100+ datasets found
  1. n

    USGS High Resolution Orthoimagery

    • cmr.earthdata.nasa.gov
    • catalog.data.gov
    Updated Jan 29, 2016
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    (2016). USGS High Resolution Orthoimagery [Dataset]. https://cmr.earthdata.nasa.gov/search/concepts/C1220567548-USGS_LTA.html
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    Dataset updated
    Jan 29, 2016
    Time period covered
    Jan 1, 1970 - Present
    Area covered
    Earth
    Description

    High resolution orthorectified images combine the image characteristics of an aerial photograph with the geometric qualities of a map. An orthoimage is a uniform-scale image where corrections have been made for feature displacement such as building tilt and for scale variations caused by terrain relief, sensor geometry, and camera tilt. A mathematical equation based on ground control points, sensor calibration information, and a digital elevation model is applied to each pixel to rectify the image to obtain the geometric qualities of a map.

    A digital orthoimage may be created from several photographs mosaicked to form the final image. The source imagery may be black-and-white, natural color, or color infrared with a pixel resolution of 1-meter or finer. With orthoimagery, the resolution refers to the distance on the ground represented by each pixel.

  2. d

    Data from: Vertical Aerial Photography

    • environment.data.gov.uk
    • data.europa.eu
    Updated Oct 21, 2024
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    Environment Agency (2024). Vertical Aerial Photography [Dataset]. https://environment.data.gov.uk/dataset/dae203a8-ba24-4c54-bab0-866b9faadb58
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    Dataset updated
    Oct 21, 2024
    Dataset authored and provided by
    Environment Agency
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Vertical aerial photography is an airborne mapping technique, which uses a high-resolution camera mounted vertically underneath the aircraft to capture reflected light in the red, green, blue and for some datasets, near infra-red spectrum. Images of the ground are captured at resolutions between 10cm and 50cm, and ortho-rectified using simultaneous LIDAR and GPS to a high spatial accuracy.

    The Environment Agency has been capturing vertical aerial photography data regularly since 2006 on a project by project basis each ranging in coverage from a few square kilometers to hundreds of square kilometers. The data is available as a raster dataset in ECW (enhanced compressed wavelet) format as either a true colour (RGB), near infra-red (NIR) or a 4-band (RGBN) raster. Where imagery has been captured under incident response conditions and the lighting conditions may be sub-optimal this is defined by the prefix IR. The data are presented as tiles in British National Grid OSGB 1936 projections. Data is available in 5km download zip files for each year of survey. Within each zip file are ECW files aligned to the Ordinance Survey grid. The size of each tile is dependent upon the spatial resolution of the data.

    Please refer to the metadata index catalgoues for the survey date captured, type of survey and spatial resolution of the imagery.

  3. G

    High Resolution Satellite Imagery

    • open.canada.ca
    • catalogue.arctic-sdi.org
    • +1more
    esri rest, html
    Updated Jan 9, 2025
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    Government of Yukon (2025). High Resolution Satellite Imagery [Dataset]. https://open.canada.ca/data/en/dataset/0a14b357-8a89-6e98-720e-3a800022cb99
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    html, esri restAvailable download formats
    Dataset updated
    Jan 9, 2025
    Dataset provided by
    Government of Yukon
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    This image service contains high resolution satellite imagery for selected regions throughout the Yukon. Imagery is 1m pixel resolution, or better. Imagery was supplied by the Government of Yukon, and the Canadian Department of National Defense. All the imagery in this service is licensed. If you have any questions about Yukon government satellite imagery, please contact Geomatics.Help@gov.yk.can. This service is managed by Geomatics Yukon.

  4. High Resolution Aerial Photography of Puerto Rico and the U.S. Virgin...

    • fisheries.noaa.gov
    • cmr.earthdata.nasa.gov
    • +2more
    jpeg
    Updated Jan 1, 2002
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    Tim Battista; Matt Kendall (2002). High Resolution Aerial Photography of Puerto Rico and the U.S. Virgin Islands, 1965-1999 [Dataset]. https://www.fisheries.noaa.gov/inport/item/39463
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    jpegAvailable download formats
    Dataset updated
    Jan 1, 2002
    Dataset provided by
    National Centers for Coastal Ocean Science
    Authors
    Tim Battista; Matt Kendall
    Time period covered
    1965 - 1999
    Area covered
    Description

    Aerial photographs were acquired for the Puerto Rico and U.S. Virgin Islands Benthic Mapping Project in 1999 by NOAA Aircraft Operation Centers aircraft and National Geodetic Survey cameras and personnel. Approximately 600, color, 9 by 9 inch photos were taken of the coastal waters of Puerto Rico and the U.S. Virgin Islands at 1:48000 scale. Specific sun angle and maximum percent cloud cover re...

