100+ datasets found
  1. f

    Power Plant Satellite Imagery Dataset

    • figshare.com
    pdf
    Updated May 31, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Kyle Bradbury; Benjamin Brigman; Gouttham Chandrasekar; Leslie Collins; Shamikh Hossain; Marc Jeuland; Timothy Johnson; Boning Li; Trishul Nagenalli (2023). Power Plant Satellite Imagery Dataset [Dataset]. http://doi.org/10.6084/m9.figshare.5307364.v1
    Explore at:
    pdfAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    figshare
    Authors
    Kyle Bradbury; Benjamin Brigman; Gouttham Chandrasekar; Leslie Collins; Shamikh Hossain; Marc Jeuland; Timothy Johnson; Boning Li; Trishul Nagenalli
    License

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

    Description

    This dataset contains satellite imagery of 4,454 power plants within the United States. The imagery is provided at two resolutions: 1m (4-band NAIP iamgery with near-infrared) and 30m (Landsat 8, pansharpened to 15m). The NAIP imagery is available for the U.S. and Landsat 8 is available globally. This dataset may be of value for computer vision work, machine learning, as well as energy and environmental analyses.Additionally, annotations of the specific locations of the spatial extent of the power plants in each image is provided. These annotations were collected via the crowdsourcing platform, Amazon Mechanical Turk, using multiple annotators for each image to ensure quality. Links to the sources of the imagery data, the annotation tool, and the team that created the dataset are included in the "References" section.To read more on these data, please refer to the "Power Plant Satellite Imagery Dataset Overview.pdf" file. To download a sample of the data without downloading the entire dataset, download "sample.zip" which includes two sample powerplants and the NAIP, Landsat 8, and binary annotations for each.Note: the NAIP imagery may appear "washed out" when viewed in standard image viewing software because it includes a near-infrared band in addition to the standard RGB data.

  2. R

    Data from: Satellite Image Classification Dataset

    • universe.roboflow.com
    zip
    Updated Mar 10, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    modelexamples (2025). Satellite Image Classification Dataset [Dataset]. https://universe.roboflow.com/modelexamples-eo848/satellite-image-classification-khyyl/model/5
    Explore at:
    zipAvailable download formats
    Dataset updated
    Mar 10, 2025
    Dataset authored and provided by
    modelexamples
    License

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

    Variables measured
    Objects
    Description

    Satellite Image Classification

    ## Overview
    
    Satellite Image Classification is a dataset for classification tasks - it contains Objects annotations for 2,000 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  3. Data from: Satellite Image

    • open.canada.ca
    • ouvert.canada.ca
    pdf
    Updated Mar 14, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Natural Resources Canada (2022). Satellite Image [Dataset]. https://open.canada.ca/data/en/dataset/912a9d77-0a3f-5e0c-91f5-197ee5317e9f
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Mar 14, 2022
    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

    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.

