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

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 dataset contains both large (A0) printable maps of the Torres Strait broken into six overlapping regions, based on a clear sky, clear water composite Sentinel 2 composite imagery and the imagery used to create these maps. These maps show satellite imagery of the region, overlaid with reef and island boundaries and names. Not all features are named, just the more prominent features. This also includes a vector map of Ashmore Reef and Boot Reef in Coral Sea as these were used in the same discussions that these maps were developed for. The map of Ashmore Reef includes the atoll platform, reef boundaries and depth polygons for 5 m and 10 m.

This dataset contains all working files used in the development of these maps. This includes all a copy of all the source datasets and all derived satellite image tiles and QGIS files used to create the maps. This includes cloud free Sentinel 2 composite imagery of the Torres Strait region with alpha blended edges to allow the creation of a smooth high resolution basemap of the region.

The base imagery is similar to the older base imagery dataset: Torres Strait clear sky, clear water Landsat 5 satellite composite (NERP TE 13.1 eAtlas, AIMS, source: NASA).

Most of the imagery in the composite imagery from 2017 - 2021.

Method: The Sentinel 2 basemap was produced by processing imagery from the World_AIMS_Marine-satellite-imagery dataset (not yet published) for the Torres Strait region. The TrueColour imagery for the scenes covering the mapped area were downloaded. Both the reference 1 imagery (R1) and reference 2 imagery (R2) was copied for processing. R1 imagery contains the lowest noise, most cloud free imagery, while R2 contains the next best set of imagery. Both R1 and R2 are typically composite images from multiple dates.

The R2 images were selectively blended using manually created masks with the R1 images. This was done to get the best combination of both images and typically resulted in a reduction in some of the cloud artefacts in the R1 images. The mask creation and previewing of the blending was performed in Photoshop. The created masks were saved in 01-data/R2-R1-masks. To help with the blending of neighbouring images a feathered alpha channel was added to the imagery. The processing of the merging (using the masks) and the creation of the feathered borders on the images was performed using a Python script (src/local/03-merge-R2-R1-images.py) using the Pillow library and GDAL. The neighbouring image blending mask was created by applying a blurring of the original hard image mask. This allowed neighbouring image tiles to merge together.

The imagery and reference datasets (reef boundaries, EEZ) were loaded into QGIS for the creation of the printable maps.

To optimise the matching of the resulting map slight brightness adjustments were applied to each scene tile to match its neighbours. This was done in the setup of each image in QGIS. This adjustment was imperfect as each tile was made from a different combinations of days (to remove clouds) resulting in each scene having a different tonal gradients across the scene then its neighbours. Additionally Sentinel 2 has slight stripes (at 13 degrees off the vertical) due to the swath of each sensor having a slight sensitivity difference. This effect was uncorrected in this imagery.

Single merged composite GeoTiff: The image tiles with alpha blended edges work well in QGIS, but not in ArcGIS Pro. To allow this imagery to be used across tools that don't support the alpha blending we merged and flattened the tiles into a single large GeoTiff with no alpha channel. This was done by rendering the map created in QGIS into a single large image. This was done in multiple steps to make the process manageable.

The rendered map was cut into twenty 1 x 1 degree georeferenced PNG images using the Atlas feature of QGIS. This process baked in the alpha blending across neighbouring Sentinel 2 scenes. The PNG images were then merged back into a large GeoTiff image using GDAL (via QGIS), removing the alpha channel. The brightness of the image was adjusted so that the darkest pixels in the image were 1, saving the value 0 for nodata masking and the boundary was clipped, using a polygon boundary, to trim off the outer feathering. The image was then optimised for performance by using internal tiling and adding overviews. A full breakdown of these steps is provided in the README.md in the 'Browse and download all data files' link.

The merged final image is available in export\TS_AIMS_Torres Strait-Sentinel-2_Composite.tif.

Change Log: 2023-03-02: Eric Lawrey Created a merged version of the satellite imagery, with no alpha blending so that it can be used in ArcGIS Pro. It is now a single large GeoTiff image. The Google Earth Engine source code for the World_AIMS_Marine-satellite-imagery was included to improve the reproducibility and provenance of the dataset, along with a calculation of the distribution of image dates that went into the final composite image. A WMS service for the imagery was also setup and linked to from the metadata. A cross reference to the older Torres Strait clear sky clear water Landsat composite imagery was also added to the record.

