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.

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.

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 2021 - April 2022.

Technical specifications:

• 450 x ortho-rectified RGB GeoTIFF images in NZTM projection, tiled into the LINZ Standard 1:50,000 tile layout
• Satellite sensors: ESA Sentinel-2A and Sentinel-2B
• Acquisition dates: September 2021 - April 2022
• 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.

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.

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.

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.

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

The ESA SPOT 1-5 collection is a dataset of SPOT 1 to 5 Panchromatic and Multispectral products that ESA collected over the years. The HRV(IR) sensor onboard SPOT 1-4 provides data at 10 m spatial resolution Panchromatic mode (-1 band) and 20 m (Multispectral mode -3 or 4 bands). The HRG sensor on board of SPOT-5 provides spatial resolution of the imagery to < 3 m in the panchromatic band and to 10 m in the multispectral mode (3 bands). The SWIR band imagery remains at 20 m. The dataset mainly focuses on European and African sites but some American, Asian and Greenland areas are also covered. Spatial coverage: Check the spatial coverage of the collection on a map available on the Third Party Missions Dissemination Service. The SPOT Collection

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.

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

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

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.

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

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

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

This cached tile service of 2015 WorldView Orthoimagery may be added to ArcMap and other GIS software and applications. The Web service was created in ArcMap 10.3 using orthorectified imagery in mosaic datasets and published to a tile package. The package was published as service that is hosted at MassGIS' ArcGIS Online organizational account.When creating the service in ArcMap, the display settings (stretching, brightness and contrast) were modified individually for each mosaic dataset in order to achieve the best possible uniform appearance across the state; however, because of the different acquisition dates and satellites, seams between strips are visible at smaller scales. With many tiles overlapping from different flights, imagery was displayed so that the best imagery (highest resolution, most cloud-free) appeared "on top".The visible scale range for this service is 1:3,000,000 to 1:2,257.See https://www.mass.gov/info-details/massgis-data-2015-satellite-imagery for full details.

The KSA Satellite Imagery Services Market is Segmented by Application (Geospatial Data Acquisition and Mapping, Natural Resource Management, Surveillance and Security, Conservation and Research, Disaster Management, and Intelligence), by End-User (Government, Construction, Transportation and Logistics, Military and Defense, Forestry, and Agriculture, and Other End Users). The Market Sizes and Forecasts are Provided in Terms of Value USD for all the Above Segments.

This dataset contains Sentinel 2 and Landsat 8 cloud free composite satellite images of the Coral Sea reef areas and some parts of the Great Barrier Reef. It also contains raw depth contours derived from the satellite imagery. This dataset was developed as the base information for mapping the boundaries of reefs and coral cays in the Coral Sea. It is likely that the satellite imagery is useful for numerous other applications. The full source code is available and can be used to apply these techniques to other locations.

This dataset contains two sets of raw satellite derived bathymetry polygons for 5 m, 10 m and 20 m depths based on both the Landsat 8 and Sentinel 2 imagery. These are intended to be post-processed using clipping and manual clean up to provide an estimate of the top structure of reefs. This dataset also contains select scenes on the Great Barrier Reef and Shark bay in Western Australia that were used to calibrate the depth contours. Areas in the GBR were compared with the GA GBR30 2020 (Beaman, 2017) bathymetry dataset and the imagery in Shark bay was used to tune and verify the Satellite Derived Bathymetry algorithm in the handling of dark substrates such as by seagrass meadows. This dataset also contains a couple of small Sentinel 3 images that were used to check the presence of reefs in the Coral Sea outside the bounds of the Sentinel 2 and Landsat 8 imagery.

The Sentinel 2 and Landsat 8 imagery was prepared using the Google Earth Engine, followed by post processing in Python and GDAL. The processing code is available on GitHub (https://github.com/eatlas/CS_AIMS_Coral-Sea-Features_Img).

This collection contains composite imagery for Sentinel 2 tiles (59 in Coral Sea, 8 in GBR) and Landsat 8 tiles (12 in Coral Sea, 4 in GBR and 1 in WA). For each Sentinel tile there are 3 different colour and contrast enhancement styles intended to highlight different features. These include: - TrueColour - Bands: B2 (blue), B3 (green), B4 (red): True colour imagery. This is useful to identifying shallow features are and in mapping the vegetation on cays. - DeepFalse - Bands: B1 (ultraviolet), B2 (blue), B3 (green): False colour image that shows deep marine features to 50 - 60 m depth. This imagery exploits the clear waters of the Coral Sea to allow the ultraviolet band to provide a much deeper view of coral reefs than is typically achievable with true colour imagery. This imagery has a high level of contrast enhancement applied to the imagery and so it appears more noisy (in particular showing artefact from clouds) than the TrueColour styling. - Shallow - Bands: B5 (red edge), B8 (Near Infrared) , B11 (Short Wave infrared): This false colour imagery focuses on identifying very shallow and dry regions in the imagery. It exploits the property that the longer wavelength bands progressively penetrate the water less. B5 penetrates the water approximately 3 - 5 m, B8 approximately 0.5 m and B11 < 0.1 m. Features less than a couple of metres appear dark blue, dry areas are white. This imagery is intended to help identify coral cay boundaries.

For Landsat 8 imagery only the TrueColour and DeepFalse stylings were rendered.

