Use the + and - buttons to zoom in and out, or center scroll button on your mouse.Hold the left mouse button down and drag to pan the map.Use the Map Date drop down to turn on and off Years to view different imagery regarding Historical Aerials from the Las Vegas Valley.Please be patient as the Imagery Data loads.

Satellite images are essentially the eyes in the sky. Some of the recent satellites, such as WorldView-3, provide images with a spatial resolution of 0.3 meters. This satellite with a revisit time of under 24 hours can scan a new image of the exact location with every revisit.

Spatial resolution explained Spatial resolution is the size of the physical dimension that can be represented on a pixel of the image. Or in other words, spatial resolution is a measure of the smallest object that the sensor can resolve measured in meters. Generally, spatial resolution can be divided into three categories:

– Low resolution: over 60m/pixel. (useful for regional perspectives such as monitoring larger forest areas)

– Medium resolution: 10‒30m/pixel. (Useful for monitoring crop fields or smaller forest patches)

– High to very high resolution: 0.30‒5m/pixel. (Useful for monitoring smaller objects like buildings, narrow streets, or vehicles)

Based on the application of the imagery for the final product, a choice can be made on the resolution, as labor intensity from person-hours to computing power required increases with the resolution of the imagery.

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.

World Imagery provides one meter or better satellite and aerial imagery for most of the world’s landmass and lower resolution satellite imagery worldwide. The map is currently comprised of the following sources:Worldwide 15-m resolution TerraColor imagery at small and medium map scales.Maxar imagery basemap products around the world: Vivid Premium at 15-cm HD resolution for select metropolitan areas, Vivid Advanced 30-cm HD for more than 1,000 metropolitan areas, and Vivid Standard from 1.2-m to 0.6-cm resolution for the most of the world, with 30-cm HD across the United States and parts of Western Europe. More information on the Maxar products is included below. High-resolution aerial photography contributed by the GIS User Community. This imagery ranges from 30-cm to 3-cm resolution. You can contribute your imagery to this map and have it served by Esri via the Community Maps Program.Maxar Basemap ProductsVivid PremiumProvides committed image currency in a high-resolution, high-quality image layer over defined metropolitan and high-interest areas across the globe. The product provides 15-cm HD resolution imagery.Vivid AdvancedProvides committed image currency in a high-resolution, high-quality image layer over defined metropolitan and high-interest areas across the globe. The product includes a mix of native 30-cm and 30-cm HD resolution imagery.Vivid StandardProvides a visually consistent and continuous image layer over large areas through advanced image mosaicking techniques, including tonal balancing and seamline blending across thousands of image strips. Available from 1.2-m down to 30-cm HD. More on Maxar HD.Updates and CoverageYou can use the World Imagery Updates app to learn more about recent updates and map coverage.CitationsThis layer includes imagery provider, collection date, resolution, accuracy, and source of the imagery. With the Identify tool in ArcGIS Desktop or the ArcGIS Online Map Viewer you can see imagery citations. Citations returned apply only to the available imagery at that location and scale. You may need to zoom in to view the best available imagery. Citations can also be accessed in the World Imagery with Metadata web map.UseYou can add this layer to the ArcGIS Online Map Viewer, ArcGIS Desktop, or ArcGIS Pro. To view this layer with a useful reference overlay, open the Imagery Hybrid web map.FeedbackHave you ever seen a problem in the Esri World Imagery Map that you wanted to report? You can use the Imagery Map Feedback web map to provide comments on issues. The feedback will be reviewed by the ArcGIS Online team and considered for one of our updates.

The NSW SPOT 5 imagery product is a state-wide satellite imagery product provided by the Remote Sensing and Regulatory Mapping team of NSW Government. Capture dates for imagery products for 2010-2015 are;

• 2015 - September 2014 through to March 2015

• 2014 - October 2013 through to August 2014

• 2013 - January 2012 through to July 2013

• 2012 - January 2011 through to July 2012

• 2011 - November 2010 through to July 2011

• 2010 - October 2009 through to August 2010

The imagery scenes used to create the NSW mosaic includes Lord Howe Island. This imagery data sets for 2010-2012 have been supplied by SPOT imaging and processing done by GeoImage Pty Ltd. Imagery for 2013-2015 has been supplied by Astrium/Airbus and processed by GeoImage Pty Ltd.

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

Data products supplied for all of NSW are:

1. State-wide mosaic

2. Reflectance scenes

3. Panchromatic scenes

The statewide mosaic is provided as a Red Green Blue (RGB) band combination; contrast enhanced lossless 8-bit JPEG2000 file.

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

The rectified reflectance and panchromatic scenes are available for download from JDAP.

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

“Includes material © CNES 2010, 2011 & 2012, Distribution Astrium Services / Spot Image S.A., France, all rights reserved”

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

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.