22 Nov 2023: Eric Lawrey Added the data and maps for close up of Mer. - 01-data/TS_DNRM_Mer-aerial-imagery/ - preview/Torres-Strait-Mer-Map-Landscape-A0.jpeg - exports/Torres-Strait-Mer-Map-Landscape-A0.pdf Updated 02-Torres-Strait-regional-maps.qgz to include the layout for the new map.

Source datasets: Complete Great Barrier Reef (GBR) Island and Reef Feature boundaries including Torres Strait Version 1b (NESP TWQ 3.13, AIMS, TSRA, GBRMPA), https://eatlas.org.au/data/uuid/d2396b2c-68d4-4f4b-aab0-52f7bc4a81f5

Geoscience Australia (2014b), Seas and Submerged Lands Act 1973 - Australian Maritime Boundaries 2014a - Geodatabase [Dataset]. Canberra, Australia: Author. https://creativecommons.org/licenses/by/4.0/ [license]. Sourced on 12 July 2017, https://dx.doi.org/10.4225/25/5539DFE87D895

Basemap/AU_GA_AMB_2014a/Exclusive_Economic_Zone_AMB2014a_Limit.shp The original data was obtained from GA (Geoscience Australia, 2014a). The Geodatabase was loaded in ArcMap. The Exclusive_Economic_Zone_AMB2014a_Limit layer was loaded and exported as a shapefile. Since this file was small no clipping was applied to the data.

Geoscience Australia (2014a), Treaties - Australian Maritime Boundaries (AMB) 2014a [Dataset]. Canberra, Australia: Author. https://creativecommons.org/licenses/by/4.0/ [license]. Sourced on 12 July 2017, http://dx.doi.org/10.4225/25/5539E01878302 Basemap/AU_GA_Treaties-AMB_2014a/Papua_New_Guinea_TSPZ_AMB2014a_Limit.shp The original data was obtained from GA (Geoscience Australia, 2014b). The Geodatabase was loaded in ArcMap. The Papua_New_Guinea_TSPZ_AMB2014a_Limit layer was loaded and exported as a shapefile. Since this file was small no clipping was applied to the data.

AIMS Coral Sea Features (2022) - DRAFT This is a draft version of this dataset. The region for Ashmore and Boot reef was checked. The attributes in these datasets haven't been cleaned up. Note these files should not be considered finalised and are only suitable for maps around Ashmore Reef. Please source an updated version of this dataset for any other purpose. CS_AIMS_Coral-Sea-Features/CS_Names/Names.shp CS_AIMS_Coral-Sea-Features/CS_Platform_adj/CS_Platform.shp CS_AIMS_Coral-Sea-Features/CS_Reef_Boundaries_adj/CS_Reef_Boundaries.shp CS_AIMS_Coral-Sea-Features/CS_Depth/CS_AIMS_Coral-Sea-Features_Img_S2_R1_Depth5m_Coral-Sea.shp CS_AIMS_Coral-Sea-Features/CS_Depth/CS_AIMS_Coral-Sea-Features_Img_S2_R1_Depth10m_Coral-Sea.shp

Murray Island 20 Sept 2011 15cm SISP aerial imagery, Queensland Spatial Imagery Services Program, Department of Resources, Queensland This is the high resolution imagery used to create the map of Mer.

Marine satellite imagery (Sentinel 2 and Landsat 8) (AIMS), https://eatlas.org.au/data/uuid/5d67aa4d-a983-45d0-8cc1-187596fa9c0c - World_AIMS_Marine-satellite-imagery

Data Location: This dataset is filed in the eAtlas enduring data repository at: data\custodian\2020-2029-AIMS\TS_AIMS_Torres-Strait-Sentinel-2-regional-maps. On the eAtlas server it is stored at eAtlas GeoServer\data\2020-2029-AIMS.

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.