  4. a

    Satellite Maps 3D Scene 2023 - for website

    • noaa.hub.arcgis.com
    Updated Jul 24, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    NOAA GeoPlatform (2023). Satellite Maps 3D Scene 2023 - for website [Dataset]. https://noaa.hub.arcgis.com/maps/320e766fff7d4b5a8280c86373ee60e0
    Explore at:
    Dataset updated
    Jul 24, 2023
    Dataset authored and provided by
    NOAA GeoPlatform
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This application is intended for informational purposes only and is not an operational product. The tool provides the capability to access, view and interact with satellite imagery, and shows the latest view of Earth as it appears from space.For additional imagery from NOAA's GOES East and GOES West satellites, please visit our Imagery and Data page or our cooperative institute partners at CIRA and CIMSS.This website should not be used to support operational observation, forecasting, emergency, or disaster mitigation operations, either public or private. In addition, we do not provide weather forecasts on this site — that is the mission of the National Weather Service. Please contact them for any forecast questions or issues. Using the Maps​What does the Layering Options icon mean?The Layering Options widget provides a list of operational layers and their symbols, and allows you to turn individual layers on and off. The order in which layers appear in this widget corresponds to the layer order in the map. The top layer ‘checked’ will indicate what you are viewing in the map, and you may be unable to view the layers below.Layers with expansion arrows indicate that they contain sublayers or subtypes.Do these maps work on mobile devices and different browsers?Yes!Why are there black stripes / missing data on the map?NOAA Satellite Maps is for informational purposes only and is not an operational product; there are times when data is not available.Why are the North and South Poles dark?The raw satellite data used in these web map apps goes through several processing steps after it has been acquired from space. These steps translate the raw data into geospatial data and imagery projected onto a map. NOAA Satellite Maps uses the Mercator projection to portray the Earth's 3D surface in two dimensions. This Mercator projection does not include data at 80 degrees north and south latitude due to distortion, which is why the poles appear black in these maps. NOAA's polar satellites are a critical resource in acquiring operational data at the poles of the Earth and some of this imagery is available on our website (for example, here ).Why does the imagery load slowly?This map viewer does not load pre-generated web-ready graphics and animations like many satellite imagery apps you may be used to seeing. Instead, it downloads geospatial data from our data servers through a Map Service, and the app in your browser renders the imagery in real-time. Each pixel needs to be rendered and geolocated on the web map for it to load.How can I get the raw data and download the GIS World File for the images I choose?NOAA Satellite Maps offers an interoperable map service to the public. Use the camera tool to select the area of the map you would like to capture and click ‘download GIS WorldFile.’The geospatial data Map Service for the NOAA Satellite Maps GOES satellite imagery is located on our Satellite Maps ArcGIS REST Web Service ( available here ).We support open information sharing and integration through this RESTful Service, which can be used by a multitude of GIS software packages and web map applications (both open and licensed).Data is for display purposes only, and should not be used operationally.Are there any restrictions on using this imagery?NOAA supports an open data policy and we encourage publication of imagery from NOAA Satellite Maps; when doing so, please cite it as "NOAA" and also consider including a permalink (such as this one) to allow others to explore the imagery.For acknowledgment in scientific journals, please use:We acknowledge the use of imagery from the NOAA Satellite Maps application: LINKThis imagery is not copyrighted. You may use this material for educational or informational purposes, including photo collections, textbooks, public exhibits, computer graphical simulations and internet web pages. This general permission extends to personal web pages. About this satellite imageryWhat am I looking at in these maps?What am I seeing in the NOAA Satellite Maps 3D Scene?There are four options to choose from, each depicting a different view of the Earth using the latest satellite imagery available. The first three views show the Western Hemisphere and the Pacific Ocean, as captured by the NOAA GOES East (GOES-16) and GOES West (GOES-17) satellites. These images are updated approximately every 15 minutes as we receive data from the satellites in space. The three views show GeoColor, infrared and water vapor. See our other FAQs to learn more about what the imagery layering options depict.The fourth option is a global view, captured by NOAA’s polar-orbiting satellites (NOAA/NASA Suomi NPP and NOAA-20). The polar satellites circle the globe 14 times a day, taking in one complete view of the Earth in daylight every 24 hours. This composite view is what is projected onto the 3D map scene each morning, so you are seeing how the Earth looked from space one day ago.What am I seeing in the Latest 24 Hrs. GOES Constellation Map?In this map you are seeing the past 24 hours (updated approximately every 15 minutes) of the Western Hemisphere and Pacific Ocean, as seen by the NOAA GOES East (GOES-16) and GOES West (GOES-17) satellites. In this map you can also view three different ‘layers’. The three views show ‘GeoColor’ ‘infrared’ and ‘water vapor’.(Please note: GOES West imagery is currently only available in GeoColor. The infrared and water vapor imagery will be available in Spring 2019.)This maps shows the coverage area of the GOES East and GOES West satellites. GOES East, which orbits the Earth from 75.2 degrees west longitude, provides a continuous view of the Western Hemisphere, from the West Coast of Africa to North and South America. GOES West, which orbits the Earth at 137.2 degrees west longitude, sees western North and South America and the central and eastern Pacific Ocean all the way to New Zealand.What am I seeing in the Global Archive Map?In this map, you will see the whole Earth as captured each day by our polar satellites, based on our multi-year archive of data. This data is provided by NOAA’s polar orbiting satellites (NOAA/NASA Suomi NPP from January 2014 to April 19, 2018 and NOAA-20 from April 20, 2018 to today). The polar satellites circle the globe 14 times a day taking in one complete view of the Earth every 24 hours. This complete view is what is projected onto the flat map scene each morning.What does the GOES GeoColor imagery show?The 'Merged GeoColor’ map shows the coverage area of the GOES East and GOES West satellites and includes the entire Western Hemisphere and most of the Pacific Ocean. This imagery uses a combination of visible and infrared channels and is updated approximately every 15 minutes in real time. GeoColor imagery approximates how the human eye would see Earth from space during daylight hours, and is created by combining several of the spectral channels from the Advanced Baseline Imager (ABI) – the primary instrument on the GOES satellites. The wavelengths of reflected sunlight from the red and blue portions of the spectrum are merged with a simulated green wavelength component, creating RGB (red-green-blue) imagery. At night, infrared imagery shows high clouds as white and low clouds and fog as light blue. The static city lights background basemap is derived from a single composite image from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day Night Band. For example, temporary power outages will not be visible. Learn more.What does the GOES infrared map show?The 'GOES infrared' map displays heat radiating off of clouds and the surface of the Earth and is updated every 15 minutes in near real time. Higher clouds colorized in orange often correspond to more active weather systems. This infrared band is one of 12 channels on the Advanced Baseline Imager, the primary instrument on both the GOES East and West satellites. on the GOES the multiple GOES East ABI sensor’s infrared bands, and is updated every 15 minutes in real time. Infrared satellite imagery can be "colorized" or "color-enhanced" to bring out details in cloud patterns. These color enhancements are useful to meteorologists because they signify “brightness temperatures,” which are approximately the temperature of the radiating body, whether it be a cloud or the Earth’s surface. In this imagery, yellow and orange areas signify taller/colder clouds, which often correlate with more active weather systems. Blue areas are usually “clear sky,” while pale white areas typically indicate low-level clouds. During a hurricane, cloud top temperatures will be higher (and colder), and therefore appear dark red. This imagery is derived from band #13 on the GOES East and GOES West Advanced Baseline Imager.How does infrared satellite imagery work?The infrared (IR) band detects radiation that is emitted by the Earth’s surface, atmosphere and clouds, in the “infrared window” portion of the spectrum. The radiation has a wavelength near 10.3 micrometers, and the term “window” means that it passes through the atmosphere with relatively little absorption by gases such as water vapor. It is useful for estimating the emitting temperature of the Earth’s surface and cloud tops. A major advantage of the IR band is that it can sense energy at night, so this imagery is available 24 hours a day.What do the colors on the infrared map represent?In this imagery, yellow and orange areas signify taller/colder clouds, which often correlate with more active weather systems. Blue areas are clear sky, while pale white areas indicate low-level clouds, or potentially frozen surfaces. Learn more about this weather imagery.What does the GOES water vapor map layer show?The GOES ‘water vapor’ map displays the concentration and location of clouds and water vapor in the atmosphere and shows data from both the GOES East and GOES West satellites. Imagery is updated approximately every 15 minutes in