  5. n

    Declassified Satellite Imagery 2 (2002)

    • cmr.earthdata.nasa.gov
    • gimi9.com
    • +4more
    Updated Jan 29, 2016
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    (2016). Declassified Satellite Imagery 2 (2002) [Dataset]. https://cmr.earthdata.nasa.gov/search/concepts/C1220567575-USGS_LTA.html
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    Dataset updated
    Jan 29, 2016
    Time period covered
    Jan 1, 1970 - Present
    Area covered
    Earth
    Description

    Declassified satellite images provide an important worldwide record of land-surface change. With the success of the first release of classified satellite photography in 1995, images from U.S. military intelligence satellites KH-7 and KH-9 were declassified in accordance with Executive Order 12951 in 2002. The data were originally used for cartographic information and reconnaissance for U.S. intelligence agencies. Since the images could be of historical value for global change research and were no longer critical to national security, the collection was made available to the public.

    Keyhole (KH) satellite systems KH-7 and KH-9 acquired photographs of the Earth’s surface with a telescopic camera system and transported the exposed film through the use of recovery capsules. The capsules or buckets were de-orbited and retrieved by aircraft while the capsules parachuted to earth. The exposed film was developed and the images were analyzed for a range of military applications.

    The KH-7 surveillance system was a high resolution imaging system that was operational from July 1963 to June 1967. Approximately 18,000 black-and-white images and 230 color images are available from the 38 missions flown during this program. Key features for this program were larger area of coverage and improved ground resolution. The cameras acquired imagery in continuous lengthwise sweeps of the terrain. KH-7 images are 9 inches wide, vary in length from 4 inches to 500 feet long, and have a resolution of 2 to 4 feet.

    The KH-9 mapping program was operational from March 1973 to October 1980 and was designed to support mapping requirements and exact positioning of geographical points for the military. This was accomplished by using image overlap for stereo coverage and by using a camera system with a reseau grid to correct image distortion. The KH-9 framing cameras produced 9 x 18 inch imagery at a resolution of 20-30 feet. Approximately 29,000 mapping images were acquired from 12 missions.

    The original film sources are maintained by the National Archives and Records Administration (NARA). Duplicate film sources held in the USGS EROS Center archive are used to produce digital copies of the imagery.

  6. New Zealand 10m Satellite Imagery (2023-2024)

    • data.linz.govt.nz
    dwg with geojpeg +8
    Updated Oct 4, 2024
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    Land Information New Zealand (2024). New Zealand 10m Satellite Imagery (2023-2024) [Dataset]. https://data.linz.govt.nz/layer/120423-new-zealand-10m-satellite-imagery-2023-2024/
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    geotiff, pdf, kea, geojpeg, dwg with geojpeg, erdas imagine, jpeg2000 lossless, jpeg2000, kmlAvailable download formats
    Dataset updated
    Oct 4, 2024
    Dataset authored and provided by
    Land Information New Zealandhttps://www.linz.govt.nz/
    License

    https://data.linz.govt.nz/license/attribution-4-0-international/https://data.linz.govt.nz/license/attribution-4-0-international/

    Area covered
    Description

    This dataset provides a seamless cloud-free 10m resolution satellite imagery layer of the New Zealand mainland and offshore islands.

    The imagery was captured by the European Space Agency Sentinel-2 satellites between September 2023 - April 2024.

    Data comprises: • 450 ortho-rectified RGB GeoTIFF images in NZTM projection, tiled into the LINZ Standard 1:50000 tile layout. • Satellite sensors: ESA Sentinel-2A and Sentinel-2B • Acquisition dates: September 2023 - April 2024 • Spectral resolution: R, G, B • Spatial resolution: 10 meters • Radiometric resolution: 8-bits (downsampled from 12-bits)

    This is a visual product only. The data has been downsampled from 12-bits to 8-bits, and the original values of the images have been modified for visualisation purposes.