The PlanetScope Level 1B Basic Scene and Level 3B Ortho Scene full archive products are available as part of Planet imagery offer. The Unrectified Asset: PlanetScope Basic Analytic Radiance (TOAR) product is a Scaled Top of Atmosphere Radiance (at sensor) and sensor corrected product, without correction for any geometric distortions inherent in the imaging processes and is not mapped to a cartographic projection. The imagery data is accompanied by Rational Polynomial Coefficients (RPCs) to enable orthorectification by the user. This kind of product is designed for users with advanced image processing and geometric correction capabilities. Basic Scene Product Components and Format Product Components Image File (GeoTIFF format) Metadata File (XML format) Rational Polynomial Coefficients (XML format) Thumbnail File (GeoTIFF format) Unusable Data Mask UDM File (GeoTIFF format) Usable Data Mask UDM2 File (GeoTIFF format) Bands 4-band multispectral image (blue, green, red, near-infrared) or 8-band (coastal-blue, blue, green I, green, yellow, red, Rededge, near-infrared) Ground Sampling Distance Approximate, satellite altitude dependent Dove-C: 3.0 m-4.1 m Dove-R: 3.0 m-4.1 m SuperDove: 3.7 m-4.2 m Accuracy <10 m RMSE The Rectified assets: The PlanetScope Ortho Scene product is radiometrically-, sensor- and geometrically- corrected and is projected to a UTM/WGS84 cartographic map projection. The geometric correction uses fine Digital Elevation Models (DEMs) with a post spacing of between 30 and 90 metres. Ortho Scene Product Components and Format Product Components Image File (GeoTIFF format) Metadata File (XML format) Thumbnail File (GeoTIFF format) Unusable Data Mask UDM File (GeoTIFF format) Usable Data Mask UDM2 File (GeoTIFF format) Bands 3-band natural colour (red, green, blue) or 4-band multispectral image (blue, green, red, near-infrared) or 8-band (coastal-blue, blue, green I, green, yellow, red, RedEdge, near-infrared) Ground Sampling Distance Approximate, satellite altitude dependent Dove-C: 3.0 m-4.1 m Dove-R: 3.0 m-4.1 m SuperDove: 3.7 m-4.2 m Projection UTM WGS84 Accuracy <10 m RMSE PlanetScope Ortho Scene product is available in the following: PlanetScope Visual Ortho Scene product is orthorectified and colour-corrected (using a colour curve) 3-band RGB Imagery. This correction attempts to optimise colours as seen by the human eye providing images as they would look if viewed from the perspective of the satellite. PlanetScope Surface Reflectance product is orthorectified, 4-band BGRN or 8-band Coastal Blue, Blue, Green I, Green, Yellow, Red, RedEdge, NIR Imagery with geometric, radiometric and corrected for surface reflection. This data is optimal for value-added image processing such as land cover classifications. PlanetScope Analytic Ortho Scene Surface Reflectance product is orthorectified, 4-band BGRN or 8-band Coastal Blue, Blue, Green I, Green, Yellow, Red, RedEdge, NIR Imagery with geometric, radiometric and calibrated to top of atmosphere radiance. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided.

**New aerial images released for free! **### All orthophotographic mosaics produced since 2002, in order to meet the needs related to the ecoforest inventory of southern Quebec (IEQM), are now available as open data. For more information on this product, please refer to the fact sheet ** Historic Airborne Forest Imagery **. To download them, please consult the ** download map **. **** Orthophotographic mosaics present an aerial view of Quebec territory at different times. Each image has been analytically straightened to eliminate inaccuracies caused by the camera being tilted at the time of shooting or by the image being moved due to terrain. These collections are the result of governmental and regional initiatives, namely: * The Ecoforest Inventory of Southern Quebec (IEQM) * Partnerships between ministries, agencies and municipal communities Their download is free, as they were acquired under an open data license (** Creative Commons 4.0 **). Three formats are available depending on the territory: JPEG 2000, ECW and GeoTIFF. For product ownership information (resolution, image type, etc.), please refer to the information for each mosaic available in the ** download card **. For more information on priced aerial imagery, please consult the sheet ** aerial imagery ** in the “Maps and Geographic Information” section of the Ministry of Energy and Natural Resources website.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The WorldView-1 Level 1B Panchromatic Imagery collection contains satellite imagery acquired from Maxar Technologies (formerly known as DigitalGlobe) by the Commercial Smallsat Data Acquisition (CSDA) Program. Panchromatic imagery is collected by the DigitalGlobe WorldView-1 satellite using the WorldView-60 camera across the global land surface from September 2007 to the present. Data have a spatial resolution of 0.5 meters at nadir and a temporal resolution of approximately 1.7 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program.

