United States of America imagery and land cover data
＋ Follow new data289 datasets about imagery and land cover in United States of America.
Dates of Images: 20180914T1609, 20180917T1553, 20180918T1549, 20180919T1540, 20180920T1539 (GMT) (YYYYMMDD: HHMM) 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 provided includes two products: Surface Water Extent maps on individual dates Maximum Surface Water Extent maps, showing the full extent of water observed over a defined time period Dates and Input Data: Flood images: September 14, 2018, September 17, 2018, September 18, 2018, September 19, 2018, September 20, 2018 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_WTR_20180914T1609_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20180917T1553_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20180918T1549_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20180919T1540_mosaic.tif, OPERA_L3_DSWX-HLS_V1_WTR_20180920T1539_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) Maximum Water Extent Layer Values: File names: ARIA-OPERA_L3_DSWX-HLS_V1_WTR_20180830T1604_20180920T1539_max_extent.tif 0: Not Water. No water was detected within the time period of the images. Masked pixels are set to No data. (suggested color: #ffffff) 1: Water - an area where open water or partial surface water was detected during the time period of the images. (suggested color: #ff15e4) Satellite/Sensor/Resolution: 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
satellite imagery by North Metro Fire Rescue District, acquired 2026-06-16 to 2026-06-16, 1.6 cm per pixel, published on OpenAerialMap.
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: Copernicus Sentinel-2, Clayton Elder (ARC) Esri REST Endpoint: See URL to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202605_FIRE_KS/202608_sentinel2_nbrburnperimeter/MapServer/WMSServer
uav imagery by North Metro Fire Rescue District, acquired 2026-03-26 to 2026-03-26, 3.9 cm per pixel, published on OpenAerialMap.
2008 DRCOG aerial photo covering the entire county. The area East of the foothills is 6-inch resolution and the area West is 1 foot.
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:Orthoimagery and Oblique imagery within Napa County, California. Projection: Capture Window:
This raster dataset represents land cover classifications for Napa County, California, for the year 2008. It is derived from the Annual National Land Cover Database (NLCD) Collection 1, Version 1.1 (June 2025), produced by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The Annual NLCD product combines methodologies from the National Land Cover Database (NLCD) and Land Change Monitoring, Assessment, and Projection (LCMAP) programs with modern geospatial deep learning techniques to produce annual, high-resolution land cover maps. The dataset provides annual land cover classifications for the conterminous United States (CONUS) from 1985 through 2024 at a 30-meter spatial resolution using a modified Anderson Level II classification system consisting of 16 land cover classes. Source data are derived from Landsat Analysis Ready Data (ARD) processed through the Land Cover Artificial Mapping System (LCAMS), a multi-stage deep learning architecture. This derivative dataset was prepared by the Napa County Planning, Building and Environmental Services (PBES) GIS Division for the Baseline Data Report (BDR) and General Plan Update (GPU) Land Cover Change Analysis. The source raster was reprojected from the native Annual NLCD Albers Equal Area CONUS coordinate system (EPSG:5070) to NAD83 California State Plane Zone II (WKID 2226, US Survey Feet) using Nearest Neighbor resampling to preserve the original land cover classifications, then clipped to the Napa County administrative boundary. Napa County encompasses approximately 507,000 acres in the North San Francisco Bay Area of California. This dataset is one of a 20-year annual time series (2005–2024) used to evaluate land cover change at the countywide scale and within the 13 Geographic Evaluation Areas (GEAs) established for the Napa County General Plan Update. The analysis documents changes associated with agricultural expansion, urban development, and major wildfire events, including the 2017 Atlas and Nuns Fires and the 2020 LNU Lightning Complex Fire.
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. Three inch coverage is limited to the City of Napa and select portions of the surrounding Napa Valley extending northwards including Lake Hennessey. A hard copy of this data is also available directly from the GIS Team. For more information, contact gisstaff@countyofnapa.org. Extent and Resolution:This imagery encompasses approximately 82 square miles of 3-inch and 842 square miles of 6-inch Orthoimagery 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 April 30th – May 12th, 2021 Bands:3 (RGB)4th band IR is available in the raw imagery mosaic. Sensor:EagleView’s patented Pentaview camera system. For details please contact EagleView. Accuracy of Orthophotography: 3-inch GSD This data set data was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for 0.50 foot (15.24 cm) RMSEx / RMSEy Horizontal Accuracy Class, which equates to +/- 1.22 feet (37.19 cm) NSSDA 95% confidence level. 6-inch GSD This data set data was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for 1.00 foot (30.48 cm) RMSEx / RMSEy Horizontal Accuracy Class, which equates to +/- 2.44 feet (74.37 cm) NSSDA 95% confidence level. For questions regarding use and access, please contact gisstaff@countyofnapa.org.
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:Orthoimagery 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 Bands:3 (RGB)4th band IR is available in the raw imagery mosaic. Sensor: Accuracy of Orthophotography: For questions regarding use and access, please contact gisstaff@countyofnapa.org.
