United States of America imagery and land cover data
＋ Follow new data289 datasets about imagery and land cover in United States of America.
uav imagery by Garrett Jobes, acquired 2026-05-29 to 2026-05-29, 18.5 cm per pixel, published on OpenAerialMap.
uav imagery by THOMPSON, acquired 2025-11-18 to 2025-11-18, 3.5 cm per pixel, published on OpenAerialMap.
uav imagery by North Metro Fire, acquired 2026-07-23 to 2026-07-24, 1.5 cm per pixel, published on OpenAerialMap.
satellite imagery by Phil Gandy, acquired 2025-07-13 to 2025-07-13, 2.0 cm per pixel, published on OpenAerialMap.
uav imagery by Crayton Litton (Crayton Technologies), acquired 2025-05-24 to 2025-05-25, 5.0 cm per pixel, published on OpenAerialMap.
uav imagery by North Metro Fire, acquired 2026-07-23 to 2026-07-23, 1.1 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.
Dates of Images: Post-Event: February 20, 2025, February 23, 2025, February 25, 2025 Pre-Event: February 10, 2025 Date of Next Image: Unknown 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. Snow cover appears as white. The Short Wave Infrared (SWIR) RGB is a product that is created using the SWIR, NIR, and Red channels of the respective instrument. Snow cover appears as various shades of teal. 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. Snow cover appears as white. 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/GSFC, USGS, ESA Copernicus Esri REST Endpoint: See URL section on right side of page WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202502_FLOOD_OHVALLEY/2502_sentinel2/ImageServer/WMSServer
Dates of Images: Post-Event: January 14, 2025 Pre-Event: January 6, 2025 Summary: Natural Color: The Natural Color RGB provides a false composite look at the surface. This RGB uses a shortwave, the near-infrared, and red channels from the 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. 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. The Normalized Burn Ratio identifies burned areas using this calculation. Darker areas are potentially burned areas. Suggested Use: Natural Color: areas of water will appear blue, healthy green vegetation will appear as a bright green, urban areas in various shades of magenta. Color Infrared: depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred. 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. Darker Areas are potentially burned in the NBR product. Satellite/Sensor: Landsat 9 Operational Land Imager (OLI) Resolution: 30 meters Credits: NASA/MSFC, USGS Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=a95eee54bd9e45548ad2b7e49ac0fd93 WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202501_FIRE_CA/2501_landsat/ImageServer/WMSServer
uav imagery by North Metro Fire Rescue District, acquired 2026-05-28 to 2026-05-28, 1.7 cm per pixel, published on OpenAerialMap.
uav imagery by North Metro Fire, acquired 2026-09-07 to 2026-09-07, 3.2 cm per pixel, published on OpenAerialMap.
uav imagery by Anna Ko, acquired 2026-09-06 to 2026-09-07, 5.0 cm per pixel, published on OpenAerialMap.
uav imagery by sky, acquired 2026-06-26 to 2026-06-26, 5.0 cm per pixel, published on OpenAerialMap.
uav imagery by NMFRD, acquired 2026-06-05 to 2026-06-05, 3.1 cm per pixel, published on OpenAerialMap.
uav imagery by North Metro Fire Rescue District, acquired 2026-06-15 to 2026-06-15, 1.2 cm per pixel, published on OpenAerialMap.
This 2006 Orthoimagery Tile Index file can be used to geo-reference the individual image tiles across the City. This tile index is used in conjunction with the 2006 Orthoimagery by individual Borough download. Full metadata on the Aerial & Orthoimagery can be found at: https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_AerialImagery.md
This 2004 Orthoimagery Tile Index file can be used to geo-reference the individual image tiles across the City. This tile index is used in conjunction with the 2004 Orthoimagery by individual Borough download. Full metadata on the Aerial & Orthoimagery can be found at: https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_AerialImagery.md
1993 black and white aerial photos of parts of Boulder.