The RapidEye Level 3A Ortho Tile, both Visual (in natural colour) and Analytic (multispectral), full archive products are available as part of Planet imagery offer. The RapidEye Ortho Tile product (L3A) is radiometric, sensor and geometrically corrected (by using DEMs with a post spacing of between 30 and 90 metres) and aligned to a cartographic map projection. Ground Control Points (GCPs) are used in the creation of every image and the accuracy of the product will vary from region to region based on available GCPs. Product Components Image File – GeoTIFF file that contains image data and geolocation information Metadata File – XML format metadata file Unusable Data Mask (UDM) file – GeoTIFF format Bands 3-band natural color (blue, green, red) or 5-band multispectral image (blue, green, red, red edge, near-infrared) Ground Sampling Distance 6.5 m at nadir (average at reference altitude 475 km) Projection UTM WGS84 Accuracy Depends on the quality of the reference data used (GCPs and DEMs) The products are available as part of the Planet provision from RapidEye, Skysat and PlanetScope constellations. RapidEye collection has worldwide coverage: the Planet Explorer Catalogue can be accessed (Planet registration requested) to discover and check the data readiness. All details about the data provision, data access conditions and quota assignment procedure are described in the Terms of Applicability. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided.

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

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 December 2016 - December 2017.

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Currency This data will be updated once a year, during the term of the 2-year pilot.

Technical specifications It comprises 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: December 2016 - December 2017
• Spectral resolution: R, G, B
• Spatial resolution: 10 metres
• 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 eo@linz.govt.nz

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

The GeoEye-1 Level 1B Panchromatic Imagery collection contains satellite imagery acquired from Maxar Technologies (formerly known as DigitalGlobe) by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery is collected by the GeoEye-1 satellite using the GeoEye-1 Imaging System across the global land surface from September 2008 to the present. This data product includes panchromatic imagery with a spatial resolution of 0.46m at nadir (0.41m before summer 2013) and a temporal resolution of approximately 3 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program.

A Digital Orthophoto Quadrangle (DOQ) is a computer-generated image of an aerial photograph in which the image displacement caused by terrain relief and camera tilt has been removed. The DOQ combines the image characteristics of the original photograph with the georeferenced qualities of a map.

DOQs are black and white (B/W), natural color, or color-infrared (CIR) images with 1-meter ground resolution.

The USGS produces three types of DOQs:

1. 3.75-minute (quarter-quad) DOQs cover an area measuring 3.75-minutes longitude by 3.75-minutes latitude. Most of the U.S. is currently available, and the remaining locations should be complete by 2004. Quarter-quad DOQs are available in both Native and GeoTIFF formats. Native format consists of an ASCII keyword header followed by a series of 8-bit binary image lines for B/W and 24-bit band-interleaved-by-pixel (BIP) for color. DOQs in native format are cast to the Universal Transverse Mercator (UTM) projection and referenced to either the North American Datum (NAD) of 1927 (NAD27) or the NAD of 1983 (NAD83). GeoTIFF format consists of a georeferenced Tagged Image File Format (TIFF), with all geographic referencing information embedded within the .tif file. DOQs in GeoTIFF format are cast to the UTM projection and referenced to NAD83. The average file size of a B/W quarter quad is 40-45 megabytes, and a color file is generally 140-150 megabytes. Quarter-quad DOQs are distributed via File Transfer Protocol (FTP) as uncompressed files.

2. 7.5-minute (full-quad) DOQs cover an area measuring 7.5-minutes longitude by 7.5-minutes latitude. Full-quad DOQs are mostly available for Oregon, Washington, and Alaska. Limited coverage may also be available for other states. Full-quad DOQs are available in both Native and GeoTIFF formats. Native is formatted with an ASCII keyword header followed by a series of 8-bit binary image lines for B/W. DOQs in native format are cast to the UTM projection and referenced to either NAD27 or NAD83. GeoTIFF is a georeferenced Tagged Image File Format with referencing information embedded within the .tif file. DOQs in GeoTIFF format are cast to the UTM projection and referenced to NAD83. The average file size of a B/W full quad is 140-150 megabytes. Full-quad DOQs are distributed via FTP as uncompressed files.

