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.

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.

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

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.

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.

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.

The Meteosat Second Generation (MSG) satellites, operated by EUMETSAT (The European Organisation for the Exploitation of Meteorological Satellites), provide almost continuous imagery to meteorologists and researchers in Europe and around the world. These include visible, infra-red, water vapour, High Resolution Visible (HRV) images and derived cloud top height, cloud top temperature, fog, snow detection and volcanic ash products. These images are available for a range of geographical areas.

This dataset contains high resolution visible images from MSG satellites over the UK area. Imagery available from March 2005 onwards at a frequency of 15 minutes (some are hourly) and are at least 24 hours old.

The geographic extent for images within this datasets is available via the linked documentation 'MSG satellite imagery product geographic area details'. Each MSG imagery product area can be referenced from the third and fourth character of the image product name giving in the filename. E.g. for EEAO11 the corresponding geographic details can be found under the entry for area code 'AO' (i.e West Africa).

Context

High-resolution satellite images can provide abundant, detailed spatial information for land cover classification, which is particularly important for studying the complicated built environment. However, due to the complex land cover patterns, the costly training sample collections, and the severe distribution shifts of satellite imageries caused by, e.g., geographical differences or acquisition conditions, few studies have applied high-resolution images to land cover mapping in detailed categories at large scale.

Content

We present a large-scale land cover dataset, Five-Billion-Pixels. It contains more than 5 billion labeled pixels of 150 high-resolution Gaofen-2 (4 m) satellite images, annotated in a 24-category system covering artificial-constructed, agricultural, and natural classes.

How I used this dataset?

Correspondence of colors (BGR) and categories:

• 0, 0, 0: unlabeled
• 200, 0, 0: industrial area
• 0, 200, 0: paddy field
• 150, 250, 0: irrigated field
• 150, 200, 150: dry cropland
• 200, 0, 200: garden land
• 150, 0, 250: arbor forest
• 150, 150, 250: shrub forest
• 200, 150, 200: park
• 250, 200, 0: natural meadow
• 200, 200, 0: artificial meadow
• 0, 0, 200: river
• 250, 0, 150: urban residential
• 0, 150, 200: lake
• 0, 200, 250: pond
• 150, 200, 250: fish pond
• 250, 250, 250: snow
• 200, 200, 200: bareland
• 200, 150, 150: rural residential
• 250, 200, 150: stadium
• 150, 150, 0: square
• 250, 150, 150: road
• 250, 150, 0: overpass
• 250, 200, 250: railway station
• 200, 150, 0: airport

Correspondence of indexes and categories:

• 0: unlabeled
• 1: industrial area
• 2: paddy field
• 3: irrigated field
• 4: dry cropland
• 5: garden land
• 6: arbor forest
• 7: shrub forest
• 8: park
• 9: natural meadow
• 10: artificial meadow
• 11: river
• 12: urban residential
• 13: lake
• 14: pond
• 15: fish pond
• 16: snow
• 17: bareland
• 18: rural residential
• 19: stadium
• 20: square
• 21: road
• 22: overpass
• 23: railway station
• 24: airport

Use the PIL library to read 8-bit data (which has been processed as normal images): image = Image.open(imgname).convert('CMYK').

Citation

@article{FBP2023,

title={Enabling country-scale land cover mapping with meter-resolution satellite imagery},

author={Tong, Xin-Yi and Xia, Gui-Song and Zhu, Xiao Xiang},

journal={ISPRS Journal of Photogrammetry and Remote Sensing},

volume={196},

pages={178-196},

year={2023}

}

Contact

E-mail: xinyi.tong@tum.de

Personal page: Xin-Yi Tong

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.

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.

Suggested use: Use tiled Map Service for large scale mapping when high resolution color imagery is needed.A web app to view tile and block metadata such as year, sensor, and cloud cover can be found here. CoverageState of AlaskaProduct TypeTile CacheImage BandsRGBSpatial Resolution50cmAccuracy5m CE90 or betterCloud Cover<10% overallOff Nadir Angle<30 degreesSun Elevation>30 degreesWMS version of this data: https://geoportal.alaska.gov/arcgis/services/ahri_2020_rgb_cache/MapServer/WMSServer?request=GetCapabilities&service=WMSWMTS version of this data:https://geoportal.alaska.gov/arcgis/rest/services/ahri_2020_rgb_cache/MapServer/WMTS/1.0.0/WMTSCapabilities.xml

"Gaofen-1 satellite" is the first earth observation system with high resolution, launched in April 2013. Its data is mainly used now in the fields of land, agriculture and environment. "Gaofeng-1" has three different resolutions such as 2 meters of panchromatic data, 8 meters and 16 meters of spectral data, combining. The Institute of agricultural resources and regionalization, Chinese academy of agricultural sciences, as the main application unit of the agricultural sector, can obtain relevant data for free and in real time. After the atmospheric and radiation correction, geometric correctionand projection transformation, and on the basis of "status of land use classification standard (GB - T21010-2015)" issued by the ministry of land and resources, for all types of land classification and summary statistics can be obtained through image analysis. At present, the land-use classification and extraction of 2016-2017 of 16 provinces have been preliminarily completed, which has formed a land-use map and statistics based on the administrative region. Comparing with the land-use data obtained by the Institute of Geographic Science and Resources, Chinese academy of sciences based on MODIS data, this data has a higher resolution and a characteristic of more up-to-date, and it can provide better service for all kinds of management and research departments.