Dates of Images: Post-Event: 7/2/2026, 7/12/2026, 7/18/2026 Pre-Event: 6/10/2026. 6/12/2026 Date of Next Image: Unknown 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: Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager (OLI-2) Resolution: 30 meters Esri REST Endpoint: See Layers below. WMS Endpoint:
Dates of Images: Post-Event: 9/19/2018 Pre-Event: 8/9/2018 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 September 19, 2018 as compared to August 9, 2018. 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: Landsat Resolution: 3 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_EX2601_201809_HURRICANE_FLORENCE/ex2601_landsat_bndvi/MapServer/WMSServer
The visible-wavelength true color RGB digital camera images were taken by astronauts aboard the International Space Station showing areas affected by the fires in Washington August 2026. Date of Images: Dates: July 30, 2026: ISS075-E-658 July 31, 2026: ISS075-E-1496, ISS075-E-1537, ISS075-E-1547, ISS075-E-1557 August 4, 2026: ISS075-E-2214-2215, ISS075-E-2218 Locations: Little Giant fire: ISS075-E-1496, ISS075-E-1537 Kaiser Canyon and Modrite fires: ISS075-E-658, ISS075-E-1547, ISS075-E-1557 Sinlahekin fire: ISS075-E-2214-2215, ISS075-E-2218 Camera: Nikon Z9 Focal Length: 400 mm: ISS075-E-1496, ISS075-E-1537, ISS075-E-1547, ISS075-E-1557, ISS075-E-2214-2215, ISS075-E-2218 240 mm: ISS075-E-658 Suggested Use: This image provides regional context, and may be useful for visualization of the ongoing event. Higher spatial resolution images may be suitable for spatial analysis to support decision making or research applications. Credits: International Space Station Program, NASA Johnson Space Center Earth Science and Remote Sensing Unit, ARES Division, Exploration Architecture, Integration & Science Directorate Esri REST Endpoint: See URL to the right WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202603_FLOOD_HI/2603_iss/ImageServer/WMSServer Data Download: Full datasets are available for download at the Gateway to Astronaut Photography of Earth. Download for this specific data can be found at: https://eol.jsc.nasa.gov/WebShare/WebShare.pl?folder=NASADisastersProgram/NDP_WashingtonFires_AUGUST2026
Date of Image: May 19, 2026 Date of Next Image: None Expected Summary: The polygon was derived from a combination of a normalized burn ratio (NBR) thresholding derived via Sentinel-2 near-infrared (NIR) and shortwave-infrared bands and a simple single-band NIR threshold from the same image. The NBR threshold for the binary burned classification was set to values Credits: USGS, Landsat, Clayton Elder (ARC) Esri REST Endpoint: See URL to the right. WMS Endpoint:
Researchers working with the Global Land Analysis & Discovery (GLAD) at University of Maryland, College Park, Maryland and Advanced Rapid Imaging and Analysis (ARIA) and Observational Products for End-Users from Remote Sensing Analysis (OPERA) teams at NASA's Jet Propulsion Laboratory, Pasadena, California, created maps of surface disturbance due to ongoing wildfires in Los Angeles County in January 2025 using the OPERA Disturbance Alert from Harmonized Landsat Sentinel-2 (DIST-ALERT-HLS) products. The results posted here are preliminary results, primarily intended to aid the field response and people who wanted to have a rough first look at the area impacted by wildfire. The ARIA-share website has always focused on posting preliminary results as fast as possible for urgent response. All information is provisional for use under emergency response guidelines. These data are provided with absolutely no warranty of any kind. Use at your own risk. OPERA DIST-ALERT-HLS The Disturbance product (DIST) maps per pixel vegetation disturbance (specifically, vegetation cover loss) from the Harmonized Landsat Sentinel-2 (HLS) scenes. We provide the (1) maximum vegetation anomaly value (VEG-ANOM-MAX) layer and (2) vegetation disturbance status (VEG-DIST-STATUS). All provided layers have been filtered to include only disturbance detected following the start of the Greater Los Angeles wildfires (starting Jan. 7, 2025). Images are provided from January 12 and January 14, 2025. The images are provided as GeoTIFF files. VEG-ANOM-MAX: Difference between historical and current year observed vegetation cover at the date of maximum decrease (vegetation loss