3. Seamless DOQs are available for free download from the Seamless site. DOQs on this site are the most current version and are available for the conterminous U.S.

[Summary provided by the USGS.]

The New Zealand Imagery dataset consists of New Zealand's publicly owned aerial and satellite imagery, which is freely available to use under an open licence. The dataset ranges from the latest high-resolution aerial imagery down to 5cm in some urban areas to lower resolution satellite imagery that provides full coverage of mainland New Zealand, Chathams and other offshore islands. It also includes historical imagery that has been scanned from film, orthorectified (removing distortions) and georeferenced (correctly positioned) to create a unique and crucial record of changes to the New Zealand landscape.
All of the imagery files are Cloud Optimised GeoTIFFs using lossless WEBP compression for the main image and lossy WEBP compression for the overviews. These image files are accompanied by STAC metadata. The imagery is organised by region and survey.

1 Description SEN2VENµS is an open dataset for the super-resolution of Sentinel-2 images by leveraging simultaneous acquisitions with the VENµS satellite. The dataset is composed of 10m and 20m cloud-free surface reflectance patches from Sentinel-2, with their reference spatially-registered surface reflectance patches at 5 meters resolution acquired on the same day by the VENµS satellite. This dataset covers 29 locations with a total of 132 955 patches of 256x256 pixels at 5 meters resolution, and can be used for the training of super-resolution algorithms to bring spatial resolution of 8 of the Sentinel-2 bands down to 5 meters. Changelog with respect to version 1.0.0 (https://zenodo.org/records/6514159) All patches are now stored in indivual geoTiFF files with proper geo-referencing, regrouped in zip files per site and per category, The dataset now includes 20 meter resolution SWIR bands B11 and B12 from Sentinel-2 (L2A from Theia). Note that there is no HR reference for those bands, since the VENµS sensor has no SWIR band. 2 Files organization The dataset is composed of separate sub-datasets embedded in separate zip files, one for each site, as described in table 1. Note that there might be slight variations in number of patches and number of pairs with respect to version 1.0.0, due do incorrect count of samples in previous version (an empty tensor was still accounted for). Table 1: Number of patches and pairs for each site, along with VENµS viewing zenith angle Site Number of patches Number of pairs VENµS Zenith Angle FR-LQ1 4888 18 1.795402 NARYN 3813 24 5.010906 FGMANAUS 129 4 7.232127 MAD-AMBO 1442 18 14.788115 ARM 15859 39 15.160683 BAMBENW2 9018 34 17.766533 ES-IC3XG 8822 34 18.807686 ANJI 2312 14 19.310494 ATTO 2258 9 22.048651 ESGISB-3 6057 19 23.683871 ESGISB-1 2891 12 24.561609 FR-BIL 7105 30 24.802892 K34-AMAZ 1384 20 24.982675 ESGISB-2 3067 13 26.209776 ALSACE 2653 16 26.877071 LERIDA-1 2281 5 28.524780 ESTUAMAR 911 12 28.871947 SUDOUE-5 2176 20 29.170244 KUDALIAR 7269 20 29.180855 SUDOUE-6 2435 14 29.192055 SUDOUE-4 935 7 29.516127 SUDOUE-3 5363 14 29.998115 SO1 12018 36 30.255978 SUDOUE-2 9700 27 31.295256 ES-LTERA 1701 19 31.971764 FR-LAM 7299 22 32.054056 SO2 738 22 32.218481 BENGA 5857 28 32.587334 JAM2018 2564 18 33.718953 Each site zip file contains a subfolder with the site name. This subfolder contains secondary zip files for each date, following this naming convention as the pair id: {site_name}_{acquisition_date}_{mgrs_tile}. For each date, 5 zip files are available, as shown in table 2.Each zip file contain subfolder {bands}/{resolution}/ in which one GeoTiFF file per patch is stored, with the following naming convention: {site_name}_{idx}_{acquisition_date}_{mgr_tile}_{bands}_{resolution}.tif. Pixel values are encoded as 16 bits signed integers and should be converted back to floating point surface reflectance by dividing each and every value by 10 000 upon reading. Table 2: Naming convention for zip files associated to each date. File Content {id}_05m_b2b3b4b8.zip 5m patches ((256\times256) pix.) for S2 B2, B3, B4 and B8 (from VENµS) {id}_10m_b2b3b4b8.zip 10m patches ((128\times128) pix.) for S2 B2, B3, B4 and B8 (from Sentinel-2) {id}_05m_b5b6b7b8a.zip 5m patches ((256\times256) pix.) for S2 B5, B6, B7 and B8A (from VENµS) {id}_20m_b5b6b7b8a.zip 20m patches ((64\times64) pix.) for S2 B5, B6, B7 and B8A (from Sentinel-2) {id}_20m_b11b12.zip 20m patches ((64\times64) pix.) for S2 B11 and B12 (from Sentinel-2) Each file comes with a master index.csv CSV (Comma Separated Values) file, with one row for each pair sampled in the given site. Columns are named after the {bands}_{resolution} pattern, and contains the full path to the corresponding GeoTiFF wihin the corresponding zip file: {site}_{acquisition_date}_{mgrs_tile}_{bands}_{resolution}.zip/{bands}/{resolution}/{site}_{idx}_{acquisition_date}_{mgrs_tile}_{bands}_{resolution}.tif 3 Licencing 3.1 Sentinel-2 patches 3.1.1 Copyright Value-added data processed by CNES for the Theia data centre www.theia-land.fr using Copernicus products. The processing uses algorithms developed by Theia's Scientific Expertise Centres. Note: Copernicus Sentinel-2 Level 1C data is subject to this license: https://theia.cnes.fr/atdistrib/documents/TC_Sentinel_Data_31072014.pdf 3.1.2 Licence Files *_b2b3b4b8_10m.tif, *_b5b6b7b8a_20m.tif and *_b11b12_20m.tif are distributed under the the original licence of the Sentinel-2 Theia L2A products, which is the Etalab Open Licence Version 2.0 2. 3.2 VENµS patches 3.2.1 Copyright Value-added data processed by CNES for the Theia data centre www.theia-land.fr using VENµS satellite imagery from CNES and Israeli Space Agency. The processing uses algorithms developed by Theia's Scientific Expertise Centres. 3.2.2 Licence Files *_b2b3b4b8_05m.tif and *_b5b6b7b8a_05m.tif are distributed under the original licence of the VENµS products, which is Crea...

