100+ datasets found
  1. G

    High Resolution Satellite Imagery

    • open.canada.ca
    • catalogue.arctic-sdi.org
    • +1more
    esri rest, html
    Updated Jan 9, 2025
    + more versions
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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.

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

    • data.linz.govt.nz
    dwg with geojpeg +8
    Updated Oct 4, 2024
    + more versions
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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

  3. n

    Declassified Satellite Imagery 2 (2002)

    • cmr.earthdata.nasa.gov
    • gimi9.com
    • +3more
    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.

  4. G

    Data from: Satellite Image

    • open.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.

  5. d

    CORONA Satellite Photography

    • catalog.data.gov
    • gimi9.com
    • +4more
    Updated Apr 10, 2025
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    DOI/USGS/EROS (2025). CORONA Satellite Photography [Dataset]. https://catalog.data.gov/dataset/corona-satellite-photography
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    Dataset updated
    Apr 10, 2025
    Dataset provided by
    DOI/USGS/EROS
    Description

    On February 24, 1995, President Clinton signed an Executive Order, directing the declassification of intelligence imagery acquired by the first generation of United States photo-reconnaissance satellites, including the systems code-named CORONA, ARGON, and LANYARD. More than 860,000 images of the Earth's surface, collected between 1960 and 1972, were declassified with the issuance of this Executive Order. Image collection was driven, in part, by the need to confirm purported developments in then-Soviet strategic missile capabilities. The images also were used to produce maps and charts for the Department of Defense and for other Federal Government mapping programs. In addition to the images, documents and reports (collateral information) are available, pertaining to frame ephemeris data, orbital ephemeris data, and mission performance. Document availability varies by mission; documentation was not produced for unsuccessful missions.

  6. Landsat 8 Satellite Imagery Collection 1 - Papua New Guinea

    • png-data.sprep.org
    • pacific-data.sprep.org
    zip
    Updated Feb 15, 2022
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    United States Geological Survey and National Aeronautics and Space Administration (2022). Landsat 8 Satellite Imagery Collection 1 - Papua New Guinea [Dataset]. https://png-data.sprep.org/dataset/landsat-8-satellite-imagery-collection-1-papua-new-guinea
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    zip(5852463504)Available download formats
    Dataset updated
    Feb 15, 2022
    Dataset provided by
    Pacific Regional Environment Programmehttps://www.sprep.org/
    Authors
    United States Geological Survey and National Aeronautics and Space Administration
    License

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

    Area covered
    142.3656463623 -10.093262015308)), 149.3968963623 -0.8733792609738, 146.4965057373 -1.4884800029826, 155.0658416748 -9.3569327887185, 153.3959197998 -2.9375549775994, 156.3842010498 -6.0913976976422, 140.7396697998 -6.4408592866477, 154.7142791748 -2.6303012095641, 155.1976776123 -11.775947798478, 142.6732635498 -1.2248822742251, Papua New Guinea
    Description

    Since 1972, the joint NASA/ U.S. Geological Survey Landsat series of Earth Observation satellites have continuously acquired images of the Earth’s land surface, providing uninterrupted data to help land managers and policymakers make informed decisions about natural resources and the environment.

    Landsat is a part of the USGS National Land Imaging (NLI) Program. To support analysis of the Landsat long-term data record that began in 1972, the USGS. Landsat data archive was reorganized into a formal tiered data collection structure. This structure ensures all Landsat Level 1 products provide a consistent archive of known data quality to support time-series analysis and data “stacking”, while controlling continuous improvement of the archive, and access to all data as they are acquired. Collection 1 Level 1 processing began in August 2016 and continued until all archived data was processed, completing May 2018. Newly-acquired Landsat 8 and Landsat 7 data continue to be processed into Collection 1 shortly after data is downlinked to USGS EROS.

