Global 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.

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

uav imagery by WebODM, acquired 2026-01-07 to 2026-01-07, 6.4 cm per pixel, published on OpenAerialMap.

uav imagery by OC Aerial, acquired 2025-06-23 to 2025-06-24, 1.8 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2026-01-04 to 2026-01-04, 5.5 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2026-01-05 to 2026-01-05, 5.6 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2026-01-18 to 2026-01-18, 5.8 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2026-01-19 to 2026-01-19, 5.8 cm per pixel, published on OpenAerialMap.

uav imagery by Leo Vanualailai, acquired 2026-07-26 to 2026-07-27, 3.0 cm per pixel, published on OpenAerialMap.

This Collection provides Sentinel-5P Level-1 RA BD5 products, which contains Earth radiance spectra for spectral band 5.

This Collection provides Sentinel-5P Level-2 CH4 products, which contains high-resolution imagery of methane concentrations.

This Collection provides Sentinel-5P Level-2 AER LH products, which contains high-resolution imagery of the UV Aerosol Index (UVAI), also called the Absorbing Layer Height (ALH).

uav imagery by Luka Koens, acquired 2026-07-31 to 2026-07-31, 1.9 cm per pixel, published on OpenAerialMap.

__Note__: _A new version of this item is available for your use. This mature version of the map remains available for use in existing applications. This item will be retired in December 2024. There is 2020 data available in the newer 9-class dataset._ Global estimates of 10-class land use/land cover (LULC) for 2020, derived from ESA Sentinel-2 imagery at 10m resolution. This dataset was generated by Impact Observatory, who used billions of human-labeled pixels (curated by the National Geographic Society) to train a deep learning model for land classification. The global map was produced by applying this model to the relevant yearly Sentinel-2 scenes on the Planetary Computer. This dataset is also available on the ArcGIS Living Atlas of the World.

Level 1 thermal inrared data (bands 10 and 11) from Landat 8 and Landsat 9.

This Collection provides Sentinel-5P Level-1 RA BD1 products, which contains Earth radiance spectra for spectral band 1.

This Collection provides Sentinel-5P Level-1 RA BD1 products, which contains Earth radiance spectra for spectral band 1.

This Collection provides Sentinel-5P Level-2 CH4 products, which contains high-resolution imagery of methane concentrations.

The Copernicus Sentinel-3 SLSTR RBT products provide global brightness temperatures and radiances with a spatial resolution of 500 meters for reflectance bands and 1 kilometer for thermal infrared bands, useful for environmental monitoring and climate studies.

This Collection provides Sentinel-5P Level-2 NO2 products, which contains high-resolution imagery of nitrogen dioxide concentrations.

This Collection provides Sentinel-5P Level-2 AER LH products, which contains high-resolution imagery of the UV Aerosol Index (UVAI), also called the Absorbing Layer Height (ALH).