  5. d

    CORONA Satellite Photography

    • catalog.data.gov
    • gimi9.com
    • +4more
    Updated Apr 10, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    DOI/USGS/EROS (2025). CORONA Satellite Photography [Dataset]. https://catalog.data.gov/dataset/corona-satellite-photography
    Explore at:
    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. R

    Merged Satellite Flood Images Dataset

    • universe.roboflow.com
    zip
    Updated Jun 21, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Fire (2023). Merged Satellite Flood Images Dataset [Dataset]. https://universe.roboflow.com/fire-fs3r3/merged-satellite-flood-images
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset authored and provided by
    Fire
    License

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

    Variables measured
    Flood Bounding Boxes
    Description

    Merged Satellite Flood Images

    ## Overview
    
    Merged Satellite Flood Images is a dataset for object detection tasks - it contains Flood annotations for 440 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  7. R

    Data from: Satellite Image Dataset

    • universe.roboflow.com
    zip
    Updated Oct 28, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    project (2022). Satellite Image Dataset [Dataset]. https://universe.roboflow.com/project-5jlv8/satellite-image-gwhnn/dataset/1
    Explore at:
    zipAvailable download formats
    Dataset updated
    Oct 28, 2022
    Dataset authored and provided by
    project
    License

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

    Variables measured
    Land Detection Bounding Boxes
    Description

    Satellite Image

    ## Overview
    
    Satellite Image is a dataset for object detection tasks - it contains Land Detection annotations for 377 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  8. e

    Indian Village Satellite Imagery and Energy Access Dataset - Dataset -...