    Acknowledgement or credit of the USGS as data source should be provided by including a line of text citation such as the example shown below. (Product, Image, Photograph, or Dataset Name) courtesy of the U.S. Geological Survey Example: Landsat-8 image courtesy of the U.S. Geological Survey

  7. g

    Ontario Imagery Web Map Service (OIWMS)

    • geohub.lio.gov.on.ca
    • hub.arcgis.com
    Updated Mar 31, 2014
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    Land Information Ontario (2014). Ontario Imagery Web Map Service (OIWMS) [Dataset]. https://geohub.lio.gov.on.ca/maps/101295c5d3424045917bdd476f322c02
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    Dataset updated
    Mar 31, 2014
    Dataset authored and provided by
    Land Information Ontario
    License

    https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario

    Area covered
    Description

    The Ontario Imagery Web Map Service (OIWMS) is an open data service available to everyone free of charge. It provides instant online access to the most recent, highest quality, province wide imagery. GEOspatial Ontario (GEO) makes this data available as an Open Geospatial Consortium (OGC) compliant web map service or as an ArcGIS map service. Imagery was compiled from many different acquisitions which are detailed in the Ontario Imagery Web Map Service Metadata Guide linked below. Instructions on how to use the service can also be found in the Imagery User Guide linked below.Note: This map displays the Ontario Imagery Web Map Service Source, a companion ArcGIS web map service to the Ontario Imagery Web Map Service. It provides an overlay that can be used to identify acquisition relevant information such as sensor source and acquisition date. OIWMS contains several hierarchical layers of imagery, with coarser less detailed imagery that draws at broad scales, such as a province wide zooms, and finer more detailed imagery that draws when zoomed in, such as city-wide zooms. The attributes associated with this data describes at what scales (based on a computer screen) the specific imagery datasets are visible.Available ProductsOntario Imagery OCG Web Map Service – public linkOntario Imagery ArcGIS Map Service – public linkOntario Imagery Web Map Service Source – public linkOntario Imagery ArcGIS Map Service – OPS internal linkOntario Imagery Web Map Service Source – OPS internal linkAdditional DocumentationOntario Imagery Web Map Service Metadata Guide (PDF)Imagery User Guide (Word)StatusCompleted: Production of the data has been completedMaintenance and Update FrequencyAnnually: Data is updated every yearContactOntario Ministry of Natural Resources, Geospatial Ontario, imagery@ontario.ca

  8. 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.

  9. 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.

  10. Orthoimages of Canada, 1999-2003

    • open.canada.ca
    • catalogue.arctic-sdi.org
    • +1more
    geotif, gml, kmz, pdf +2
    Updated Aug 11, 2021
    + more versions
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    Natural Resources Canada (2021). Orthoimages of Canada, 1999-2003 [Dataset]. https://open.canada.ca/data/en/dataset/560351c7-061f-442f-9539-e38bb453ccbf
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    geotif, wms, shp, pdf, gml, kmzAvailable download formats
    Dataset updated
    Aug 11, 2021
    Dataset provided by
    Ministry of Natural Resources of Canadahttps://www.nrcan.gc.ca/
    License

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

    Time period covered
    Jan 1, 1999 - Jan 1, 2003
    Area covered
    Canada
    Description

    This collection is a legacy product that is no longer supported. It may not meet current government standards. This inventory presents chronologically the satellite images acquired, orthorectified and published over time by Natural Resources Canada. It is composed of imagery from the Landsat7 (1999-2003) and RADARSAT-1 (2001-2002) satellites, as well as the CanImage by-product and the control points used to process the images. Landsat7 Orthorectified Imagery: The orthoimage dataset is a complete set of cloud-free (less than 10%) orthoimages covering the Canadian landmass and created with the most accurate control data available at the time of creation. RADARSAT-1 Orthorectified Imagery: The 5 RADARSAT-1 images (processed and distributed by RADARSAT International (RSI) complete the landsat 7 orthoimagery coverage. They are stored as raster data produced from SAR Standard 7 (S7) beam mode with a pixel size of 15 m. They have been produced in accordance with NAD83 (North American Datum of 1983) using the Universal Transverse Mercator (UTM) projection. RADARSAT-1 orthoimagery were produced with the 1:250 000 Canadian Digital Elevation Data (CDED) and photogrammetric control points generated from the Aerial Survey Data Base (ASDB). CanImage -Landsat7 Orthoimages of Canada,1:50 000: CanImage is a raster image containing information from Landsat7 orthoimages that have been resampled and based on the National Topographic System (NTS) at the 1:50 000 scale in the UTM projection. The product is distributed in datasets in GeoTIFF format. The resolution of this product is 15 metres. Landsat7 Imagery Control Points: the control points were used for the geometric correction of Landsat7 satellite imagery. They can also be used to correct vector data and for simultaneously displaying data from several sources prepared at different scales or resolutions.