The Harmonized Landsat and Sentinel-2 (HLS) project takes input data from the joint NASA/USGS Landsat 8 and Landsat 9 satellites and the European Space Agency's Sentinel-2A, Sentinel-2B, and Sentinel-2C satellites to generate a harmonized, analysis-ready surface reflectance data product with observations every 1.6 days.  Intended Use: The frequent revisit times of HLS allow for time series of land surface applications at the field/plot scale, which supports a wide range of applications, including agricultural health, insect infestations, and natural hazard impacts. The HLSS30 and HLSL30 products are gridded to the same resolution and tiling system and thus are “stackable” for time series analysis. Key Properties: Geographic Coverage: Global Land Temporal Coverage: March 2026 - Present Spatial Resolution: 30-meter Revisit Time: ~1 Day Update Frequency: Daily Product Level: Level-3 Source Data Coordinate System: Universal Transverse Mercator (UTM) WGS84 Service Coordinate System: Web Mercator Auxiliary Sphere (EPSG:3857) Multispectral Bands NameDescriptionUnitsData TypeFill ValueScale FactorBand 1Coastal AerosolN/Aint16-99990.0001Band 2BlueN/Aint16-99990.0001Band 3GreenN/Aint16-99990.0001Band 4RedN/Aint16-99990.0001Band 5NIRN/Aint16-99990.0001Band 6SWIR 1N/Aint16-99990.0001Band 7SWIR 2N/Aint16-99990.0001Band 9CirrusN/Aint16-99990.0001Band 10TIRS 1N/Aint16-99990.01Band 11TIRS 2N/Aint16-99990.01FmaskQuality BitsBit Fielduint8255N/ASAASun Azimuth AngleDegreeuint16400000.01SZASun Zenith AngleDegreeuint16400000.01VAAView Azimuth AngleDegreeuint16400000.01VZAView Zenith AngleDegreeuint16400000.01Processing Templates Server-side renderings available on this layer (select via the Rendering / Image Display options). The default rendering is Natural Color. Band-combination templates are for visualization; index templates (NDVI, NDWI, NBR, NDBI) return values suitable for analysis. "DRA" applies dynamic range adjustment; "Cloud Mask" variants suppress pixels flagged by the Fmask quality band. NDVI Colormap — Normalized difference vegetation index (NDVI) with colormap. Dark green represents vigorous vegetation and brown represents sparse vegetation. It is computed as (b5 - b4) / (b5 + b4) and is suitable for vegetation, land cover and plant health monitoring. (also available: Cloud Mask) NDVI Raw — Normalized difference vegetation index (NDVI) computed as (b5 - b4) / (b5 + b4) and is suitable for vegetation, land cover and plant health monitoring. (also available: Cloud Mask) NDWI Raw — The NDWI index is computed as Green(Band03)-NIR(Band05)/ Green(Band03)+NIR(Band05) and is most suitable for mapping of water bodies, droughts, boundary evaluation. Water bodies have strong absorbability and low radiation within the visible to infrared spectral ranges and this index is based on this phenomenon. (also available: Cloud Mask) Natural Color — Natural Color bands red, green, blue(4, 3, 2) displayed with fixed stretch applied. (also available: Cloud Mask, DRA, DRA and Cloud Mask) Normalized Burn Ratio — The NBR index is computed as NIR(Band05)-SWIR(Band7)/NIR(Band05)+SWIR(Band7) and appropriate for highlighting burned areas and estimating fire severity. It highlights burnt areas in fire zones greater than 500 acres. You will need to generate a differenced NBR image by subtracting a post-fire image from a pre-fire image. The resulting darker pixels represent burned areas. (also available: Cloud Mask) Normalized Difference Built-Up Index — The NDBI index is computed as SWIR(Band6)-NIR(Band05)/ SWIR(Band6)+NIR(Band05) and is suitable for watershed runoff predictions, tracking urbananisation and land-use planning. It highlights urban areas with higher reflectance in the SWIR region, compared to the NIR region. This index also contains a cloud mask. (also available: Cloud Mask) Limitations of Use: HLSL30 v2.0 data contain several known limitations related to atmospheric correction, cloud masking, geolocation, and metadata that users should carefully consider before analysis. A full description of these known issues is available here. Latency: Imagery tiles are configured to render at a 150 meter scale. Dynamic Mosaic rendering can take an extended period of time.  Resource Links: Download Data User Guide General Documentation For inquiries about this service, please contact support@earthdata.nasa.gov or post/view questions on the Earthdata Forum Citation: Neigh, C., Ju, J., Roger, J.-C., Skakun, S., Vermote, E., Claverie, M., Dungan, J., Yin, Z., Freitag, B., & Justice, C. (2021). HLS Operational Land Imager Surface Reflectance and TOA Brightness Daily Global 30m v2.0 [Dataset]. NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/HLS/HLSL30.002

The Harmonized Landsat and Sentinel-2 (HLS) project takes input data from the joint NASA/USGS Landsat 8 and Landsat 9 satellites and the European Space Agency's Sentinel-2A, Sentinel-2B, and Sentinel-2C satellites to generate a harmonized, analysis-ready surface reflectance data product with observations every 1.6 days.  Intended Use: The frequent revisit times of HLS allow for time series of land surface applications at the field/plot scale, which supports a wide range of applications, including agricultural health, insect infestations, and natural hazard impacts. The HLSS30 and HLSL30 products are gridded to the same resolution and tiling system and thus are “stackable” for time series analysis. Key Properties: Geographic Coverage: Global Land Temporal Coverage: May 2026 - Present Spatial Resolution: 30-meter Revisit Time: ~1 Day Update Frequency: Daily Product Level: Level-3 Source Data Coordinate System: Universal Transverse Mercator (UTM) WGS84 Service Coordinate System: Web Mercator Auxiliary Sphere (EPSG:3857) Multispectral Bands Name Description Units Data Type Fill Value Scale Factor Band 1Coastal AerosolN/Aint16-99990.0001 Band 2BlueN/Aint16-99990.0001 Band 3GreenN/Aint16-99990.0001 Band 4RedN/Aint16-99990.0001 Band 5Red Edge 1N/Aint16-99990.0001 Band 6Red Edge 2N/Aint16-99990.0001 Band 7Red Edge 3N/Aint16-99990.0001 Band 8NIR BroadN/Aint16-99990.0001 Band 8ANIR NarrowN/Aint16-99990.0001 Band 9Water VaporN/Aint16-99990.0001 Band 10CirrusN/Aint16-99990.0001 Band 11SWIR 1N/Aint16-99990.0001 Band 12SWIR 2N/Aint16-99990.0001 FmaskQuality BitsBit Fielduint8255N/A SAASun Azimuth AngleDegreeuint16400000.01 Processing Templates Server-side renderings available on this layer (select via the Rendering / Image Display options). The default rendering is Natural Color. Band-combination templates are for visualization; index templates (NDVI, NDWI, NBR, NDBI) return values suitable for analysis. "DRA" applies dynamic range adjustment; "Cloud Mask" variants suppress pixels flagged by the Fmask quality band. NDVI Colormap — Normalized difference vegetation index (NDVI) with colormap. Dark green represents vigorous vegetation and brown represents sparse vegetation. It is computed as (b5 - b4) / (b5 + b4) and is suitable for vegetation, land cover and plant health monitoring. (also available: Cloud Mask) NDVI Raw — Normalized difference vegetation index (NDVI) computed as (b5 - b4) / (b5 + b4) and is suitable for vegetation, land cover and plant health monitoring. (also available: Cloud Mask) NDWI Raw — The NDWI index is computed as Green(Band03)-NIR(Band05)/ Green(Band03)+NIR(Band05) and is most suitable for mapping of water bodies, droughts, boundary evaluation. Water bodies have strong absorbability and low radiation within the visible to infrared spectral ranges and this index is based on this phenomenon. (also available: Cloud Mask) Natural Color — Natural Color bands red, green, blue(4, 3, 2) displayed with fixed stretch applied. (also available: Cloud Mask, DRA, DRA and Cloud Mask) Normalized Burn Ratio — The NBR index is computed as NIR(Band05)-SWIR(Band7)/NIR(Band05)+SWIR(Band7) and appropriate for highlighting burned areas and estimating fire severity. It highlights burnt areas in fire zones greater than 500 acres. You will need to generate a differenced NBR image by subtracting a post-fire image from a pre-fire image. The resulting darker pixels represent burned areas. (also available: Cloud Mask) Normalized Difference Built-Up Index — The NDBI index is computed as SWIR(Band6)-NIR(Band05)/ SWIR(Band6)+NIR(Band05) and is suitable for watershed runoff predictions, tracking urbananisation and land-use planning. It highlights urban areas with higher reflectance in the SWIR region, compared to the NIR region. This index also contains a cloud mask. (also available: Cloud Mask) Limitations of Use: HLSS30 v2.0 data contain several known limitations related to atmospheric correction, cloud masking, geolocation, and metadata that users should carefully consider before analysis. A full description of these known issues is available here. Latency: Imagery tiles are configured to render at a 150 meter scale. Dynamic Mosaic rendering can take an extended period of time.  Resource Links: Download Data User Guide General Documentation For inquiries about this service, please contact support@earthdata.nasa.gov or post/view questions on the Earthdata Forum Citation: Neigh, C., Ju, J., Roger, J.-C., Skakun, S., Vermote, E., Claverie, M., Dungan, J., Yin, Z., Freitag, B., & Justice, C. (2021). HLS Sentinel-2 Multi-spectral Instrument Surface Reflectance Daily Global 30m v2.0 [Dataset]. NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/HLS/HLSS30.002.