    If you require the 12-bit imagery (R, G, B, NIR bands), send your request to imagery@linz.govt.nz

  7. G

    Data from: Satellite Image

    • open.canada.ca
    • ouvert.canada.ca
    pdf
    Updated Mar 14, 2022
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    Natural Resources Canada (2022). Satellite Image [Dataset]. https://open.canada.ca/data/en/dataset/912a9d77-0a3f-5e0c-91f5-197ee5317e9f
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    pdfAvailable download formats
    Dataset updated
    Mar 14, 2022
    Dataset provided by
    Natural Resources Canada
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    The satellite image of Canada is a composite of several individual satellite images form the Advanced Very High Resolution Radiometre (AVHRR) sensor on board various NOAA Satellites. The colours reflect differences in the density of vegetation cover: bright green for dense vegetation in humid southern regions; yellow for semi-arid and for mountainous regions; brown for the north where vegetation cover is very sparse; and white for snow and ice. An inset map shows a satellite image mosaic of North America with 35 land cover classes, based on data from the SPOT satellite VGT (vegetation) sensor.

  8. USGS Imagery Only Base Map Service from The National Map

    • data.wu.ac.at
    • cloud.csiss.gmu.edu
    • +1more
    esri rest, wms
    Updated Feb 8, 2018
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    U.S. Geological Survey, Department of the Interior (2018). USGS Imagery Only Base Map Service from The National Map [Dataset]. https://data.wu.ac.at/schema/data_gov/OGFlMDRhZmQtZGQ0Yy00NjVhLWJhMGQtYjc4Nzg2NDY1ZmRm
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    esri rest, wmsAvailable download formats
    Dataset updated
    Feb 8, 2018
    Dataset provided by
    United States Department of the Interiorhttp://www.doi.gov/
    United States Geological Surveyhttp://www.usgs.gov/
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Area covered
    a6fa34133a576dd4279d5ed2f8bcae81b4797a78
    Description

    USGS Imagery Only is a tile cache base map of orthoimagery in The National Map visible to the 1:18,000 scale. Orthoimagery data are typically high resolution images that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a planimetric map. USGS digital orthoimage resolution may vary from 6 inches to 1 meter. In the former resolution, every pixel in an orthoimage covers a six inch square of the earth's surface, while in the latter resolution, one meter square is represented by each pixel. Blue Marble: Next Generation source is displayed at small to medium scales. However, the majority of the imagery service source is from the National Agriculture Imagery Program (NAIP) for the conterminous United States. The data is 1-meter pixel resolution with "leaf-on". Collection of NAIP imagery is administered by the U.S. Department of Agriculture's Farm Service Agency (FSA). In areas where NAIP data is not available, other imagery may be acquired through partnerships by the USGS. The National Map program is working on acquisition of high resolution orthoimagery (HRO) for Alaska and Hawaii. Most of the new Alaska imagery data will not be available in this service due to license restrictions. The National Map viewer allows free downloads of public domain, 1-meter resolution orthoimagery in JPEG 2000 (jp2) format for the conterminous United States, with many urban areas and other locations at 1-foot (or better) resolution also in JPEG 2000 (jp2) format. For scales below 1:18,000, use the dynamic USGS Imagery Only Large service, https://services.nationalmap.gov/arcgis/rest/services/USGSImageOnlyLarge/MapServer.

  9. w

    Statewide NAIP 2017 3ft 4band Imagery

    • geo.wa.gov
    • hub.arcgis.com
    Updated Jan 1, 2017
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    Washington State Geospatial Portal (2017). Statewide NAIP 2017 3ft 4band Imagery [Dataset]. https://geo.wa.gov/datasets/785aa8e8876c4b8b9ed54e9816fb02c4
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    Dataset updated
    Jan 1, 2017
    Dataset authored and provided by
    Washington State Geospatial Portal
    Area covered
    Earth
    Description