  11. d

    Landsat 7 ETM/1G satellite imagery - Hawaiian Islands cloud-free mosaics

    • catalog.data.gov
    • datadiscoverystudio.org
    • +2more
    Updated May 22, 2025
    + more versions
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    (Point of Contact, Custodian) (2025). Landsat 7 ETM/1G satellite imagery - Hawaiian Islands cloud-free mosaics [Dataset]. https://catalog.data.gov/dataset/landsat-7-etm-1g-satellite-imagery-hawaiian-islands-cloud-free-mosaics6
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    Dataset updated
    May 22, 2025
    Dataset provided by
    (Point of Contact, Custodian)
    Area covered
    Hawaiian Islands, Hawaii
    Description

    Cloud-free Landsat satellite imagery mosaics of the islands of the main 8 Hawaiian Islands (Hawaii, Maui, Kahoolawe, Lanai, Molokai, Oahu, Kauai and Niihau). Landsat 7 ETM (enhanced thematic mapper) is a polar orbiting 8 band multispectral satellite-borne sensor. The ETM+ instrument provides image data from eight spectral bands. The spatial resolution is 30 meters for the visible and near-infrared (bands 1-5 and 7). Resolution for the panchromatic (band 8) is 15 meters, and the thermal infrared (band 6) is 60 meters. The approximate scene size is 170 x 183 kilometers (106 x 115 miles). A Nadir-looking system, the sensor has provided continuous coverage since July 1999, with a 16-day repeat cycle. The Level 1G product is radiometrically and geometrically corrected (systematic) to the user-specified parameters including output map projection, image orientation, pixel grid-cell size, and resampling kernel. The correctional gorithms model the spacecraft and sensor using data generated by onboard computers during imaging. Sensor, focal plane, and detector alignment information provided by the Image Assessment System (IAS) in the Calibration Parameter File (CPF) is also used to improve the overall geometric fidelity. The resulting product is free from distortions related to the sensor (e.g., jitter, view angle effect), satellite (e.g., attitude deviations from nominal), and Earth (e.g., rotation, curvature). Residual error in the systematic L1G product is less than 250 meters (1 sigma) inflat areas at sea level. The systematic L1G correction process does not employ ground control or relief models to attain absolute geodetic accuracy.

  12. n

    CORONA Satellite Photographs from the U.S. Geological Survey

    • cmr.earthdata.nasa.gov
    • data.nasa.gov
    • +2more
    not provided
    Updated Dec 28, 2022
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    (2022). CORONA Satellite Photographs from the U.S. Geological Survey [Dataset]. https://cmr.earthdata.nasa.gov/search/concepts/C1220566377-USGS_LTA.html
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    not providedAvailable download formats
    Dataset updated
    Dec 28, 2022
    Time period covered
    Aug 1, 1960 - May 31, 1972
    Area covered
    Earth
    Description

    The first generation of U.S. photo intelligence satellites collected more than 860,000 images of the Earth’s surface between 1960 and 1972. The classified military satellite systems code-named CORONA, ARGON, and LANYARD acquired photographic images from space and returned the film to Earth for processing and analysis.

    The images were originally used for reconnaissance and to produce maps for U.S. intelligence agencies. In 1992, an Environmental Task Force evaluated the application of early satellite data for environmental studies. Since the CORONA, ARGON, and LANYARD data were no longer critical to national security and could be of historical value for global change research, the images were declassified by Executive Order 12951 in 1995.

    The first successful CORONA mission was launched from Vandenberg Air Force Base in 1960. The satellite acquired photographs with a telescopic camera system and loaded the exposed film into 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 intelligence community used Keyhole (KH) designators to describe system characteristics and accomplishments. The CORONA systems were designated KH-1, KH-2, KH-3, KH-4, KH-4A, and KH-4B. The ARGON systems used the designator KH-5 and the LANYARD systems used KH-6. Mission numbers were a means for indexing the imagery and associated collateral data.

    A variety of camera systems were used with the satellites. Early systems (KH-1, KH-2, KH-3, and KH-6) carried a single panoramic camera or a single frame camera (KH-5). The later systems (KH-4, KH-4A, and KH-4B) carried two panoramic cameras with a separation angle of 30° with one camera looking forward and the other looking aft.

