published on OpenAerialMap.

uav imagery by INGD, acquired 2025-09-21 to 2025-12-12, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by Rabi Shrestha, acquired 2026-03-09 to 2026-03-09, 1.3 cm per pixel, published on OpenAerialMap.

uav imagery by Geo-Planning for Advanced Development (GPAD), acquired 2026-06-15 to 2026-06-16, 3.5 cm per pixel, published on OpenAerialMap.

aircraft imagery by Centro de Estudios Pomote, acquired 2026-02-21 to 2026-02-21, 5.0 cm per pixel, published on OpenAerialMap.

aircraft imagery by ?, acquired 2025-08-19 to 2025-08-19, 4.9 cm per pixel, published on OpenAerialMap.

uav imagery by Dronexx, acquired 2025-03-31 to 2025-03-31, 2.0 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2026-01-09 to 2026-01-10, 5.8 cm per pixel, published on OpenAerialMap.

uav imagery by Justin Forest, acquired 2025-10-05 to 2025-10-06, 5.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Asbury, acquired 2026-06-01 to 2026-06-02, 27.9 cm per pixel, published on OpenAerialMap.

Dates of Images: Post-Event: July 4, 2026 Pre-Event: June 19, 2026 Date of Next Image: Unknown Summary: 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. NDVI change was created by subtracting the cloud-masked post-event NDVI from the cloud-masked pre-event NDVI to show areas of potentially impacted vegetation as negative values (darker shades) and healthy/unimpacted vegetation in positive values (lighter shades). NDVI change can give insights to impacts from an event (like the scouring of vegetation from the riverbeds) but can also show changes in unrelated areas like the clearing of agriculture fields. This layer is a binary NDVI change polygon (threshold of areas where NDVI decreased by -0.25 or more) for June 19, 2026 as compared to July 4, 2026. Suggested Use: NDVI change: Commonly used to distinguish healthy/active vegetation (positive values) from potentially unhealthy/impacted vegetation (negative values). This map shows a binary flag where NDVI decreased. Satellite/Sensor: MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites Resolution: 10 meters Credits: NASA/MSFC, USGS, ESA Copernicus Esri REST Endpoint: See URL section on right side of page

satellite imagery by Rodolfo Vargas Chile. GEÓGRAFO, acquired 2025-10-15 to 2025-10-15, 50.0 cm per pixel, published on OpenAerialMap.

uav imagery by Nowitsky Nikolay, acquired 2025-05-31 to 2025-05-31, 4.1 cm per pixel, published on OpenAerialMap.

uav imagery by Rodolfo Vargas Chile. GEÓGRAFO, acquired 2025-10-28 to 2025-11-01, 7.0 cm per pixel, published on OpenAerialMap.

uav imagery by Help.NGO, ADMU, acquired 2026-07-19 to 2026-07-20, 3.8 cm per pixel, published on OpenAerialMap.

Date of Image: 2/10/2023 Date of Next Image: Unknown Summary: 2/10/2023 (ARIA, Copernicus Sentinel-1) The Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory and California Institute of Technology in Southern California created this Damage Proxy Map (DPM) depicting areas that are likely damaged by the large earthquakes (Feb. 06, 2023) in Turkiye (Turkey) and Syria. The map was derived from synthetic aperture radar (SAR) images on Feb. 10, 2023 by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA). The pre-event images were taken from Sep. 19, 2022 to Jan. 29, 2022). Suggested Use: Standard Version: The color variation from pale yellow to red indicates increasingly more significant surface change (drop in radar reflection coherence). Preliminary validation was done by comparing with high-resolution optical imagery and media reports. NOTE: This damage proxy map could be used as a guidance to identify damaged areas, and may be less reliable over vegetated and mountainous areas. Scattered pixels over vegetated areas may be false positives, and a lack of colored pixels over vegetated areas may not mean no damage. Satellite/Sensor: Copernicus Sentinel-1 Synthetic Aperture Radar (SAR) Resolution: 30 meters Credits: Sentinel-1 data were accessed through the Copernicus Open Hub and the Alaska Satellite Facility server. The product contains modified Copernicus Sentinel data (2022-2023), processed by ESA and analyzed by the NASA-JPL/Caltech ARIA team in collaboration with Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS). Part of the funding was provided by NASA's Earth Applied Sciences Disasters Program. Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=4e684f9ad7e74e5d991cb011ca0d07ad WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202302_EARTHQUAKE_TURKIYE/2302_opera_dpm/ImageServer/WMSServer Data Download: https://aria-share.jpl.nasa.gov/20230206_Turkey_EQ/DPM/