    • energydata.info
    Updated Apr 21, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2020). Indian Village Satellite Imagery and Energy Access Dataset - Dataset - ENERGYDATA.INFO [Dataset]. https://energydata.info/dataset/indian-village-satellite-imagery-and-energy-access-dataset
    Explore at:
    Dataset updated
    Apr 21, 2020
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This dataset contains remote sensing data for every village in the state of Bihar, India. For most of these villages, the data contains the corresponding electrification rate as reported by the Garv data platform from the Indian government as of July 2017. This dataset contains satellite imagery, political boundaries, lights at night imagery, rainfall measurements, and vegetation indices data for 45,220 villages and the electrification rate data for 32,817 of those villages. This dataset may be of particular interest to those investigating how electricity access maps to infrastructure and agricultural production. This dataset was compiled as part of the Summer 2017 Duke University Data+ team, titled "Electricity Access in Developing Countries from Aerial Imagery."

  9. G

    High Resolution Satellite Imagery

    • open.canada.ca
    • catalogue.arctic-sdi.org
    • +1more
    esri rest, html
    Updated Jan 9, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Government of Yukon (2025). High Resolution Satellite Imagery [Dataset]. https://open.canada.ca/data/en/dataset/0a14b357-8a89-6e98-720e-3a800022cb99
    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.

  10. Sentinel-1&2 Image Pairs (SAR & Optical)

    • kaggle.com
    Updated Mar 9, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Paritosh Tiwari (2021). Sentinel-1&2 Image Pairs (SAR & Optical) [Dataset]. https://www.kaggle.com/datasets/requiemonk/sentinel12-image-pairs-segregated-by-terrain
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 9, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Paritosh Tiwari
    License

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

    Description

    Dataset consists of SAR and Optical (RGB) image pairs from Sentinel‑1 and Sentinel‑2 satellites, provided by the Technical University of Munich. Sentinel-1&2 Image Pairs, Michael Schmitt, Technical University of Munich (TUM)

    We searched through images captured during the fall season in the original dataset provided by TUM, and selected images which could belong to each of the four classes: barren land, grassland, agricultural land, and urban areas. Optical images shown in the following sections give an idea of the type of images belonging to each class. We have tried to introduced as much variation as possible when selecting images for a class.

    Data can be used to train a Conditional GAN. Since the images in this dataset are highly complex i.e. they are not regularized and they do not have a neat geometric pattern or orientation, it can also be used to check the robustness of a model, no matter the task.

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

    • png-data.sprep.org
    • pacific-data.sprep.org
    zip
    Updated Feb 15, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    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
    Explore at:
    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
    Papua New Guinea, 140.7396697998 -6.4408592866477, 155.1976776123 -11.775947798478, 146.4965057373 -1.4884800029826, 156.3842010498 -6.0913976976422, 154.7142791748 -2.6303012095641, 142.3656463623 -10.093262015308)), 149.3968963623 -0.8733792609738, 142.6732635498 -1.2248822742251, 153.3959197998 -2.9375549775994, 155.0658416748 -9.3569327887185
    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

  12. d

    Landsat 8

    • catalog.data.gov
    • gimi9.com
    Updated Apr 10, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    DOI/USGS/EROS (2025). Landsat 8 [Dataset]. https://catalog.data.gov/dataset/landsat-8
    Explore at:
    Dataset updated
    Apr 10, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Description

    The Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) are onboard the Landsat 8 satellite, have acquired images of the Earth since February 2013. The sensors collect images of the Earth with a 16-day repeat cycle, referenced to the Worldwide Reference System-2. The approximate scene size is 170 km north-south by 183 km east-west (106 mi by 114 mi). Landsat 8 image data files consist of 11 spectral bands with a spatial resolution of 30 meters for bands 1-7 and bands 9-11; 15-meters for the panchromatic band 8. Delivered Landsat 8 Level-1 data typically include both OLI and TIRS data files; however, there may be OLI-only and/or TIRS-only scenes in the USGS archive. A Quality Assurance (QA.tif) band is also included. This file provides bit information regarding conditions that may affect the accuracy and usability of a given pixel – clouds, water or snow, for example.