    The USGS NAIP Imagery service from The National Map consists of 4-band high resolution images that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a map. Resolution of National Agriculture Imagery Program (NAIP) data is most commonly 1 meter, which means that every pixel in the digital orthoimage covers a one meter square of the earth’s surface. Some states to include Wyoming and New York began collection of 0.5 meter pixel resolution NAIP in 2015. Many states contribute orthoimagery to The National Map, and USGS relies on a partnership with the U.S. Department of Agriculture’s Farm Service Agency for NAIP data. The USGS NAIP Imagery service is a mosaic of natural color and color infrared (4-band) aerial imagery, containing NAIP and other imagery sources to complete the mosaic. The National Map download client allows free downloads of public domain compressed orthoimagery in JPEG 2000 (.jp2) format for the conterminous United States, with many urban areas and other locations at 1-foot (or better) resolution, also in JPEG 2000 (.jp2) format. For additional information on orthoimagery, go to https://nationalmap.gov/ortho.html. This imagery service is for viewing only, no downloading of the raster images available. NAIP/Statewide_NAIP_2017_3ft_4band_wsps_83h_img

  10. The WorldStrat Dataset: Open High-Resolution Satellite Imagery With Paired...

    • zenodo.org
    application/gzip, csv +2
    Updated Jul 16, 2024
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    Julien Cornebise; Julien Cornebise; Ivan Oršolić; Ivan Oršolić; Freddie Kalaitzis; Freddie Kalaitzis (2024). The WorldStrat Dataset: Open High-Resolution Satellite Imagery With Paired Multi-Temporal Low-Resolution [Dataset]. http://doi.org/10.5281/zenodo.6810792
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    csv, application/gzip, txt, pdfAvailable download formats
    Dataset updated
    Jul 16, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Julien Cornebise; Julien Cornebise; Ivan Oršolić; Ivan Oršolić; Freddie Kalaitzis; Freddie Kalaitzis
    Description

    What is this dataset?

    Nearly 10,000 km² of free high-resolution and matched low-resolution satellite imagery of unique locations which ensure stratified representation of all types of land-use across the world: from agriculture to ice caps, from forests to multiple urbanization densities.

    Those locations are also enriched with typically under-represented locations in ML datasets: sites of humanitarian interest, illegal mining sites, and settlements of persons at risk.

    Each high-resolution image (1.5 m/pixel) comes with multiple temporally-matched low-resolution images from the freely accessible lower-resolution Sentinel-2 satellites (10 m/pixel).

    We accompany this dataset with a paper, datasheet for datasets and an open-source Python package to: rebuild or extend the WorldStrat dataset, train and infer baseline algorithms, and learn with abundant tutorials, all compatible with the popular EO-learn toolbox.

    Why make this?

    We hope to foster broad-spectrum applications of ML to satellite imagery, and possibly develop the same power of analysis allowed by costly private high-resolution imagery from free public low-resolution Sentinel2 imagery. We illustrate this specific point by training and releasing several highly compute-efficient baselines on the task of Multi-Frame Super-Resolution.

    Licences

    • The high-resolution Airbus imagery is distributed, with authorization from Airbus, under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).
    • The labels, Sentinel2 imagery, and trained weights are released under Creative Commons with Attribution 4.0 International (CC BY 4.0).
    • The source code (will be shortly released on GitHub) under 3-Clause BSD license.
  11. d

    NSW Imagery

    • data.gov.au
    • data.nsw.gov.au
    • +1more
    esri mapserver, pdf +3
    Updated Sep 16, 2024
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    Spatial Services (DCS) (2024). NSW Imagery [Dataset]. https://data.gov.au/dataset/ds-nsw-88b00529-bc95-4dde-b5f0-662b3086eb45
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    pdf, url, xml, wms, esri mapserverAvailable download formats
    Dataset updated
    Sep 16, 2024
    Dataset provided by
    Spatial Services (DCS)
    Area covered
    New South Wales
    Description

