Imagery and land cover data

satellite imagery by Vantor, acquired 2026-03-20 to 2026-03-20, 40.2 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.

uav imagery by WebODM, acquired 2026-02-08 to 2026-02-08, 3.3 cm per pixel, published on OpenAerialMap.

Dates of Images: 4/30/2024, 5/7/2024 Date of Next Image: Varies by region, typically 12 days since previous pass. Set time slider to most recent interval and click on area of interest to identify date of last pass. Summary: The Alaska Satellite Facility has developed false color Red, Green, Blue (RGB) and Radiometrically Terrain-Correct (RTC) composites of the Sentinel-1A/B Synthetic Aperture Radar (SAR) instrument which assigns the co- and cross-polarization information to a channel in the composite. When used to support a flooding event, areas in blue denotes water present at the time of the satellite overpass before or after the start of the flooding event. Sentinel-1 RGB Decomposition of RTC VV and VH imagery over United States coastlines. Blue areas have low returns in VV and VH (smooth surfaces such as calm water, but also frozen/crusted soil or dry sand), Green areas have high returns in VH (volume scatterers such as vegetation or some types of snow/ice), and Red areas have relatively high VV returns and relatively low VH returns (such as urban or sparsely vegetated areas). Suggested Use: In this image, water appears in blue, vegetated areas in shades of green and urban areas in bright orange. It is recommended to use this product with ancillary information to derive flooded areas. Satellite/Sensor: Synthetic Aperture Radar on European Space Agency's (ESA) Copernicus Sentinel-1A satellite Resolution: 30 meters Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=e893329c61b6428bbe903d3452a8ba0a WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202405_FLOOD_TX/2408_sentinel1/ImageServer/WMSServer

Dates of Images: Post-Event: 3/14/2026 Pre-Event: 1/25/2026 Date of Next Image: Unknown Summary: True Color: 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. Suggested Use: True Color: provides a product of how the surface would look to the naked eye from space. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred. Satellite/Sensor: Landsat 9 Operational Land Imager (OLI) Resolution: 30 meters Credits: NASA/MSFC, USGS Esri REST Endpoint: See URL section on right side of page WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202603_FLOOD_HI/2605_landsat/ImageServer/WMSServer

uav imagery by NetApex, acquired 2026-02-24 to 2026-02-24, 5.0 cm per pixel, published on OpenAerialMap.

Dates of Images: Post-Event: January 12, 2025 Pre-Event: December 18, 2024 Summary: 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. The Short Wave Infrared (SWIR) RGB is a product that is created using the SWIR, NIR, and Red channels of the respective instrument. The Color Infrared composite is created using the near-infrared, red, and green channels, allowing for the ability to see areas impacted by the fires. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue. The Normalized Burn Ratio identifies burned areas using this calculation. Darker areas are potentially burned areas. Suggested Use: The True Color RGB provides a product of how the surface would look to the naked eye from space. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred. The Short Wave Infrared (SWIR) RGB is a product that can provides value in flood detection. Areas of water will appear blue, healthy green vegetation will appear as a bright green, urban areas in various shades of magenta, snow will appear as a bright blue/cyan, and bare soils being multicolor dependent on their makeup. Compare pre-event imagery to post-event imagery to identify potential affected areas. A Color Infrared composite depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred. Satellite/Sensor: MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites Resolution: True Color and Color Infrared: 10 meters Shortwave Infrared: 20 meters Credits: NASA/MSFC, USGS, ESA Copernicus Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=cc620f9a325a4c8a9e10fa90f1ce7e11 WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202501_FIRE_CA/2501_sentinel2/ImageServer/WMSServer

ArcGIS Image ServiceTime Interval: Full Climatology Version: 1 Spatial Resolution: 3 km Time Extent: 2004 to 2024 Projection: GCS WGS84 Extent: Regional | Europe Other Formats: OGC WMS, OGC WCS, REST CollectionThis collection contains European CTH detection climatological 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