  13. R

    Satellite Image Detection Dataset

    • universe.roboflow.com
    zip
    Updated Jun 25, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    ProjectDetect (2024). Satellite Image Detection Dataset [Dataset]. https://universe.roboflow.com/projectdetect-lrwa1/satellite-image-detection-pcqmq
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jun 25, 2024
    Dataset authored and provided by
    ProjectDetect
    License

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

    Variables measured
    Forest Water Fire Bounding Boxes
    Description

    Satellite Image Detection

    ## Overview
    
    Satellite Image Detection is a dataset for object detection tasks - it contains Forest Water Fire annotations for 237 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  14. n

    High-Resolution QuickBird Imagery and Related GIS Layers for Barrow, Alaska,...

    • cmr.earthdata.nasa.gov
    • datasets.ai
    • +4more
    not provided
    Updated May 23, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2023). High-Resolution QuickBird Imagery and Related GIS Layers for Barrow, Alaska, USA, Version 1 [Dataset]. https://cmr.earthdata.nasa.gov/search/concepts/C1386246127-NSIDCV0.html
    Explore at:
    not providedAvailable download formats
    Dataset updated
    May 23, 2023
    Time period covered
    Aug 1, 2002 - Aug 2, 2002
    Area covered
    Description

    This data set contains high-resolution QuickBird imagery and geospatial data for the entire Barrow QuickBird image area (156.15° W - 157.07° W, 71.15° N - 71.41° N) and Barrow B4 Quadrangle (156.29° W - 156.89° W, 71.25° N - 71.40° N), for use in Geographic Information Systems (GIS) and remote sensing software. The original QuickBird data sets were acquired by DigitalGlobe from 1 to 2 August 2002, and consist of orthorectified satellite imagery. Federal Geographic Data Committee (FGDC)-compliant metadata for all value-added data sets are provided in text, HTML, and XML formats.

    Accessory layers include: 1:250,000- and 1:63,360-scale USGS Digital Raster Graphic (DRG) mosaic images (GeoTIFF format); 1:250,000- and 1:63,360-scale USGS quadrangle index maps (ESRI Shapefile format); an index map for the 62 QuickBird tiles (ESRI Shapefile format); and a simple polygon layer of the extent of the Barrow QuickBird image area and the Barrow B4 quadrangle area (ESRI Shapefile format).

    Unmodified QuickBird data comprise 62 data tiles in Universal Transverse Mercator (UTM) Zone 4 in GeoTIFF format. Standard release files describing the QuickBird data are included, along with the DigitalGlobe license agreement and product handbooks.

    The baseline geospatial data support education, outreach, and multi-disciplinary research of environmental change in Barrow, which is an area of focused scientific interest. Data are provided on four DVDs. This product is available only to investigators funded specifically from the National Science Foundation (NSF), Office of Polar Programs (OPP), Arctic Sciences Section. An NSF OPP award number must be provided when ordering this data. Contact NSIDC User Services at nsidc@nsidc.org to order the data, and include an NSF OPP award number in the email.

  15. i

    Data from: MMFlood: A Multimodal Dataset for Flood Delineation from...

    • ieee-dataport.org
    Updated Jun 7, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Edoardo Arnaudo (2022). MMFlood: A Multimodal Dataset for Flood Delineation from Satellite Imagery [Dataset]. https://ieee-dataport.org/documents/mmflood-multimodal-dataset-flood-delineation-satellite-imagery
    Explore at:
    Dataset updated
    Jun 7, 2022
    Authors
    Edoardo Arnaudo
    License

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

    Description

    including

  16. d

    CORONA Satellite Photographs from the U.S. Geological Survey

    • catalog.data.gov
    • cmr.earthdata.nasa.gov
    • +2more
    Updated Apr 11, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    DOI/USGS/EROS (2025). CORONA Satellite Photographs from the U.S. Geological Survey [Dataset]. https://catalog.data.gov/dataset/corona-satellite-photographs-from-the-u-s-geological-survey
    Explore at:
    Dataset updated
    Apr 11, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    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.