Here we provide a mosaic of the Copernicus DEM 30m for Europe and the corresponding hillshade derived from the GLO-30 public instance of the Copernicus DEM. The CRS is the same as the original Copernicus DEM CRS: EPSG:4326. Note that GLO-30 Public provides limited coverage at 30 meters because a small subset of tiles covering specific countries are not yet released to the public by the Copernicus Programme. Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs.

The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. The original GLO-30 provides worldwide coverage at 30 meters (refers to 10 arc seconds). Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Note that the vertical unit for measurement of elevation height is meters.

The Copernicus DEM for Europe at 30 m in COG format has been derived from the Copernicus DEM GLO-30, mirrored on Open Data on AWS, dataset managed by Sinergise (https://registry.opendata.aws/copernicus-dem/).

Processing steps: The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in https://gdal.org/drivers/raster/vrt.html format and defined within the VRT file the rule to apply cubic resampling while reading the data, i.e. importing them into GRASS GIS for further processing. We chose cubic instead of bilinear resampling since the height-width ratio of non-square pixels is up to 1:5. Hence, artefacts between adjacent tiles in rugged terrain could be minimized: gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt

The pixel values were scaled with 1000 (storing the pixels as integer values) for data volume reduction. In addition, a hillshade raster map was derived from the resampled elevation map (using r.relief, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files.