of 0-100%). This layer can be used to threshold vegetation disturbance per a given sensitivity (e.g. disturbance of >=20% vegetation cover loss). The sum of the historical percent vegetation and the anomaly value will be the vegetation cover estimate for the current year. VEG-DIST-STATUS: Indication of vegetation cover loss (vegetation disturbance). The status label is based on the maximum anomaly value, confidence level, and whether it is ongoing or finished. "First" means the pixel has had an anomaly detection but no subsequent observations whether anomalous or not. ''Provisional'' means there have been two consecutive disturbance detections but not yet with high confidence. ''Confirmed'' means that vegetation disturbance is detected with high confidence. The label ''finished'' is applied to confirmed disturbances that have had two consecutive no-anomaly observations or one 15 days or more after the last anomaly detection. If a new disturbance is detected, it will overwrite those in a ''finished'' state. These labels are reported for both above and below the 50% disturbance threshold based on the maximum anomaly value. Satellite/Sensor: MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/B satellites and Operational Land Imager 2 (OLI-2) on NASA's Landsat 8/9 satellite. Resolution: 30 meters The DIST-ALERT-HLS products included here have these flags: 255 represents ''No Data'' and is based on the Fmask layer of the source HLS granule. OPERA DIST-ALERT-HLS data availability: The post-processed products are available to download at https://aria-share.jpl.nasa.gov/20250113-GreaterLosAngeles_Fires/DIST-HLS/ The OPERA DIST-HLS products have been in production since January 2022, are freely distributed to the public via NASA's Land Processes Distributed Active Archive Center (LP DAAC), and can be downloaded through NASA's Earthdata search. For more information about the Surface Disturbance product suite, please refer to the DIST Product page: https://www.jpl.nasa.gov/go/opera/products/dist-product-suite/ For more information about the GLAD project, visit https://glad.umd.edu/ For more information about the Caltech-JPL ARIA project, visit https://aria.jpl.nasa.gov For more information about the JPL OPERA project, visit https://www.jpl.nasa.gov/go/opera/ Suggested Use for DIST-HLS: VEG-DIST-STATUS: Layer values: 0: No disturbance (suggested color: #121212) 1: first 2: provisional 3: confirmed 4: first >=50% (suggested color: #008888) 5: provisional >=50% (suggested color: #e48727) 6: confirmed >=50% (suggested color: #e01b07) 7: confirmed 8: confirmed >=50%, finished (suggested color: #dddddd) 255: No data (suggested color: transparent) VEG-ANOM-MAX: Layer values: 0-100: Maximum loss of percent vegetation (suggested color: white to red gradient) 255: No data (suggested color: transparent) Product POCs: Alexander L. Handwerger (alexander.handwerger@jpl.nasa.gov) Zhen Song (zhensong@umd.edu) Matt Hansen (mhansen@umd.edu) Steven Chan (steventsz.k.chan@jpl.nasa.gov) David Bekaert (david.bekaert@jpl.nasa.gov) Credits: The product contains modified Copernicus Sentinel data (2024) and is produced as part of the OPERA project, which is funded by NASA to address remote sensing needs identified by the Satellite Needs Working Group. Managed by NASA's Jet Propulsion Laboratory, OPERA funds and manages the DIST-ALERT-HLS product developed and produced by the Global Land Analysis and Discovery (GLAD) laboratory at the University of Maryland. NASA JPL-Caltech-UMD ARIA/OPERA Team ================== Files: OPERA-DIST-ALERT-HLS-VEG-ANOM-MAX_01-14-2025.tif: January 14, 2025 showing the maximum vegetation anomaly. OPERA-DIST-ALERT-HLS-VEG-DIST-STATUS_01-14-2025.tif: January 14, 2025 showing the status anomaly. OPERA-DIST-ALERT-HLS-VEG-ANOM-MAX_20250112.tif: January 12, 2025 showing the maximum vegetation anomaly. OPERA-DIST-ALERT-HLS-VEG-DIST-STATUS_20250112.tif: January 12, 2025 showing the status anomaly. Last Update 14 January 2025 Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=3a64b84ac45040a4bc78adf5872ad7de WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202501_FIRE_CA/2501_opera_dist_hls/ImageServer/WMSServer Data Download: https://aria-share.jpl.nasa.gov/20250113-GreaterLosAngeles_Fires/DIST-HLS/
2002 aerial photos of the City and the surrounding area.