  17. n

    Latest Orthoimagery

    • nconemap.gov
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +1more
    Updated Dec 9, 2016
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    NC OneMap / State of North Carolina (2016). Latest Orthoimagery [Dataset]. https://www.nconemap.gov/datasets/c5b316f805ab4d74bf7b598220ac5558
    Explore at:
    Dataset updated
    Dec 9, 2016
    Dataset authored and provided by
    NC OneMap / State of North Carolina
    License

    https://www.nconemap.gov/pages/termshttps://www.nconemap.gov/pages/terms

    Area covered
    Description

    NOTE: DO NOT DOWNLOAD THE IMAGERY BY USING THE MAP OR DOWNLOAD TOOLS ON THIS ARCGIS HUB ITEM PAGE. IT WILL RESULT IN A PIXELATED ORTHOIMAGE. INSTEAD, DOWNLOAD THE IMAGERY BY TILE OR BY COUNTY MOSAIC (2010 - current year).This service contains the most recent imagery collected by the NC Orthoimagery Program for any given area of North Carolina. The imagery has a pixel resolution of 6 inches with an RMSE of 1.0 ft X and Y. Individual pixel values may have been altered during image processing. Therefore, this service should be used for general reference and viewing. Image analysis requiring examination of individual pixel values is discouraged.

  18. n

    QuickBird full archive

    • cmr.earthdata.nasa.gov
    • eocat.esa.int
    • +2more
    not provided
    Updated Apr 24, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). QuickBird full archive [Dataset]. https://cmr.earthdata.nasa.gov/search/concepts/C1965336934-ESA.html
    Explore at:
    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.

  19. Imagery-Satellite-SPOT 2022

    • researchdata.edu.au
    Updated May 20, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    data.nsw.gov.au (2024). Imagery-Satellite-SPOT 2022 [Dataset]. https://researchdata.edu.au/imagery-satellite-spot-2022/2959381
    Explore at:
    Dataset updated
    May 20, 2024
    Dataset provided by
    Government of New South Waleshttp://nsw.gov.au/
    Area covered
    Description

    The NSW SPOT6/7 imagery product is a state-wide satellite imagery product provided by Geoimage Pty Ltd for NSW Government. The images were captured September 2021 through to March 2022. The imagery scenes used to create the NSW mosaic includes Lord Howe Island. This imagery data set has been acquired through GeoImages Pty Ltd and Airbus Defence and Space. \r \r SPOT imagery products offer high resolution over broad areas using the SPOT 6/7 satellites. A SPOT satellite acquisition covers large areas in a single pass at resolutions up to 1.5m. Such precise coverage is ideal for applications at national and regional scales from 1:250,000 to 1:15,000. SPOT 6/7 also includes the benefits of the near-infrared (NIR) which enables applications for detection of features not visible to the human eye, such as detecting and monitoring vegetation health.\r \r Data products supplied for all of NSW are:\r \r 1. State-wide mosaic \r \r 2. 100k Mapsheet tiles (GDA94 and GDA2020)\r \r 3. Multi spectral scenes (GDA94 and GDA2020)\r \r 4. Pan sharpened scenes (GDA94 and GDA2020)\r \r 5. Panchromatic scenes (GDA94 and GDA2020)\r \r 6. Shapefile cutlines of statewide mosaic \r \r \r The statewide mosaic is provided as a Red Green Blue (RGB) band combination; contrast enhanced lossless 8-bit JPEG2000 file (456gb in size). Individual 100k mapsheet mosaics contain BGR+NIR band combination; unenhanced 16-bit GeoTIFF format tile.\r \r The NSW mosaic is available from internal DPE APOLLO Image Webserver for DCCEEW employees.\r \r The 4band 100k mapsheet tiles are available for download from JDAP.\r The rectified multispectral, pan sharpened and panchromatic scenes are available for download from JDAP (pending)\r \r Acknowledgement when referencing: includes material © CNES_ (year of production), Distribution Airbus Services/SPOT Image, S.A, France, all rights reserved\r \r Contact spatial.imagery@environment.nsw.gov.au for further information or to request access to JDAP \r \r These image products are only available to other NSW Government agencies upon request.\r