Loudoun County annually obtains leaf-off, aerial imagery in the spring. Since 2004, the County has utilized this imagery to support the development of an annual digital orthophoto base. In 2023, the imagery was captured with a Vexcel Ultracam Eagle digital camera, in 4-band (R,G,B, and NIR) format. These files contain 1-foot ground-resolution, 8-bit, 4-band orthorectified aerial image map products in GeoTIFF version 6.0 file format. GeoTIFF files are uncompressed raster images complete with TFW coordinate information. The aerial imagery project encompasses the entire land area of the County of Loudoun, VA. Images were flown during leaf-off conditions and cover 5000' by 5000' and are tiled according to the VBMP 200-scale gridding schema (Virginia Geographic Information Network)."March 2023 Photography flown by The Sanborn Map Company, Inc. Colorado Springs, CO." "Digital Orthophotography compiled by Sanborn Map Company, Inc. Colorado Springs, CO"

The WorldView-2 Level 1B Multispectral 8-Band Imagery collection contains satellite imagery acquired from Maxar Technologies (formerly known as DigitalGlobe) by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery is collected by the DigitalGlobe WorldView-2 satellite using the WorldView-110 camera across the global land surface from October 2009 to the present. This satellite imagery is in the visible and near-infrared waveband range with data in the coastal, blue, green, yellow, red, red edge, and near-infrared (2 bands) wavelengths. It has a spatial resolution of 1.85m at nadir and a temporal resolution of approximately 1.1 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program.

The Sentinel-2 mission is a land monitoring constellation of two satellites that provide high resolution optical imagery and provide continuity for the current SPOT and Landsat missions. The mission provides a global coverage of the Earth's land surface every 5 days, making the data of great use in ongoing studies. This dataset is the same as the Sentinel-2 dataset, except the JP2K files were converted into Cloud-Optimized GeoTIFFs (COGs). Additionally, SpatioTemporal Asset Catalog metadata has were in a JSON file alongside the data, and a STAC API called Earth-search is freely available to search the archive. This dataset contains all of the scenes in the original Sentinel-2 Public Dataset and will grow as that does. L2A data are available from April 2017 over wider Europe region and globally since December 2018.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

Landsat TM, and ETM+ data are provided in GeoTIFF for Level 1T (terrain corrected) products, or for either Level 1Gt (systematic terrain corrected) or Level 1G (systematic corrected) products, if Level 1T processing is not available. GeoTIFF defines a set of publicly available TIFF tags that describe cartographic and geodetic information associated with TIFF images. GeoTIFF is a format that enables referencing a raster image to a known geodetic model or map projection.

The initial tags are followed by image data that, in turn, may be interrupted by more descriptive tags. By using the GeoTIFF format, both metadata and image data can be encoded into the same file. The Landsat 7 ETM+ GeoTIFF file format is described in detail in the"Landsat 7 ETM+ Level 1 Product Data Format Control Book (DFCB), LSDS-272": http://landsat.usgs.gov/documents/LSDS-272.pdf. The Landsat 4-5 TM GeoTIFF file format is described in detail in the "Landsat Thematic Mapper (TM) Level 1 (L1) Data Format Control Book (DFCB), LS-DFCB-20": http://landsat.usgs.gov/documents/LS-DFCB-20.pdf.

For more information on GeoTIFF visit: http://trac.osgeo.org/geotiff

Dataset History

ORGANIZATION

Each band of Landsat data in the GeoTIFF format is delivered as a grayscale, uncompressed, 8-bit string of unsigned integers. A metadata (MTL) file is included with data processed through the Level-1 Product Generation System (LPGS). A file containing the ground control points (GCP) used during image processing is also included. A processing history (WO) file is included with data processed through the National Landsat Archive Production System (NLAPS). Landsat 7 ETM+ SLC-off products processed after December 11, 2008, will include an additional directory (gap_mask) that contains a set of flat binary scan gap mask files (one per band). (Please note that the processing date and acquisition date are not necessarily the same.)

* DATA FILE NAMES

The file naming convention for Landsat LPGS-processed GeoTIFF data

is as follows:

LMSppprrrYYYYDOYGSIVV_BN.TIF where:

 L      = Landsat 

 M      = Mission (E for ETM+ data; T for TM data; M for MSS)

 S      = Satellite (7 = Landsat 7, 5 = Landsat 5, 4 = Landsat 4)

 ppp     = starting path of the product

 rrr     = starting and ending rows of the product

 YYYY    = acquisition year

 DOY     = Julian date

 GSI     = Ground Station Identifier 

 VV     = 2 digit version number

 BN     = file type:

   B1     = band 1

   B2     = band 2

   B3     = band 3

   B4     = band 4

   B5     = band 5

   B6_VCID_1 = band 6L (low gain) (ETM+)

   B6_VCID_2 = band 6H (high gain) (ETM+)