    The original film and technical mission-related documents 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.

    Mathematical calculations based on camera operation and satellite path were used to approximate image coordinates. Since the accuracy of the coordinates varies according to the precision of information used for the derivation, users should inspect the preview image to verify that the area of interest is contained in the selected frame. Users should also note that the images have not been georeferenced.

  13. 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.
  14. LINZ Aerial Imagery Basemap - Web Mercator

    • data-smpdc.opendata.arcgis.com
    • opendata.rcmrd.org
    Updated Jun 10, 2021
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    Land Information New Zealand (2021). LINZ Aerial Imagery Basemap - Web Mercator [Dataset]. https://data-smpdc.opendata.arcgis.com/maps/850d6096d89b48228a0638842fa3801c
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    Dataset updated
    Jun 10, 2021
    Dataset authored and provided by
    Land Information New Zealandhttps://www.linz.govt.nz/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    An aerial imagery basemap of New Zealand in Web Mercator (WGS 1984) using the latest quality data from Land Information New Zealand.Add the map service directly to your ArcGIS Online map, or copy the Web Map Tile Service (WMTS) URL below for use in the desktop.This basemap is also available in NZTM from: https://linz.maps.arcgis.com/home/item.html?id=39cf07ebf8a2413696d8fd4d80570b84 The LINZ Aerial Imagery Basemap details New Zealand in high resolution - from a nationwide view all the way down to individual buildings.This basemap combines the latest high-resolution aerial imagery down to 5cm in urban areas and 10m satellite imagery to provide full coverage of mainland New Zealand, Chathams and other offshore islands.LINZ Basemaps are powered by data from the LINZ Data Service and other authoritative open data sources, providing you with a basemap that is free to use under an open licence.A XYZ tile API (Web Mercator only) is also available for use in web and mobile applications.See more information or provide your feedback at https://basemaps.linz.govt.nz/.For attribution requirements and data sources see: https://www.linz.govt.nz/data/linz-data/linz-basemaps/data-attribution.

  15. Global commercial satellite imagery data cost 2022, by cost per square...

    • statista.com
    Updated Jul 12, 2022
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    Statista (2022). Global commercial satellite imagery data cost 2022, by cost per square kilometer [Dataset]. https://www.statista.com/statistics/1293877/commercial-satellite-imagery-cost-worldwide/
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    Dataset updated
    Jul 12, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Worldwide
    Description

    The cost of acquiring a satellite data was highest for the images from the GeoEye-1 satellite at 25 U.S. dollars per square kilometer of the image. Most of the satellite data have a minimum order quantities based on the company and the cost depends mostly on the spatial resolution of the satellite image.

    Most of the satellites are commercially owned and provide users with data as an end product based on the requirement. Processing smaller patches of the raw images obtained from a satellite to an end product are not profitable. Hence, there is a minimum order limit of 25 to 50 square kilometers based on the requested product.

  16. NZ 10m Satellite Imagery (2020-2021)

    • geodata.nz
    • data.linz.govt.nz
    Updated 2021
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    Toitū Te Whenua Land Information New Zealand (2021). NZ 10m Satellite Imagery (2020-2021) [Dataset]. https://geodata.nz/geonetwork/srv/api/records/8eb716be-fcac-da53-e424-816b335cf8f6
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    Dataset updated
    2021
    Dataset provided by
    Land Information New Zealandhttps://www.linz.govt.nz/
    Authors
    Toitū Te Whenua Land Information New Zealand
    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 2020 - April 2021.

    Technical specifications:

    • 450 x ortho-rectified RGB GeoTIFF images in NZTM projection, tiled into the LINZ Standard 1:50,000 tile layout
    • Satellite sensors: ESA Sentinel-2A and Sentinel-2B
    • Acquisition dates: September 2020 - April 2021
    • 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.