  20. D

    Imagery-Satellite-SPOT 2008-2009

    • data.nsw.gov.au
    pdf
    Updated May 21, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    NSW Department of Climate Change, Energy, the Environment and Water (2024). Imagery-Satellite-SPOT 2008-2009 [Dataset]. https://data.nsw.gov.au/data/dataset/spot-mosaic-nsw-2008-2009-rw
    Explore at:
    pdfAvailable download formats
    Dataset updated
    May 21, 2024
    Dataset provided by
    Department of Climate Change, Energy, the Environment and Water of New South Waleshttps://www.nsw.gov.au/departments-and-agencies/dcceew
    Description

    The NSW SPOT 5 imagery product is a state-wide satellite imagery product provided by the Remote Sensing and Regulatory Mapping team of NSW Government. Capture dates for imagery products for 2008-2009 are;

    • 2008 - October 2007 through to September 2008

    • 2009 - October 2008 through to August 2009

    The imagery scenes used to create the NSW mosaic includes Lord Howe Island. This imagery data sets for have been acquired from SPOT Imaging and processed by GeoImage Pty Ltd.

    SPOT imagery products offer high resolution over broad areas using the SPOT 5 satellites. A SPOT satellite acquisition covers large areas in a single pass at resolutions up to 2.5m. Such precise coverage is ideal for applications at national and regional scales from 1:250,000 to 1:15,000.

    Data products supplied for all of NSW are:

    1. State-wide mosaic

    2. Reflectance scenes

    3. Panchromatic scenes

    The statewide mosaic is provided as a Red Green Blue (RGB) band combination; contrast enhanced lossless 8-bit JPEG2000 file. The reflectance and panchromatic scenes are available to download from JDAP.

    The NSW mosaic is available from internal DPE APOLLO Image Webserver for DCCEEW employees.

    Contact spatial.imagery@environment.nsw.gov.au for further information

    “Includes material © CNES 2008 & 2009, Distribution Astrium Services / Spot Image S.A., France, all rights reserved”

    These image products are only available to other NSW Government agencies upon request.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Kyle Bradbury; Benjamin Brigman; Gouttham Chandrasekar; Leslie Collins; Shamikh Hossain; Marc Jeuland; Timothy Johnson; Boning Li; Trishul Nagenalli (2023). Power Plant Satellite Imagery Dataset [Dataset]. http://doi.org/10.6084/m9.figshare.5307364.v1

Power Plant Satellite Imagery Dataset

Explore at:
pdfAvailable download formats
Dataset updated
May 31, 2023
Dataset provided by
figshare
Authors
Kyle Bradbury; Benjamin Brigman; Gouttham Chandrasekar; Leslie Collins; Shamikh Hossain; Marc Jeuland; Timothy Johnson; Boning Li; Trishul Nagenalli
License

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

Description

This dataset contains satellite imagery of 4,454 power plants within the United States. The imagery is provided at two resolutions: 1m (4-band NAIP iamgery with near-infrared) and 30m (Landsat 8, pansharpened to 15m). The NAIP imagery is available for the U.S. and Landsat 8 is available globally. This dataset may be of value for computer vision work, machine learning, as well as energy and environmental analyses.Additionally, annotations of the specific locations of the spatial extent of the power plants in each image is provided. These annotations were collected via the crowdsourcing platform, Amazon Mechanical Turk, using multiple annotators for each image to ensure quality. Links to the sources of the imagery data, the annotation tool, and the team that created the dataset are included in the "References" section.To read more on these data, please refer to the "Power Plant Satellite Imagery Dataset Overview.pdf" file. To download a sample of the data without downloading the entire dataset, download "sample.zip" which includes two sample powerplants and the NAIP, Landsat 8, and binary annotations for each.Note: the NAIP imagery may appear "washed out" when viewed in standard image viewing software because it includes a near-infrared band in addition to the standard RGB data.

Search
Clear search
Close search
Google apps
Main menu