   B6     = band 6 (TM and MSS)

   B7     = band 7 

   B8     = band 8 (ETM+)

   MTL    = Level-1 metadata

   GCP    = ground control points

 TIF     = GeoTIFF file extension

The file naming convention for Landsat NLAPS-processed GeoTIFF data

is as follows:

LLNppprrrOOYYDDDMM_AA.TIF where:

 LL     = Landsat sensor (LT for TM data)

 N      = satellite number

 ppp     = starting path of the product

 rrr     = starting row of the product

 OO     = WRS row offset (set to 00)

 YY     = last two digits of the year of 

        acquisition

 DDD     = Julian date of acquisition

 MM     = instrument mode (10 for MSS; 50 for TM)

 AA     = file type:

   B1     = band 1

   B2     = band 2

   B3     = band 3

   B4     = band 4

   B5     = band5

   B6     = band 6

   B7     = band 7

   WO     = processing history file 

 TIF     = GeoTIFF file extension

* GAP MASKS

All Landsat 7 ETM+ SLC-off imagery processed on or after December 11, 2008, will include gap mask files. (Please note the difference between acquisition date and processing date, files dates are not necessarily the same.) The gap mask files are bit mask files showing the locations of the image gaps (areas that fall between ETM+ scans). One tarred and gzip-compressed gap mask file is provided for each band in GeoTIFF format. The file naming convention for gap mask files is identical to that described above for LPGS-processed GeoTIFF data, with "_GM" inserted before file type.

If gap mask files are not included with the data, a tutorial for creating them can be found at: http://landsat.usgs.gov/gap_mask_files_are_not_provided_can_I_create_my_own.php

* README

The README_GTF.TXT (or README.GTF) is an ASCII text file and is this file.

* READING DATA

Delivered via file transfer protocol (FTP): data files are tarred and g-zip compressed and will need to be unzipped and untarred before the data files can be used. UNIX systems should have the "gunzip" and "tar"

commands available for uncompressing and accessing the data. For PC users, free software can be downloaded from an online source. Otherwise, check your PC, as you may already have appropriate software available.

No software is included on this product for viewing Landsat data.

GENERAL INFORMATION and DOCUMENTATION

Landsat Project Information:

http://landsat.usgs.gov

Landsat data access:

* USGS Global Visualization Viewer (GloVis): http://glovis.usgs.gov

* USGS EarthExplorer: http://earthexplorer.usgs.gov

* USGS LandsatLook Viewer: http://landsatlook.usgs.gov

* Landsat International Ground Station (IGS) network:

         http://landsat.usgs.gov/about_ground_stations.php

FGDC metadata:

http://www.fgdc.gov/metadata

Data restrictions and citation:

https://lta.cr.usgs.gov/citation

* National Snow and Ice Data Center (NSIDC)

Radarsat Antarctic Mapping Project (RAMP) elevation data citation:

Liu, H., K. Jezek, B. Li, and Z. Zhao. 2001.

Radarsat Antarctic Mapping Project digital elevation model version 2.

Boulder, CO: National Snow and Ice Data Center. Digital media.

For information on the data, please refer to the data set documentation

available at the following web site:

http://nsidc.org/data/nsidc-0082.html

PRODUCT SUPPORT

For further information on this product, contact USGS

EROS Customer Services:

Customer Services (ATTN: Landsat)

U.S. Geological Survey

Earth Resources Observation and Science (EROS) Center

47914 252nd Street

Sioux Falls, SD 57198-0001

Tel: 800-252-4547

Tel: 605-594-6151

Email: custserv@usgs.gov

For information on other products from USGS EROS:

http://eros.usgs.gov/ or https://lta.cr.usgs.gov/

For information on other USGS products:

http://ask.usgs.gov/

or call 1-888-ASK-USGS (275-8747)

DISCLAIMER

Any use of trade, product, or firm names is for descriptive

purposes only and does not imply endorsement by the U.S.

Government.

Publication Date: July 2014

Dataset Citation

U.S. Geological Survey (2014) SYD Landsat raw data v01. Bioregional Assessment Source Dataset. Viewed 18 June 2018, http://data.bioregionalassessments.gov.au/dataset/fe7aa98d-ea2a-48fc-bc09-1d5ce3a50246.