  17. WorldView-2 full archive and tasking

    • earth.esa.int
    • fedeo.ceos.org
    • +1more
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    European Space Agency, WorldView-2 full archive and tasking [Dataset]. https://earth.esa.int/eogateway/catalog/worldview-2-full-archive-and-tasking
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    Dataset authored and provided by
    European Space Agencyhttp://www.esa.int/
    License

    https://earth.esa.int/eogateway/documents/20142/1560778/ESA-Third-Party-Missions-Terms-and-Conditions.pdfhttps://earth.esa.int/eogateway/documents/20142/1560778/ESA-Third-Party-Missions-Terms-and-Conditions.pdf

    Description

    WorldView-2 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, WorldView-2 offers archive and tasking panchromatic products up to 0.46 m GSD resolution, and 4-Bands/8-Bands Multispectral products up to 1.84 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 8-bands Standard(2A)/View Ready Standard (OR2A) 30 cm, 40 cm, 50/60 cm View Ready Stereo 30 cm, 40 cm, 50/60 cm Map-Ready (Ortho) 1:12.000 Orthorectified 30 cm, 40 cm, 50/60 cm 4-Bands being an optional 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). 8-Bands being an optional from: 8-Band Multispectral (COASTAL, BLUE, GREEN, YELLOW, RED, RED EDGE, NIR1, NIR2) 8-Band Bundle (PAN, COASTAL, BLUE, GREEN, YELLOW, RED, RED EDGE, NIR1, NIR2). 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 increases the number of pixels, improves the visual clarity and allows to obtain an aesthetically refined imagery with precise edges and well reconstructed details. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided.

  18. Trees in Satellite Imagery

    • kaggle.com
    Updated Jul 13, 2022
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    Mehmet Cagri Aksoy (2022). Trees in Satellite Imagery [Dataset]. https://www.kaggle.com/datasets/mcagriaksoy/trees-in-satellite-imagery
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 13, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Mehmet Cagri Aksoy
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    About Dataset

    Context

    This dataset is being used for classifying the land with class of trees or not in geospatial images. Satellite: https://sentinel.esa.int/web/sentinel/missions/sentinel-2

    Content

    The content architecture is simple. Each datum has 64x64 resolution and located under "tree" and "notree" folders. Each folder (class) has 5200 images. So the total dataset has 10.4K images.

    Cite

    You can cite my work with: M.Ç.Aksoy (2022). Trees in Satellite Imagery [Dataset].https://www.kaggle.com/datasets/mcagriaksoy/trees-in-satellite-imagery

    And you can also cite the source of this data EUROSAT: Helber, P., Bischke, B., Dengel, A., & Borth, D. (2019). Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(7), 2217-2226.

  19. 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.

  20. WorldView-3 full archive and tasking

    • earth.esa.int
    • fedeo.ceos.org
    • +1more
    Updated Sep 2, 2014
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    European Space Agency (2014). WorldView-3 full archive and tasking [Dataset]. https://earth.esa.int/eogateway/catalog/worldview-3-full-archive-and-tasking
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    Dataset updated
    Sep 2, 2014
    Dataset authored and provided by
    European Space Agencyhttp://www.esa.int/
    License

    https://earth.esa.int/eogateway/documents/20142/1560778/ESA-Third-Party-Missions-Terms-and-Conditions.pdfhttps://earth.esa.int/eogateway/documents/20142/1560778/ESA-Third-Party-Missions-Terms-and-Conditions.pdf

    Description

    WorldView-3 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, WorldView-3 offers archive and tasking panchromatic products up to 0.31m GSD resolution, 4-Bands/8-Bands products up to 1.24 m GSD resolution, and SWIR products up to 3.70 m GSD resolution. Band Combination Data Processing Level Resolution High Res Optical: 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 High Res Optical: 8-bands Standard(2A)/View Ready Standard (OR2A) 30 cm, 40 cm, 50/60 cm View Ready Stereo 30 cm, 40 cm, 50/60 cm Map Ready (Ortho) 1:12.000 Orthorectified 30 cm, 40 cm, 50/60 cm High Res Optical: SWIR Standard(2A)/View Ready Standard (OR2A) 3.7 m or 7.5 m (depending on the collection date) Map Ready (Ortho) 1:12.000 Orthorectified 4-Bands being an optional 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) 8-Bands being an optional from: 8-Band Multispectral (COASTAL, BLUE, GREEN, YELLOW, RED, RED EDGE, NIR1, NIR2) 8-Band Bundle (PAN, COASTAL, BLUE, GREEN, YELLOW, RED, RED EDGE, NIR1, NIR2) 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 increases the number of pixels and improves the visual clarity achieving aesthetically refined imagery with precise edges and well reconstructed details. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided.

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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

High Resolution Satellite Imagery

Explore at:
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.

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