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 2022 through to March 2023. 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.

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.

Data products supplied for all of NSW are:

1. State-wide mosaic

2. 100k Mapsheet tiles (GDA94 and GDA2020)

3. Multi spectral scenes (GDA94 and GDA2020)

4. Pan sharpened scenes (GDA94 and GDA2020)

5. Panchromatic scenes (GDA94 and GDA2020)

6. Shapefile cutlines of statewide mosaic

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.

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

The 4band 100k mapsheet tiles are available for download from JDAP(pending). The rectified multispectral, pan sharpened and panchromatic scenes are available for download from JDAP (pending)

Acknowledgement when referencing: includes material © CNES_ (year of production), Distribution Airbus Services/SPOT Image, S.A, France, all rights reserved

Contact spatial.imagery@environment.nsw.gov.au for further information or to request access to JDAP

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

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.

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

This dataset collection contains A0 maps of the Keppel Island region based on satellite imagery and fine-scale habitat mapping of the islands and marine environment. This collection provides the source satellite imagery used to produce these maps and the habitat mapping data.

The imagery used to produce these maps was developed by blending high-resolution imagery (1 m) from ArcGIS Online with a clear-sky composite derived from Sentinel 2 imagery (10 m). The Sentinel 2 imagery was used to achieve full coverage of the entire region, while the high-resolution was used to provide detail around island areas.

The blended imagery is a derivative product of the Sentinel 2 imagery and ArcGIS Online imagery, using Photoshop to to manually blend the best portions of each imagery into the final product. The imagery is provided for the sole purpose of reproducing the A0 maps.

Methods:

The high resolution satellite composite composite was developed by manual masking and blending of a Sentinel 2 composite image and high resolution imagery from ArcGIS Online World Imagery (2019).

The Sentinel 2 composite was produced by statistically combining the clearest 10 images from 2016 - 2019. These images were manually chosen based on their very low cloud cover, lack of sun glint and clear water conditions. These images were then combined together to remove clouds and reduce the noise in the image.

The processing of the images was performed using a script in Google Earth Engine. The script combines the manually chosen imagery to estimate the clearest imagery. The dates of the images were chosen using the EOBrowser (https://www.sentinel-hub.com/explore/eobrowser) to preview all the Sentinel 2 imagery from 2015-2019. The images that were mostly free of clouds, with little or no sun glint, were recorded. Each of these dates was then viewed in Google Earth Engine with high contrast settings to identify images that had high water surface noise due to algal blooms, waves, or re-suspension. These were excluded from the list. All the images were then combined by applying a histogram analysis of each pixel, with the final image using the 40th percentile of the time series of the brightness of each pixel. This approach helps exclude effects from clouds.

The contrast of the image was stretched to highlight the marine features, whilst retaining detail in the land features. This was done by choosing a black point for each channel that would provide a dark setting for deep clear water. Gamma correction was then used to lighten up the dark water features, whilst not ove- exposing the brighter shallow areas.

Both the high resolution satellite imagery and Sentinel 2 imagery was combined at 1 m pixel resolution. The resolution of the Sentinel 2 tiles was up sampled to match the resolution of the high-resolution imagery. These two sets of imagery were then layered in Photoshop. The brightness of the high-resolution satellite imagery was then adjusting to match the Sentinel 2 imagery. A mask was then used to retain and blend the imagery that showed the best detail of each area. The blended tiles were then merged with the overall area imagery by performing a GDAL merge, resulting in an upscaling of the Sentinel 2 imagery to 1 m resolution.


Habitat Mapping:

A 5 m resolution habitat mapping was developed based on the satellite imagery, aerial imagery available, and monitoring site information. This habitat mapping was developed to help with monitoring site selection and for the mapping workshop with the Woppaburra TOs on North Keppel Island in Dec 2019.

The habitat maps should be considered as draft as they don't consider all available in water observations. They are primarily based on aerial and satellite images.

The habitat mapping includes: Asphalt, Buildings, Mangrove, Cabbage-tree palm, Sheoak, Other vegetation, Grass, Salt Flat, Rock, Beach Rock, Gravel, Coral, Sparse coral, Unknown not rock (macroalgae on rubble), Marine feature (rock).

This assumed layers allowed the digitisation of these features to be sped up, so for example, if there was coral growing over a marine feature then the boundary of the marine feature would need to be digitised, then the coral feature, but not the boundary between the marine feature and the coral. We knew that the coral was going to cut out from the marine feature because the coral is on top of the marine feature, saving us time in digitising this boundary. Digitisation was performed on an iPad using Procreate software and an Apple pencil to draw the features as layers in a drawing. Due to memory limitations of the iPad the region was digitised using 6000x6000 pixel tiles. The raster images were converted back to polygons and the tiles merged together.