    The NSW Imagery web service provides access to a repository of the Spatial Services (DCS) maintained standard imagery covering NSW, plus additional sourced imagery. It depicts an imagery map of NSW …Show full descriptionThe NSW Imagery web service provides access to a repository of the Spatial Services (DCS) maintained standard imagery covering NSW, plus additional sourced imagery. It depicts an imagery map of NSW showing a selection of LANDSAT® satellite imagery, standard 50cm orthorectified imageries, High resolution 10cm Town Imageries. It also contains high resolution imageries within multiple areas of NSW within DFSI, Spatial Services maintained projects and captured by AAM, VEKTA and Jacobs (previously SKM). The image web service is updated periodically when new imageries are available. The imageries are shown progressively from scales larger than 1:150,000 higher resolution imagery overlays lower resolution imagery and most recent imagery overlays older imagery within each resolution. The characteristics of each image such as accuracy, resolution, viewing scale, image format etc varies by sensor, location, capture methodology, source and processing. For specific information about the metadata for the imagery used, please refer to the individual data series within the NSW Data Catalogue. As a consequence of the variety of source data, each map displayed by the user within this map service may have a number of copyright permissions. It is emphasised that the user should check the use constraints for each image data series. NOTE: Please contact the Customer HUB https://customerhub.spatial.nsw.gov.au/ for advice on datasets access.

  12. a

    Aerial Imagery 2010

    • hub.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +1more
    Updated May 14, 2010
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    Florida Department of Environmental Protection (2010). Aerial Imagery 2010 [Dataset]. https://hub.arcgis.com/datasets/391b0a1f180c499983f3bf588cee1526
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    Dataset updated
    May 14, 2010
    Dataset authored and provided by
    Florida Department of Environmental Protection
    Area covered
    Description

    1 ft ortho rectified imagery for the counties flown in the October 2009 - April 2010 flight acquistion cycle. This imagery layer was rebuilt in ArcGIS 10.2 as a raster mosaic dataset using MrSID imagery for the data source and published in ArcGIS Server 10.2 as a Image Service. This dataset has been published as an ArcGIS Server Image Service for easier maintenance and improved performance. Counties included in this dataset are: Bay, Calhoun, Charlotte (partial), Citrus, Columbia, Dixie, Escambia, Franklin, Gadsden, Gilchrist, Gulf, Hamilton, Hernando, Hillsborough, Jackson, Jefferson, Lafayette, Levy (partial), Madison, Manatee, Marion (partial), Okaloosa, Pasco, Pinellas, Santa Rosa, Sarasota, Suwannee, Taylor, Wakulla, and Washington. Please contact GIS.Librarian@FloridaDEP.gov for more information.

  13. n

    QuickBird full archive

    • cmr.earthdata.nasa.gov
    • fedeo.ceos.org
    • +1more
    not provided
    Updated Apr 24, 2025
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    (2025). QuickBird full archive [Dataset]. https://cmr.earthdata.nasa.gov/search/concepts/C1965336934-ESA.html
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    not providedAvailable download formats
    Dataset updated
    Apr 24, 2025
    Time period covered
    Nov 1, 2001 - Mar 31, 2015
    Area covered
    Earth
    Description

    QuickBird high resolution optical products are available as part of the Maxar Standard Satellite Imagery products from the QuickBird, WorldView-1/-2/-3/-4, and GeoEye-1 satellites. All details about the data provision, data access conditions and quota assignment procedure are described into the Terms of Applicability available in Resources section.

    In particular, QuickBird offers archive panchromatic products up to 0.60 m GSD resolution and 4-Bands Multispectral products up to 2.4 m GSD resolution.

    Band Combination Data Processing Level Resolution Panchromatic and 4-bands Standard(2A)/View Ready Standard (OR2A) 15 cm HD, 30 cm HD, 30 cm, 40 cm, 50/60 cm View Ready Stereo 30 cm, 40 cm, 50/60 cm Map-Ready (Ortho) 1:12,000 Orthorectified 15 cm HD, 30 cm HD, 30 cm, 40 cm, 50/60 cm

    4-Bands being an option from:

    4-Band Multispectral (BLUE, GREEN, RED, NIR1) 4-Band Pan-sharpened (BLUE, GREEN, RED, NIR1) 4-Band Bundle (PAN, BLUE, GREEN, RED, NIR1) 3-Bands Natural Colour (pan-sharpened BLUE, GREEN, RED) 3-Band Colored Infrared (pan-sharpened GREEN, RED, NIR1) Natural Colour / Coloured Infrared (3-Band pan-sharpened) Native 30 cm and 50/60 cm resolution products are processed with MAXAR HD Technology to generate respectively the 15 cm HD and 30 cm HD products: the initial special resolution (GSD) is unchanged but the HD technique intelligently increases the number of pixels and improves the visual clarity achieving aesthetically refined imagery with precise edges and well reconstructed details.