Date of Image(s): 1/11/2025 Date of Next Image: 1/16/2025 Summary: This product visualizes three dominant principal components derived from the surface reflectance estimates from airborne imaging spectroscopy measurements taken by NASA JPL’s AVIRIS-3. The image visualizes the relative strength of three dominant eigenvectors, estimated from data across the full scene. Eigenvectors from this high (284) dimensional dataset do not specifically identify physical features but are correlated to physical phenomena; similar to how ‘red’, ‘green’, or ‘blue’ in a traditional image are correlated to, but not directly indicative of, specific physical processes. Instead of just “red,” “green,” and “blue,” this analysis considers 284 unique “colors” in the visible to shortwave infrared spectrum, providing a much more robust depiction of spectral differences. Thus, contrast between different colored regions in this image can be used to infer strong differences in surface type. For example, the fire boundary at the time of image collection is readily apparent. Explained another way, within a given scene, burned structures will share a unique spectral reflectance signature in “284-color-space” compared to other surfaces and display as the same color in the PCA image. The product ground spatial resolution is approximately 2.8 m, and flights occurred between 19:40 and 21:00 UTC on Jan 11th 2025. Raw data are available for download here: https://popo.jpl.nasa.gov/pub/LA_Fires/dist/eaton_pca_20250111.tif, https://popo.jpl.nasa.gov/pub/LA_Fires/dist/palisades_pca_20250111.tif. In the absence of a supervised image classification, the PCA image can demonstrate areas with similar spectral reflectance properties. On visual inspection of the PCA image, we can intuitively differentiate burned areas from non-burned areas, even for different types of burned surfaces (e.g. burned vegetation vs. burned structures). Note: PCA images are produced on a scene-specific basis. This means unique PCA color representation in one scene does not translate to the same colors in another scene. For example, colors in the Eaton Fire scene do not relate to the same colors in the Palisades fire scene. Suggested Use: As an unsupervised method to reduce dimensionality and improve feature extraction in high-spectral resolution datasets, the PCA image can serve as an intermediate visual guide to reveal the information content and diversity of surfaces in the AVIRIS-3 datasets. Analysts may use this image to visually understand the spectral diversity of fire impacted areas, especially in conjunction with ancillary data that characterizes the unique underlying physical phenomena represented by unique colors in the PCA image. POC: Philip G. Brodrick (JPL) and David R. Thompson (JPL) Citation: AVIRIS-3 Radiance Data: Eckert, R., D.R. Thompson, A.M. Chlus, J.W. Chapman, M. Eastwood, M. Bernas, S. Geier, M. Helmlinger, D. Keymeulen, E. Liggett, S. Nadgauda, L.M. Rios, L.A. Shaw, W. Olson-Duvall, P.G. Brodrick, and R.O. Green. 2024. AVIRIS-3 L1B Calibrated Radiance, Facility Instrument Collection. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2356 AVIRIS-3 Reflectance Data: Brodrick, P.G., A.M. Chlus, U.N. Bohn, E. Greenberg, J. Montgomery, J.W. Chapman, M. Eastwood, S.R. Lundeen, R. Eckert, W. Olson-Duvall, D.R. Thompson, and R.O. Green. 2025. AVIRIS-3 L2A Orthocorrected Surface Reflectance, Facility Instrument Collection. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2357 Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=6898f96fcb1d4b12ba0ba02fb7df28e3 WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202501_FIRE_CA/2501_aviris_pca/ImageServer/WMSServer

ArcGIS Image ServiceTime Interval: Full Climatology Version: 1 Spatial Resolution: 3 km Time Extent: 2015 to 2025 Projection: GCS WGS84 Extent: Regional | Australia Other Formats: OGC WMS, OGC WCS, REST CollectionThis collection contains Australian OT detection climatological statistics averaged over 2015-2025 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

ArcGIS Image ServiceTime Interval: Seasonal Climatology Version: 1 Spatial Resolution: 3 km Time Extent: 2015 to 2025 (Dec-Feb, Mar-May, Jun-Aug, Sep-Nov) Projection: GCS WGS84 Extent: Regional | Australia Other Formats: OGC WMS, OGC WCS, REST CollectionThis collection contains Australian CTH detection climatological statistics averaged over: Dec-Feb, Mar-May, Jun-Aug, Sep-Nov 2015-2025 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

Dates of Images Post-Event: 5/21/2026 Summary Skysat is a high-resolution satellite constellation operated by Planet and allows for multiple viewing opportunities of any location on Earth daily. Skysat collects 4-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. The Color Infrared composite is created using the near-infrared, red, and green channels. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue. Resolution ~1 m Credits NASA Disasters Program, Processing from MSFC, Planet. For derived products: “Includes copyrighted material of Skysat. All rights reserved.” This work utilized data made available through the NASA Commercial Satellite Data Acquisition (CSDA) program.

Date(s) of Images: Post-Event: 5/21/2026 Summary: Satellogic’s operates a commercial constellation of satellites and sensors that offers 4 band (R,G, B and NIR) acquisitions. True Color: 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. Color Infrared: The Color Infrared composite is created using the near-infrared, red, and green channels, allowing for the ability to see areas impacted from the fires. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue. 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."