A python script was then used to clip the layer sandwich so that there is no overlap between feature types.

Habitat Validation:

Only limited validation was performed on the habitat map. To assist in the development of the habitat mapping, nearly every YouTube video available, at the time of development (2019), on the Keppel Islands was reviewed and, where possible, georeferenced to provide a better understanding of the local habitats at the scale of the mapping, prior to the mapping being conducted. Several validation points were observed during the workshop. The map should be considered as largely unvalidated.

data/coastline/Keppels_AIMS_Coastline_2017.shp:
The coastline dataset was produced by starting with the Queensland coastline dataset by DNRME (Downloaded from http://qldspatial.information.qld.gov.au/catalogue/custom/detail.page?fid={369DF13C-1BF3-45EA-9B2B-0FA785397B34} on 31 Aug 2019). This was then edited to work at a scale of 1:5000, using the aerial imagery from Queensland Globe as a reference and a high-tide satellite image from 22 Feb 2015 from Google Earth Pro. The perimeter of each island was redrawn. This line feature was then converted to a polygon using the "Lines to Polygon" QGIS tool. The Keppel island features were then saved to a shapefile by exporting with a limited extent.

data/labels/Keppel-Is-Map-Labels.shp:
This contains 70 named places in the Keppel island region. These names were sourced from literature and existing maps. Unfortunately, no provenance of the names was recorded. These names are not official. This includes the following attributes:
- Name: Name of the location. Examples Bald, Bluff
- NameSuffix: End of the name which is often a description of the feature type: Examples: Rock, Point
- TradName: Traditional name of the location
- Scale: Map scale where the label should be displayed.

data/lat/Keppel-Is-Sentinel2-2016-19_B4-LAT_Poly3m_V3.shp:
This corresponds to a rough estimate of the LAT contours around the Keppel Islands. LAT was estimated from tidal differences in Sentinel-2 imagery and light penetration in the red channel. Note this is not very calibrated and should be used as a rough guide. Only one rough in-situ validation was performed at low tide on Ko-no-mie at the edge of the reef near the education centre. This indicated that the LAT estimate was within a depth error range of about +-0.5 m.

data/habitat/Keppels_AIMS_Habitat-mapping_2019.shp:
This shapefile contains the mapped land and marine habitats. The classification type is recorded in the Type attribute.

Format:

GeoTiff (Internal JPEG format - 538 MB)
PDF (A0 regional maps - ~30MB each)
Shapefile (Habitat map, Coastline, Labels, LAT estimate)

Data Location:

This dataset is filed in the eAtlas enduring data repository at: data\custodian\2020-2029-AIMS\Keppels_AIMS_Regional-maps

The Pléiades ESA archive is a dataset of Pléiades-1A and 1B products that ESA collected over the years. The dataset regularly grows as ESA collects new Pléiades products. Pléiades Primary and Ortho products can be available in the following modes: Panchromatic image at 0.5 m resolution Pansharpened colour image at 0.5 m resolution Multispectral image in 4 spectral bands at 2 m resolution Bundle (0.5 m panchromatic image + 2 m multispectral image) Spatial coverage: Check the spatial coverage of the collection on a map available on the Third Party Missions Dissemination Service. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided.

Since its launch in September 1999, GeoEye's IKONOS satellite has provided a reliable stream of image data since January 2000, which has become the standard for commercial high-resolution satellite data products. With an altitude of 681 km and a revisit time of approximately 3 days, IKONOS produces one-meter panchromatic and four-meter multispectral imagery that can be combined to accommodate a wide range of high-resolution imagery applications.

We introduce a cost-effective public health analysis solution for low- and middle-income countries—the Multi-Modal Satellite Imagery Dataset in Colombia. By leveraging high-quality, spatiotemporally aligned satellite images and corresponding metadata, the dataset integrates economic, demographic, meteorological, and epidemiological data. Employing a single forwards and a forward-backward technique ensures clear satellite images with minimal cloud cover for every epi-week, significantly enhancing overall data quality. The extraction process utilizes the satellite extractor package powered by the SentinelHub API, resulting in a comprehensive dataset of 12,636 satellite images from 81 municipalities in Colombia between 2016 and 2018, along with relevant metadata. Beyond expediting public health data analysis across diverse locations and timeframes, this versatile framework consistently captures multimodal features. Its applications extend to various realms in multimodal AI, encompassing deforestation monitoring, forecasting education indices, water quality assessment, tracking extreme climatic events, addressing epidemic illnesses, and optimizing precision agriculture.

High-resolution satellite cloud imagery *The download URL has been changed since September 15, 2023. Please update it before December 31, 2023, otherwise the old version link will be invalid. If you need to download a large amount of data, please apply for membership on the Meteorological Data Open Platform at https://opendata.cwa.gov.tw/index