  14. d

    Aerial imagery data of the Colorado River Corridor, Arizona - 2021

    • catalog.data.gov
    Updated Jul 6, 2024
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    U.S. Geological Survey (2024). Aerial imagery data of the Colorado River Corridor, Arizona - 2021 [Dataset]. https://catalog.data.gov/dataset/aerial-imagery-data-of-the-colorado-river-corridor-arizona-2021
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Colorado River, Arizona
    Description

    In May 2021, the Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey’s (USGS), Southwest Biological Science Center (SBSC) acquired airborne multispectral high resolution data for the Colorado River in Grand Canyon in Arizona, USA. The imagery data consist of four bands (Band 1 – red, Band 2 – green, Band 3 – blue, and Band 4 – near infrared) with a ground resolution of 20 centimeters (cm). These image data are available to the public as 16-bit GeoTIFF files, which can be read and used by most geographic information system (GIS) and image-processing software. The spatial reference of the image data are in the State Plane (SP) map projection using the central Arizona zone (FIPS 0202) and the North American Datum of 1983 (NAD83) National Adjustment of 2011 (NA2011). The airborne data acquisition was conducted under contract by Fugro Earthdata Inc (Fugro) using two fixed wing aircraft from May 29th to June 4th, 2021 at flight altitudes from approximately 2,440 to 3,350 meters above mean sea level. Fugro produced a corridor-wide mosaic using the best possible flight line images with the least amount of smear, the smallest shadow extent, and clearest, most glint-free water possible. The mosaic delivered by Fugro was then further corrected by GCMRC for smear, shadow extent and water clarity as described in the process steps of this metadata and for previous image acquisitions in Durning et al. (2016) and Davis (2012). 47 ground controls points (GCPs) were used to conduct an independent spatial accuracy assessment by GCMRC. The accuracy calculated from the GCPs is reported at 95% confidence as 0.514 m and a Root Mean Square Error (RMSE) of 0.297 m.

  15. w

    NAIP 2005 2m Color Imagery

    • geo.wa.gov
    • data-wutc.opendata.arcgis.com
    Updated Jan 1, 2005
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    Washington State Geospatial Portal (2005). NAIP 2005 2m Color Imagery [Dataset]. https://geo.wa.gov/datasets/4ce9c7f04fca4dec96b8b1078e730733
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    Dataset updated
    Jan 1, 2005
    Dataset authored and provided by
    Washington State Geospatial Portal
    Area covered
    Earth
    Description

    The USGS NAIP Imagery service from The National Map consists of 4-band high resolution images that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a map. Resolution of National Agriculture Imagery Program (NAIP) data is most commonly 1 meter, which means that every pixel in the digital orthoimage covers a one meter square of the earth’s surface. Some states to include Wyoming and New York began collection of 0.5 meter pixel resolution NAIP in 2015. Many states contribute orthoimagery to The National Map, and USGS relies on a partnership with the U.S. Department of Agriculture’s Farm Service Agency for NAIP data. The USGS NAIP Imagery service is a mosaic of natural color and color infrared (4-band) aerial imagery, containing NAIP and other imagery sources to complete the mosaic. The National Map download client allows free downloads of public domain compressed orthoimagery in JPEG 2000 (.jp2) format for the conterminous United States, with many urban areas and other locations at 1-foot (or better) resolution, also in JPEG 2000 (.jp2) format. For additional information on orthoimagery, go to https://nationalmap.gov/ortho.html. This imagery service is for viewing only, no downloading of the raster images available. NAIP/NAIP_2005_2m_color_wsps_83h_img

  16. New Jersey Statewide Digital Aerial Imagery Catalog

    • registry.opendata.aws
    Updated Jul 9, 2020
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    The New Jersey Office of GIS, NJ Office of Information Technology (2020). New Jersey Statewide Digital Aerial Imagery Catalog [Dataset]. https://registry.opendata.aws/nj-imagery/
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    Dataset updated
    Jul 9, 2020
    Dataset provided by
    New Jersey Office of Information Technologyhttp://www.state.nj.us/it/
    Area covered
    New Jersey
    Description

    The New Jersey Office of GIS, NJ Office of Information Technology manages a series of 11 digital orthophotography and scanned aerial photo maps collected at various years ranging from 1930 to 2017. Each year’s worth of imagery are available as Cloud Optimized GeoTIFF (COG) files and some years are available as compressed MrSID and/or JP2 files. Additionally, each year of imagery is organized into a tile grid scheme covering the entire geography of New Jersey. Many years share the same tiling grid while others have unique grids as defined by the project at the time.