ArcGIS Image ServiceTime Interval: Annual Version: 1 Spatial Resolution: 3 km Time Extent: 2015 to 2025 Projection: GCS WGS84 Extent: Regional | Australia Other Formats: OGC WMS, OGC WCS, REST CollectionThis service contains Australian Anvil Cloud Days/Year statistics averaged Annually. 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

Date of Images: 2/2/2023, 2/10/2023, 2/17/2023 Summary: This PlanetScope imagery captured by Planet Labs Inc. in February 2023 shows a few landslides following the earthquakes in Türkiye. True Color RGB provides a product of how the surface would look to the naked eye from space. The True Color RGB s produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred. Suggested Use: True Color RGB provides a product of how the surface would look to the naked eye from space. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred. Satellite/Sensor: PlanetScope Resolution: 3 meters Credits: NASA Disasters Program, NASA GSFC, Includes copyrighted material of Planet Labs PBC. All rights reserved. Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=871506b5ebee48c18ff6b89fa5f775f9 WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202302_EARTHQUAKE_TURKIYE/2302_planet/ImageServer/WMSServer

Dates of Images: Post-Event: May 20, 2026; May 19, 2026 Pre-Event: May 7, 2026; April 20, 2026 Date of Next Image: None Summary: 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. The Color Infrared composite is created using the near-infrared, red, and green channels. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue. Suggested Use: The True Color RGB provides a product of how the surface would look to the naked eye from space. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred. A Color Infrared composite depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred. Satellite/Sensor: MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites Resolution: 10 meters Credits: NASA Disasters/MSFC, USGS, ESA Copernicus Esri REST Endpoint: See URL section on right side of page WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202605_FIRE_CA/202609_sentinel2/ImageServer/WMSServer

Dates of Images: Post-Event: 3/12, 3/14, 3/15, 3/16, 3/17, 3/18, 3/19, 3/20, 3/21, 3/22 Pre-Event: 3/10, 3/11,  Date of Next Image: Varies by region, typically 6 days since previous pass. Summary: The Alaska Satellite Facility has developed false color Red, Green, Blue (RGB) and Radiometrically Terrain-Correct (RTC) composite products of the Sentinel-1A/B Synthetic Aperture Radar (SAR) instrument which assigns the co- and cross-polarization information to a channel in the composite. When used to support a flooding event, areas in blue denotes water present at the time of the satellite overpass before or after the start of the flooding event. Sentinel-1 RGB Decomposition of RTC VV and VH imagery over United States coastlines. Blue areas have low returns in VV and VH (smooth surfaces such as calm water, but also frozen/crusted soil or dry sand), Green areas have high returns in VH (volume scatterers such as vegetation or some types of snow/ice), and Red areas have relatively high VV returns and relatively low VH returns (such as urban or sparsely vegetated areas). Suggested Use: In the RGB images, water appears in blue, vegetated areas in shades of green and urban areas in bright orange. It is recommended to use this product with ancillary information to derive flooded areas. Satellite/Sensor: Synthetic Aperture Radar on European Space Agency's (ESA) Copernicus Sentinel-1A satellite Resolution: 20 meters REST Endpoint: See URL below to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202603_FLOOD_HI/2605_sentinel1/ImageServer/WMSServer

uav imagery by Geo-Planning for Advanced Development (GPAD), acquired 2026-08-28 to 2026-08-29, 3.5 cm per pixel, published on OpenAerialMap.

aircraft imagery by IGAC Emergencia Terremoto 2026, acquired 2026-08-28 to 2026-08-28, 10.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2026-08-28 to 2026-08-28, 53.0 cm per pixel, published on OpenAerialMap.

uav imagery by Gaylord Ebro, acquired 2026-07-11 to 2026-07-12, 5.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Sam Colchester, acquired 2026-07-11 to 2026-07-11, 6.3 cm per pixel, published on OpenAerialMap.

uav imagery by Harry Machmud, acquired 2026-06-19 to 2026-06-19, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by Leo Vanualailai, acquired 2026-06-11 to 2026-06-11, 7.1 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 GisBudva, acquired 2026-06-11 to 2026-06-11, 2.0 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 GisBudva, acquired 2026-06-11 to 2026-06-11, 2.0 cm per pixel, published on OpenAerialMap.

uav imagery by RP Agri, acquired 2025-04-27 to 2025-04-28, 3.3 cm per pixel, published on OpenAerialMap.

uav imagery by Garrett Jobes, acquired 2026-05-29 to 2026-05-29, 13.0 cm per pixel, published on OpenAerialMap.

satellite imagery by HOT, acquired 2026-05-18 to 2026-05-18, 6.4 cm per pixel, published on OpenAerialMap.

uav imagery by Pietro S. Fontanella, acquired 2025-12-06 to 2025-12-06, 3.0 cm per pixel, published on OpenAerialMap.

uav imagery by Maxwell Ward, acquired 2025-08-16 to 2025-08-17, 6.5 cm per pixel, published on OpenAerialMap.

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

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

This Collection provides Sentinel-5P Level-2 O3 PR products, which contains ozone concentration for 33 levels in the atmosphere.