__Note__: _A new version of this item is available for your use. This mature version of the map remains available for use in existing applications. This item will be retired in December 2024. There is 2023 data available in the newer 9-class v2 dataset._ Time series of annual global maps of land use and land cover (LULC). It currently has data from 2017-2022. The maps are derived from ESA Sentinel-2 imagery at 10m resolution. Each map is a composite of LULC predictions for 9 classes throughout the year in order to generate a representative snapshot of each year. This dataset was generated by Impact Observatory, who used billions of human-labeled pixels (curated by the National Geographic Society) to train a deep learning model for land classification. The global map was produced by applying this model to the Sentinel-2 annual scene collections on the Planetary Computer. Each of the maps has an assessed average accuracy of over 75%. This map uses an updated model from the 10-class model and combines Grass(formerly class 3) and Scrub (formerly class 6) into a single Rangeland class (class 11). The original Esri 2020 Land Cover collection uses 10 classes (Grass and Scrub separate) and an older version of the underlying deep learning model. The Esri 2020 Land Cover map was also produced by Impact Observatory. The map remains available for use in existing applications. New applications should use the updated version of 2020 once it is available in this collection, especially when using data from multiple years of this time series, to ensure consistent classification. All years are available under a Creative Commons BY-4.0.

OPERA Level-2 Radiometric Terrain Corrected (RTC) products in VV polarization generated from Sentinel-1 SAR imagery, processed by OPERA (JPL). Values for the VV polarization are commonly driven by surface roughness and/or soil moisture, with rougher surfaces and higher soil moisture returning higher backscatter values. Surface water appears very dark under calm conditions, as the signal bounces off the surface away from the sensor. OPERA RTC-S1 data is available over all landmasses (excluding Antarctica) for Sentinel-1 acquisitions starting April 14, 2016, but only products from October 4, 2023, onward are included in this image service. The source rasters referenced in this service are hosted by the Alaska Satellite Facility in NASA's Earthdata Cloud, and the service is updated daily to include new products. More information about the dataset is available at https://asf.alaska.edu/datasets/daac/opera/. OPERA includes partners from NASA’s Goddard Space Flight Center, the U.S. Geological Survey (USGS), the University of Maryland College Park, the University of Alaska Fairbanks, Southern Methodist University, and EarthScope. Refer to https://www.jpl.nasa.gov/go/opera for more details.  This service is still under development. Please contact hjkristenson@alaska.edu if you encounter any problems.

uav imagery by Luka Koens, acquired 2026-08-01 to 2026-08-02, 1.0 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2026-01-11 to 2026-01-12, 5.1 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2026-01-11 to 2026-01-12, 6.0 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2026-01-10 to 2026-01-10, 10.0 cm per pixel, published on OpenAerialMap.