For the purposes of training AI-based models to identify (map) road features in rural/remote tropical regions on the basis of true-colour satellite imagery, and subsequently testing the accuracy of these AI-derived road maps, we produced a dataset of 8904 satellite image ‘tiles’ and their corresponding known road features across Equatorial Asia (Indonesia, Malaysia, Papua New Guinea).

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.

Deforestation Satellite Imagery

## Overview

Deforestation Satellite Imagery is a dataset for instance segmentation tasks - it contains Tree annotations for 2,026 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. Remotely-sensed imagery provides the foundation for mapping vegetation types and other land cover classes. Imagery taken by the GeoEye-1 satellite/sensor was acquired from LandInfo Worldwide Mapping, LLC. The product was delivered as bundled 50 cm panchromatic and 2 meter 4-band multispectral (R, G, B, and NIR) images. The imagery has a positional accuracy of <3 m. Specifications for the GeoEye acquisition included the following: Total area for new collection of 372 square kilometers, 10% or less cloud cover , 0-20 off-nadir angle guarantee, Acquisition dates between late May and late June, 2011 Imagery satisfying the requirements was successfully acquired for the BICA project area on June 15, 2011 and delivered to CSU in July 2011. Each image was delivered as a geo-referenced product mosaicked as a single scene/image. We created a 50 cm resolution pan-sharpened set of multispectral bands to use for interpretation of vegetation. The acquisition provided 4-band imagery during the peak growing season. Additional imagery supplementing interpretation included 30 cm true-color Google Earth/Bing imagery imported to ArcGIS using Arc2Earth™ software and older true-color imagery viewed using the Google Earth online viewer.

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.

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. 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.

This map is a work in progress. Please help us to improve it on www.openstreetmap.org or email corrections/additions to imusouth@un.org.

This REST Service provides cached satellite imagery for the City of Tempe. Imagery was flown in late 2022 and early 2023.

This layer of the map based index (GeoIndex) shows satellite data at different resolutions depending on the current map scale. At small scales, it is shown in generalised form with each pixel covering 300 metres, and at larger scales it is shown at its actual resolution of 30 metres. The satellite imagery in GeoIndex was acquired by the Landsat Thematic Mapper sensor between 1984 and 1990. The imagery has been processed by the BGS Remote Sensing Section to increase contrast and thus enhance natural boundaries. Winter imagery was chosen due to the low sun angle, which enables geomorphic features on the landscape to be distinguished and interpreted. The colours in the image are not what one would normally expect to see because we have used infrared wavelengths to help us extract more geological information than would be possible if we had used visible bands. To create a single image of the whole country, many smaller images covering different rectangular areas and taken at different dates have been patched together. This will in some cases produce marked changes where the smaller images meet and is due to the different conditions when the images were taken.

The first generation of U.S. photo intelligence satellites collected more than 860,000 images of the Earth’s surface between 1960 and 1972. The classified military satellite systems code-named CORONA, ARGON, and LANYARD acquired photographic images from space and returned the film to Earth for processing and analysis. The images were originally used for reconnaissance and to produce maps for U.S. intelligence agencies. In 1992, an Environmental Task Force evaluated the application of early satellite data for environmental studies. Since the CORONA, ARGON, and LANYARD data were no longer critical to national security and could be of historical value for global change research, the images were declassified by Executive Order 12951 in 1995. The first successful CORONA mission was launched from Vandenberg Air Force Base in 1960. The satellite acquired photographs with a telescopic camera system and loaded the exposed film into recovery capsules. The capsules or buckets were de-orbited and retrieved by aircraft while the capsules parachuted to earth. The exposed film was developed and the images were analyzed for a range of military applications. The intelligence community used Keyhole (KH) designators to describe system characteristics and accomplishments. The CORONA systems were designated KH-1, KH-2, KH-3, KH-4, KH-4A, and KH-4B. The ARGON systems used the designator KH-5 and the LANYARD systems used KH-6. Mission numbers were a means for indexing the imagery and associated collateral data. A variety of camera systems were used with the satellites. Early systems (KH-1, KH-2, KH-3, and KH-6) carried a single panoramic camera or a single frame camera (KH-5). The later systems (KH-4, KH-4A, and KH-4B) carried two panoramic cameras with a separation angle of 30° with one camera looking forward and the other looking aft. The original film and technical mission-related documents are maintained by the National Archives and Records Administration (NARA). Duplicate film sources held in the USGS EROS Center archive are used to produce digital copies of the imagery. Mathematical calculations based on camera operation and satellite path were used to approximate image coordinates. Since the accuracy of the coordinates varies according to the precision of information used for the derivation, users should inspect the preview image to verify that the area of interest is contained in the selected frame. Users should also note that the images have not been georeferenced.

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.

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.

