Imagery and land cover data

uav imagery by Central Institute of Forensic Science, acquired 2026-01-13 to 2026-01-13, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by Philip Gandy, acquired 2025-05-05 to 2025-05-05, 3.4 cm per pixel, published on OpenAerialMap.

uav imagery by GIS, acquired 2026-07-29 to 2026-07-30, 2.4 cm per pixel, published on OpenAerialMap.

satellite imagery by Rodolfo Vargas Chile. GEÓGRAFO, acquired 2026-06-15 to 2026-06-21, 100 cm per pixel, published on OpenAerialMap.

satellite imagery by Rodolfo Vargas Chile. GEÓGRAFO, acquired 2026-05-20 to 2026-05-20, 100 cm per pixel, published on OpenAerialMap.

uav imagery by Izaak Gabriel, acquired 2025-10-20 to 2025-10-20, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by Malloy Aero, acquired 2026-02-11 to 2026-02-11, 2.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-06-25 to 2026-06-25, 34.3 cm per pixel, published on OpenAerialMap.

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

uav imagery by Rodolfo Vargas Chile. GEÓGRAFO, acquired 2025-10-28 to 2025-10-28, 5.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-08-11 to 2026-08-11, 57.7 cm per pixel, published on OpenAerialMap.

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).

satellite imagery by SDI kenya-Muungano wa wanavijiji, acquired 2026-10-13 to 2026-10-14, 4.0 cm per pixel, published on OpenAerialMap.

uav imagery by Clinton Nkolokosa, acquired 2026-08-13 to 2026-08-14, 5.0 cm per pixel, published on OpenAerialMap.

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

uav imagery by Alex, acquired 2026-05-06 to 2026-05-06, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by Mtukuzi Primary School, acquired 2026-06-13 to 2026-06-14, 5.5 cm per pixel, published on OpenAerialMap.

uav imagery by Johannes Andersen, acquired 2026-08-08 to 2026-08-08, 1.1 cm per pixel, published on OpenAerialMap.

uav imagery by IGAC Emergencia Terremoto 2026, acquired 2026-08-26 to 2026-08-26, 10.0 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2025-11-20 to 2025-11-20, 4.4 cm per pixel, published on OpenAerialMap.

satellite imagery by Netas Ciudadanas, acquired 2026-01-26 to 2026-01-26, 6.3 cm per pixel, published on OpenAerialMap.

uav imagery by GIS, acquired 2026-07-29 to 2026-07-30, 2.6 cm per pixel, published on OpenAerialMap.

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

uav imagery by Rodolfo Vargas Chile. GEÓGRAFO, acquired 2025-09-22 to 2025-09-22, 10.0 cm per pixel, published on OpenAerialMap.

uav imagery by Open Mapping Hub - Asia Pacific, acquired 2025-10-07 to 2025-10-07, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by Madagascar Red Cross, acquired 2026-03-24 to 2026-03-24, 10.5 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-08-28 to 2026-08-28, 40.3 cm per pixel, published on OpenAerialMap.

uav imagery by Openstreetmap Perú, acquired 2025-03-22 to 2025-03-22, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by Help.NGO, acquired 2026-05-25 to 2026-05-25, 9.7 cm per pixel, published on OpenAerialMap.

satellite imagery by Ivo Toledo Grillo, acquired 2025-10-08 to 2025-10-08, 0.2 cm per pixel, published on OpenAerialMap.

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.

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

satellite imagery by Vantor, acquired 2026-08-21 to 2026-08-21, 53.3 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-08-21 to 2026-08-21, 53.3 cm per pixel, published on OpenAerialMap.

uav imagery by Open Mapping Hub - Asia Pacific, acquired 2025-10-02 to 2025-10-02, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by HOT-OSM y Alcaldia de Medio Atrato, acquired 2026-07-24 to 2026-07-25, 5.0 cm per pixel, published on OpenAerialMap.