This tiled imagery service represents a snapshot of the land surface within Napa County and is made available for public use. The tile cache scheme follows the ArcGIS Online Model and can viewed down to ~1:283 scale. A hard copy of this data is also available directly from the GIS Team. For more information, contact gisstaff@countyofnapa.org. Extent and Resolution:Ortho-imagery and Oblique imagery within Napa County, California. Projection:State Plane Coordinate System1983 California Zone 2North American Datum 1983 (2011) NAVD88 US Survey Feet Capture Window:Imagery was obtained between the dates of June 5 and June18th. Bands:3 (RGB) Sensor: Accuracy of Orthophotography: For questions regarding use and access, please contact gisstaff@countyofnapa.org.
Dates of Images: May 24, 2026 Summary: The Advanced Rapid Imaging and Analysis (ARIA) and Observational Products for End-Users from Remote Sensing Analysis (OPERA) teams at the Jet Propulsion Laboratory, California Institute of Technology produced flood mapping products using the OPERA Dynamic Surface Water Extent from Harmonized Landsat Sentinel-2 (DSWx-HLS) dataset. These products provide a rapid assessment of surface water extent to support emergency response and situational awareness during flood events. The dataset provides: Surface Water Extent maps on individual dates Dates and Input Data: Flood images: May 24, 2026 Products are generated from OPERA DSWx-HLS satellite imagery and mosaicked across tiles to provide continuous coverage. Product Description: Surface water is identified from optical satellite imagery and mapped at 30 m spatial resolution. Maximum Surface Water Extent maps show all locations where water was detected at any time during the analysis period. Caveats and Limitations: We note the HLS snow/ice mask often misclassifies sediment rich water as snow/ice. Detecting inundation under vegetation, in the urban perimeter, in arid environments, and along water body edges is known to be challenging. The local accuracy of the flood maps in such environments may be impacted. These results are intended to support rapid emergency response. All information is provisional for use under emergency response guidelines. These data are provided with absolutely no warranty of any kind. Use at your own risk. Suggested Use: The OPERA DSWx-HLS Water product classifies the Harmonized Landsat Sentinel-2 (HLS) input imagery into "not water", "open surface water", and “partial surface water”. The "HLS cloud/cloud shadow" and "HLS snow/ice" layers are direct inputs from the HLS Fmask. Water (WTR) Layer Values: File names: OPERA_L3_DSWX-HLS_V1_BWTR_20260524T1609_mosaic.tif, Values: 0: Not Water - an area with valid reflectance data that is not open water (class 1), partial surface water (class 2), snow/ice (class 252), cloud/cloud shadow (class 253), or ocean masked (class 254). Masking can result in a not water (class 0) where land cover masking is applied. (suggested color: #ffffff) 1: Open Water - an area that is entirely water and unobstructed to the sensor, including obstructions by vegetation, terrain, and buildings. (suggested color: #0000ff) 2: Partial Surface Water - an inundated area that is at least 20% and less than 100% open water. This may be referred to as “subpixel inundation” when referring to a pixel’s area. Examples include wetlands, water bodies with emergent vegetation, and pixels bisected by coastlines. (suggested color: #b4d5f4) 252: Snow/Ice/Sediment Rich Water - an area identified as snow/ice according to input HLS Fmask quality assurance (QA) data (suggested color: #00ffff) 253: Cloud/Cloud Shadow - an area identified as cloud or cloud shadow or adjacent to cloud/cloud shadow according to input HLS Fmask quality assurance (QA) data (suggested color: #afafaf) 254: Ocean Masked - an area identified as ocean using a shoreline database with an added margin (suggested color: #00007f) 255: No data (suggested color: transparent) Satellite/Sensor: Harmonized Landsat Sentinel-2 (HLS) derived from MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B/2C satellites and Operational Land Imager 2 (OLI-2) on NASA/USGS Landsat 8/9 satellites. Spatial Resolution: 30 meters Temporal Resolution: Sub-weekly Esri REST Endpoint: See URL to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2601_201809_HURRICANE_FLORENCE/ex2601_opera_dswx_hls/MapServer/WMSServer