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:Orthoimagery and Oblique imagery within Napa County, California. Projection: Capture Window: Bands: Sensor: Accuracy of Orthophotography: For questions regarding use and access, please contact gisstaff@countyofnapa.org.
Polygon features classified as Masked, Not Masked, or Analyzed Area, with attributes including gridcode and shape area and length. Published by patrick_rea, it covers the United States of America.
uav imagery by CM, acquired 2025-08-06 to 2025-08-06, 1.8 cm per pixel, published on OpenAerialMap.
uav imagery by CM, acquired 2025-09-14 to 2025-09-14, 2.6 cm per pixel, published on OpenAerialMap.
Orthorectified imagery data for Arlington County Virginia captured in 2022. This imagery was captured in the late winter, early spring timeframe. The resolution for the imagery is 3 inches.
Orthorectified imagery data for Arlington County Virginia captured in 2017. This imagery was captured in the late winter, early spring timeframe. The resolution for the imagery is 3 inches.
Orthorectified imagery data for Arlington County Virginia captured in 2019. This imagery was captured in the late winter, early spring timeframe. The resolution for the imagery is 3 inches.
Rasters/CCAP_Land_Cover_2005_2011_EnviroAtlasVersion_HI_WM
2008 1 foot resolution aerial photos covering the City and east to 287. These are different than the 2008 DRCOG aerial photos.
Rasters/CCAP_Land_Cover_2010_2012_EnviroAtlasVersion_PRVI_WM
uav imagery by North Metro Fire Rescue District, acquired 2026-06-01 to 2026-06-01, 2.4 cm per pixel, published on OpenAerialMap.
Dates of Images: 20180914T1114, 20180914T2305, 20180915T1106, 20180915T2257, 20180917T2329, 20180918T2320, 20180919T1122, 20180919T2313 (GMT) (YYYYMMDD: HHMM) 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 Sentinel-1 (DSWx-S1) dataset. These products provide a rapid assessment of surface water extent to support emergency response and situational awareness during flood events. The dataset provided includes two products: Surface Water Extent maps on individual dates Maximum Surface Water Extent maps, showing the full extent of water observed over a defined time period Dates and Input Data: Post-event images were collected on September 14, 2018; September 15, 2018; September 17, 2018; September 18, 2018; and September 19, 2018. Two acquisitions were available on September 14, 15, and 19, with one acquired in the morning and the other in the late evening. The products were generated using OPERA DSWx-S1 satellite imagery and mosaicked across tiles to provide continuous spatial coverage. Product Description: Surface water is identified from Synthetic Aperture Radar (SAR) 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: 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-S1 Water product classifies the Sentinel-1 (S1) input imagery into "not water", "open surface water", and "inundated vegetation”, masks include Height Above Nearest Drainage (HAND) mask and layover/shadow mask), or no data classes. File names: OPERA_L3_DSWX-S1_V1_WTR_20180914T1114_mosaic.tif OPERA_L3_DSWX-S1_V1_WTR_20180914T2305_mosaic.tif OPERA_L3_DSWX-S1_V1_WTR_20180915T1106_mosaic.tif OPERA_L3_DSWX-S1_V1_WTR_20180915T2257_mosaic.tif OPERA_L3_DSWX-S1_V1_WTR_20180917T2329_mosaic.tif OPERA_L3_DSWX-S1_V1_WTR_20180918T2320_mosaic.tif OPERA_L3_DSWX-S1_V1_WTR_20180919T1122_mosaic.tif OPERA_L3_DSWX-S1_V1_WTR_20180919T2313_mosaic.tif Water (WTR) Layer Values: 0: Not Water - an area with valid data that is not open water (class 1),inundated vegetation (class 3)height above nearest drainage masked (class 250)or layover/shadow masked (class 251) (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) 3: Inundated vegetation - an area that is considered inundated, extracted from the high value in dual polarization ratio and the wetland class in land cover map. (suggested color: #00ff00) 250: Height Above Nearest Drainage (HAND) masked - an area where topographic height is higher than the HAND threshold (suggested color: #c8c8c8) 251: Layover/shadow masked - an area identified as layover or shadow computed from the geometry of the digital elevation model and sensor. The area is directly copied from input burst RTC-S1 products (suggested color: #808080) 255: No data (suggested color: transparent) Maximum Water Extent Layer Values: The maximum water extent observed during the event was created by aggregating OPERA DSWx-S1 water products. File names: ARIA-OPERA_L3_DSWX-S1_V1_WTR_20180831T2321_20180919T2313_max_extent.tif 0: Not Water. No water was detected within the time period of the images. Masked pixels are set to No data. (suggested color: #ffffff) 1: Water - an area where open water or partial surface water was detected during the time period of the images. (suggested color: #ff15e4) Satellite/Sensor/Resolution: Satellite/Sensor: Synthetic Aperture Radar (SAR) instrument on European Space Agency's (ESA) Sentinel-1A/C satellites. Spatial Resolution: 30 meters Temporal Resolution: sub-daily to bi-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_s1/MapServer/WMSServer