  17. Sentinel-2 Satellite Imagery - Samoa

    • samoa-data.sprep.org
    • niue-data.sprep.org
    • +10more
    zip
    Updated Feb 15, 2022
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    European Space Agency (ESA) (2022). Sentinel-2 Satellite Imagery - Samoa [Dataset]. https://samoa-data.sprep.org/dataset/sentinel-2-satellite-imagery-samoa
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    zip(234415159)Available download formats
    Dataset updated
    Feb 15, 2022
    Dataset provided by
    Pacific Regional Environment Programmehttps://www.sprep.org/
    Authors
    European Space Agency (ESA)
    License

    Public Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
    License information was derived automatically

    Area covered
    Samoa, POLYGON ((187.0565700531 -14.238178463369, 188.69353294373 -14.238178463369)), 187.0565700531 -13.229668723175, 188.69353294373 -13.229668723175
    Description

    SENTINEL-2 is a wide-swath, high-resolution, multi-spectral imaging mission, supporting Copernicus Land Monitoring studies, including the monitoring of vegetation, soil and water cover, as well as observation of inland waterways and coastal areas.

    The SENTINEL-2 Multispectral Instrument (MSI) samples 13 spectral bands: four bands at 10 metres, six bands at 20 metres and three bands at 60 metres spatial resolution.

    The acquired data, mission coverage and high revisit frequency provides for the generation of geoinformation at local, regional, national and international scales. The data is designed to be modified and adapted by users interested in thematic areas such as: • spatial planning • agro-environmental monitoring • water monitoring • forest and vegetation monitoring • land carbon, natural resource monitoring • global crop monitoring

  18. n

    NEON (National Ecological Observatory Network) High-resolution...

    • data.neonscience.org
    zip
    Updated Jun 15, 2023
    + more versions
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    (2023). NEON (National Ecological Observatory Network) High-resolution orthorectified camera imagery mosaic (DP3.30010.001) [Dataset]. https://data.neonscience.org/data-products/DP3.30010.001
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    zipAvailable download formats
    Dataset updated
    Jun 15, 2023
    License

    https://www.neonscience.org/data-samples/data-policies-citationhttps://www.neonscience.org/data-samples/data-policies-citation

    Time period covered
    Jun 2013 - Jun 2025
    Area covered
    SJER, WOOD, TEAK, LIRO, JERC, UNDE, ABBY, CLBJ, CPER, GUAN
    Description

    Level 1 high-resolution orthorectified camera images are mosaiced and tiled into 1 km by 1 km data sets. Mosiac is output onto a fixed, uniform spatial grid using nearest-neighbor resampling; spatial resolution is at least 0.1 m.

  19. N

    Nordics Satellite Imagery Services Market Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Dec 15, 2024
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    Data Insights Market (2024). Nordics Satellite Imagery Services Market Report [Dataset]. https://www.datainsightsmarket.com/reports/nordics-satellite-imagery-services-market-14598
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    pdf, doc, pptAvailable download formats
    Dataset updated
    Dec 15, 2024
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Nordic countries, Global
    Variables measured
    Market Size
    Description

    The Nordics satellite imagery services market is projected to grow from $0.22 million in 2025 to $0.96 million by 2033, exhibiting a CAGR of 13.62% during the forecast period. The increasing adoption of satellite imagery for various applications, such as geospatial data acquisition and mapping, natural resource management, and surveillance and security, is driving the market growth. Moreover, the expanding construction and transportation & logistics sectors in the region are further boosting the demand for satellite imagery services. Key trends shaping the Nordics satellite imagery services market include:

    Growing adoption of cloud-based platforms and services for satellite imagery processing and analysis: This trend is enabling end-users to access satellite imagery data and services without the need for significant upfront investments in infrastructure. Increasing availability of high-resolution satellite imagery: The launch of new satellites and the development of new image processing technologies are making it possible to obtain high-resolution satellite imagery, which is essential for a variety of applications, such as mapping and land use planning. Emergence of new applications for satellite imagery: Satellite imagery is increasingly being used for a variety of new applications, such as environmental monitoring, disaster management, and precision agriculture. These new applications are creating new opportunities for growth in the Nordics satellite imagery services market. Recent developments include: May 2023 - Business Finland granted EUR 30 million (USD 32.75 million) loan funding for ICEYE's product development project based on innovative new sensor and space technology that will provide real-time and reliable information to support decision-making worldwide. The project aims to create a unique information and software platform, design and develop technology for next-generation satellites, and apply the high-accuracy information from satellites globally for natural catastrophe analysis, modeling, and decision-making., March 2023 - Norway's International Climate and Forest Initiative (NICFI) announced that NICFI's satellite data program is extended until September 2023. Norway's International Climate and Forest Initiative (NICFI) grant free access to high-resolution satellite imagery of the tropics to anyone, anywhere, to monitor tropical deforestation. Through Norway's International Climate & Forests Initiative, users can access the planet's high-resolution, analysis-ready satellite images of the world's tropics to help reduce and combat climate change and reverse the loss of tropical forests.. Key drivers for this market are: Increasing Demand among Various End-user Industries, notablly in Forestry Sector, Adoption of Big Data and Imagery Analytics. Potential restraints include: High Cost of Satellite Imaging Data Acquisition and Processing. Notable trends are: Forestry and Agriculture is Analyzed to Hold Significant Market Share.

  20. P

    AID Dataset

    • paperswithcode.com
    Updated May 15, 2021
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    Gui-Song Xia; Jingwen Hu; Fan Hu; Baoguang Shi; Xiang Bai; Yanfei Zhong; Liangpei Zhang (2021). AID Dataset [Dataset]. https://paperswithcode.com/dataset/aid
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    Dataset updated
    May 15, 2021
    Authors
    Gui-Song Xia; Jingwen Hu; Fan Hu; Baoguang Shi; Xiang Bai; Yanfei Zhong; Liangpei Zhang
    Description

    AID is a new large-scale aerial image dataset, by collecting sample images from Google Earth imagery. Note that although the Google Earth images are post-processed using RGB renderings from the original optical aerial images, it has proven that there is no significant difference between the Google Earth images with the real optical aerial images even in the pixel-level land use/cover mapping. Thus, the Google Earth images can also be used as aerial images for evaluating scene classification algorithms.

    The new dataset is made up of the following 30 aerial scene types: airport, bare land, baseball field, beach, bridge, center, church, commercial, dense residential, desert, farmland, forest, industrial, meadow, medium residential, mountain, park, parking, playground, pond, port, railway station, resort, river, school, sparse residential, square, stadium, storage tanks and viaduct. All the images are labelled by the specialists in the field of remote sensing image interpretation, and some samples of each class are shown in Fig.1. In all, the AID dataset has a number of 10000 images within 30 classes.

    The images in AID are actually multi-source, as Google Earth images are from different remote imaging sensors. This brings more challenges for scene classification than the single source images like UC-Merced dataset. Moreover, all the sample images per each class in AID are carefully chosen from different countries and regions around the world, mainly in China, the United States, England, France, Italy, Japan, Germany, etc., and they are extracted at different time and seasons under different imaging conditions, which increases the intra-class diversities of the data.

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(2016). USGS High Resolution Orthoimagery [Dataset]. https://cmr.earthdata.nasa.gov/search/concepts/C1220567548-USGS_LTA.html

USGS High Resolution Orthoimagery

HRO_Not provided

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37 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jan 29, 2016
Time period covered
Jan 1, 1970 - Present
Area covered
Earth
Description

High resolution orthorectified images combine the image characteristics of an aerial photograph with the geometric qualities of a map. An orthoimage is a uniform-scale image where corrections have been made for feature displacement such as building tilt and for scale variations caused by terrain relief, sensor geometry, and camera tilt. A mathematical equation based on ground control points, sensor calibration information, and a digital elevation model is applied to each pixel to rectify the image to obtain the geometric qualities of a map.

A digital orthoimage may be created from several photographs mosaicked to form the final image. The source imagery may be black-and-white, natural color, or color infrared with a pixel resolution of 1-meter or finer. With orthoimagery, the resolution refers to the distance on the ground represented by each pixel.

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