Full Metadata This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). The EnviroAtlas One Meter-scale Urban Land Cover (MULC) Data were generated individually for each EnviroAtlas community to provide a detailed view of the urban environment for analysis of multiple human and ecosystem health metrics and services. Source imagery varies by community. Land cover classes mapped also vary by community and include the following: water, impervious surfaces, soil and barren land, trees, shrub, grass and herbaceous, agriculture, orchards, woody wetlands, and emergent wetlands. Accuracy assessments were completed for each community's classification. For specific information about methods and accuracy of each community's land cover classification, consult their individual metadata records: Austin, TX; Cleveland, OH; Des Moines, IA; Durham, NC; Fresno, CA; Green Bay, WI; Memphis, TN; Milwaukee, WI; Minneapolis/St. Paul, MN; New Bedford, MA; New York, NY; Phoenix, AZ; Pittsburgh, PA; Portland, ME; Paterson, NJ; Portland, OR; Tampa, FL; and Woodbine, IA.
Dates of Images: Post-Event: 6/29/2026, 7/01/2026, 7/02/2026, 7/04/2026, 7/6/2026, 7/9/2026, 7/11/2026, 7/14/2026 Pre-Event: 6/16/2026, 6/19/2026 Date of Next Image: Unknown 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. Federal permitted grazing land maps from the US Forest Service and Department of Interior - Bureau of Land Management (BLM) are shown in the web map. For more information: https://data-usfs.hub.arcgis.com/datasets/usfs::range-unit-allotment-3/about & https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-colorado-grazing-allotments/about 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: True Color: 10 meters Credits: NASA/MSFC, USGS, ESA Copernicus Esri REST Endpoint: See layers below. WMS Endpoint: See individual layer pages.
Dates of Images: Post-Event: 9/18/2018 Pre-Event: 8/29/2018 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 May 6, 2024 compared to April 21, 2024. 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 WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2601_201809_HURRICANE_FLORENCE/ex2601_sentinel2_bndvi/MapServer/WMSServer
Polygon features coded with comprehensive information related to foot aerial photography image frames collected by Kentucky's Aerial Photography and Elevation Data program (KYAPED) from 2012-2014. Aerial photography related to this data was captured in late winter and early spring as part of a collaborative effort among federal, state and local government agencies as well as educational entities in Kentucky. https://ky.box.com/v/kymartian-image-frames-2012-14
Dates of Images: Post-Event: 6/29/2026, 7/01/2026, 7/02/2026, 7/04/2026, 7/6/2026, 7/9/2026, 7/11/2026, 7/14/2026 Pre-Event: 6/16/2026, 6/19/2026 Date of Next Image: Unknown 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. Federal permitted grazing land maps from the US Forest Service and Department of Interior - Bureau of Land Management (BLM) are shown in the web map. For more information: https://data-usfs.hub.arcgis.com/datasets/usfs::range-unit-allotment-3/about & https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-colorado-grazing-allotments/about 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: True Color: 10 meters Credits: NASA/MSFC, USGS, ESA Copernicus Esri REST Endpoint: See layers below. WMS Endpoint: See individual layer pages.
Dates of Images: Post-Event: 7/2/2026, 7/12/2026, 7/18/2026 Pre-Event: 6/10/2026. 6/12/2026 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. 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. 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. Color Infrared: depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred. Satellite/Sensor: Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager (OLI-2) Resolution: 30 meters Credits: NASA/MSFC, USGS Esri REST Endpoint: See Layers below. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202606_EARTHQUAKE_VENEZUELA/202611_landsat/ImageServer/WMSServer