All Sentinel 2 and Landsat 8 imagery has Satellite Derived Bathymetry (SDB) depth contours. - Depth5m - This corresponds to an estimate of the area above 5 m depth (Mean Sea Level). - Depth10m - This corresponds to an estimate of the area above 10 m depth (Mean Sea Level). - Depth20m - This corresponds to an estimate of the area above 20 m depth (Mean Sea Level).

For most Sentinel and some Landsat tiles there are two versions of the DeepFalse imagery based on different collections (dates). The R1 imagery are composites made up from the best available imagery while the R2 imagery uses the next best set of imagery. This splitting of the imagery is to allow two composites to be created from the pool of available imagery. This allows any mapped features to be checked against two images. Typically the R2 imagery will have more artefacts from clouds. In one Sentinel 2 tile a third image was created to help with mapping the reef platform boundary.

The satellite imagery was processed in tiles (approximately 100 x 100 km for Sentinel 2 and 200 x 200 km for Landsat 8) to keep each final image small enough to manage. These tiles were not merged into a single mosaic as it allowed better individual image contrast enhancement when mapping deep features. The dataset only covers the portion of the Coral Sea where there are shallow coral reefs and where their might have been potential new reef platforms indicated by existing bathymetry datasets and the AHO Marine Charts. The extent of the imagery was limited by those available through the Google Earth Engine.

Methods:

The Sentinel 2 imagery was created using the Google Earth Engine. The core algorithm was: 1. For each Sentinel 2 tile, images from 2015 – 2021 were reviewed manually after first filtering to remove cloudy scenes. The allowable cloud cover was adjusted so that at least the 50 least cloud free images were reviewed. The typical cloud cover threshold was 1%. Where very few images were available the cloud cover filter threshold was raised to 100% and all images were reviewed. The Google Earth Engine image IDs of the best images were recorded, along with notes to help sort the images based on those with the clearest water, lowest waves, lowest cloud, and lowest sun glint. Images where there were no or few clouds over the known coral reefs were preferred. No consideration of tides was used in the image selection process. The collection of usable images were grouped into two sets that would be combined together into composite images. The best were added to the R1 composite, and the next best images into the R2 composite. Consideration was made as to whether each image would improve the resultant composite or make it worse. Adding clear images to the collection reduces the visual noise in the image allowing deeper features to be observed. Adding images with clouds introduces small artefacts to the images, which are magnified due to the high contrast stretching applied to the imagery. Where there were few images all available imagery was typically used. 2. Sunglint was removed from the imagery using estimates of the sunglint using two of the infrared bands (described in detail in the section on Sun glint removal and atmospheric correction). 3. A composite image was created from the best images by taking the statistical median of the stack of images selected in the previous stage, after masking out clouds and their shadows (described in detail later). 4. The brightness of the composite image was normalised so that all tiles would have a similar average brightness for deep water areas. This correction was applied to allow more consistent contrast enhancement. Note: this brightness adjustment was applied as a single offset across all pixels in the tile and so this does not correct for finer spatial brightness variations. 5. The contrast of the images was enhanced to create a series of products for different uses. The TrueColour colour image retained the full range of tones visible, so that bright sand cays still retain detail. The DeepFalse style was optimised to see features at depth and the Shallow style provides access to far red and infrared bands for assessing shallow features, such as cays and island. 6. The various contrast enhanced composite images were exported from Google Earth Engine and optimised using Python and GDAL. This optimisation added internal tiling and overviews to the imagery. The depth polygons from each tile were merged into shapefiles covering the whole for each depth.

Cloud Masking

Prior to combining the best images each image was processed to mask out clouds and their shadows.

The cloud masking uses the COPERNICUS/S2_CLOUD_PROBABILITY dataset developed by SentinelHub (Google, n.d.; Zupanc, 2017). The mask includes the cloud areas, plus a mask to remove cloud shadows. The cloud shadows were estimated by projecting the cloud mask in the direction opposite the angle to the sun. The shadow distance was estimated in two parts.

A low cloud mask was created based on the assumption that small clouds have a small shadow distance. These were detected using a 40% cloud probability threshold. These were projected over 400 m, followed by a 150 m buffer to expand the final mask.

A high cloud mask was created to cover longer shadows created by taller, larger clouds. These clouds were detected based on an 80% cloud probability threshold, followed by an erosion and dilation of 300 m to remove small clouds. These were then projected over a 1.5 km distance followed by a 300 m buffer.

The buffering was applied as the cloud masking would often miss significant portions of the edges of clouds and their shadows. The buffering allowed a higher percentage of the cloud to be excluded, whilst retaining as much of the original imagery as possible.

The parameters for the cloud masking (probability threshold, projection distance and buffer radius) were determined through trial and error on a small number of scenes. The algorithm used is significantly better than the default Sentinel 2 cloud masking and slightly better than the COPERNICUS/S2_CLOUD_PROBABILITY cloud mask because it masks out shadows, however there is potentially significant improvements that could be made to the method in the future.

Erosion, dilation and buffer operations were performed at a lower image resolution than the native satellite image resolution to improve the computational speed. The resolution of these operations were adjusted so that they were performed with approximately a 4 pixel resolution during these operations. This made the cloud mask significantly more spatially coarse than the 10 m Sentinel imagery. This resolution was chosen as a trade-off between the coarseness of the mask verse the processing time for these operations.

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

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.

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.

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.