The near-real-time data dissemination service is delivered by Earth Observation from Space - a Program of Geoscience Australia responsible for acquiring, curating and analysing remotely sensed data from satellites orbiting the earth.

Landsat 7 and Landsat 8 data is scene based and comprises preview images in JPG format (one at high and one at low resolution) and individual files per spectral band in TIFF format. Included with the data are licence and product descriptions where applicable.

All files are in folders sorted according to date of acquisition and are made available within 3 to 6 hours of the receipt of source information.

Only the last few days of data is held on the server due to the size of the imagery files. Downloading data requires an FTP enabled browser.

ftp://ftp.ga.gov.au/outgoing-emergency-imagery

Landsat ETM+, TM and MSS data is available under Creative Commons Licence 3.0

Dataset History

Geoscience Australia receives and processes data from the Landsat series of satellites. The Landsat Program is the longest running satellite series for imaging Earth from space. The first satellite in the series was launched in 1972, and since then seven satellites have been launched. The eighth satellite, the Landsat Data Continuity Mission, is due to be launched early 2013. The Landsat Program has produced one of the most successful satellite ventures in space history with Landsat 5. Commencing in March 1984, the satellite had an expected life of 3 years. As of 2012 Geoscience Australia no longer processes or distributes Multispectral Scanner (MSS) data.

Of the sensors carried, the Multispectral Scanner (MSS) with 80-metre pixels and four spectral bands was found to provide information of unforeseen value. In July 1982, the launch of Landsat 4 saw the inclusion of the Thematic Mapper (TM) sensor with a 30-metre resolution and 7 spectral bands. Both sensors are on Landsat 5.

The newest in this series of remote sensing satellites is Landsat 7. Launched on 15 April 1999, Landsat 7 has the new Enhanced Thematic Mapper Plus (ETM+) sensor. This sensor has the same 7 spectral bands as its predecessor, TM, but has an added panchromatic band with 15-metre resolution and a higher resolution thermal band of 60 metres. The ETM+ sensor also has a five percent absolute radiometric calibration.

Landsat MSS data was recorded over Australia by USGS from 1972 to 1979. Geoscience Australia (then ACRES) began acquisition of this data in September 1979. Acquisition of Landsat MSS image data ceased in December 1997. From late 1979 we have archived nearly every pass over Australia and continue to receive and archive data from Landsat 7 daily.

Dataset Citation

Geoscience Australia (2015) HUN Historical Landsat Images Mine Foot Prints v01. Bioregional Assessment Source Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/28de7771-28f5-4d24-943f-0addea07c8c4.

This dataset contains processed satellite imageries of the Gulf of Papua - Torres Strait (GP-TS) region. It includes: - 12-year (mid 2008-mid 2019) of daily MODIS water type images (Wet season colour scale), and summaries (seasonal, annual, long term, difference composite maps) - 1 year (2019) of weekly Sentinel-3 water type images (Forel-Ule colour scale)

** This dataset is currently under embargo until 31/01/2022.

These outputs have been produced though the remote sensing components of the NESP Project 2.2.1 and NESP Project 5.14: Identifying the water quality and ecosystem health threats to the high diversity Torres Strait and Far Northern GBR from runoff from the Fly River (Waterhouse et al., 2018, in review and Petus et al., in prep.) These studies used different sources and long-term databases of freely available satellite data to describe large-scale turbidity patterns around the GP-TS region, map the Fly River plume and to identify instances and areas with likely plume intrusion into the Torres Strait protected zone. Multi-year datasets of medium-resolution satellite images (MODIS-Aqua and Sentinel-3) of the study area have been downloaded and processed. Medium-resolution satellite data have been processed into daily colour class and water type maps of the study area using two respective colour classification scales. Several spatial summaries have been produced (median, frequency, difference composite maps) at different time scales (seasonal, annual, long term). These spatial summaries provides a large scale baseline of the composition of coastal waters around the GP-TS region, as well as a description of seasonal trends. This baseline is particularly important as field water quality data are scarce and challenging to collect due to the remoteness of the study area, They provide a reference against which to compare future changes, as well as spatially explicit information for when and where the influence from Fly River discharge is likely to occur and which TS ecosystems are likely to be the most exposed. In making this data publicly available for management, the authors from the TropWATER Catchment to Reef Research Group request being contacted and involved in decision making processes that incorporate this data, to ensure its methodology and limitations are fully understood.

Methods:

MODIS-Aqua water type maps Twelve years of water type maps (mid-2008 to mid-2019) were produced using daily MODIS-Aqua (MA) true colour satellite imagery reclassified to 6 distinct ocean colour classes. The ocean colour is the result of interactions between sunlight and materials in the water. It is co-determined by the absorption and scattering of various optically active water quality components: the suspended sediment: SS, the coloured dissolved organic matter: CDOM and the chlorophyll-a: Chl-a. The ocean colour is a simple indicator available to study the composition of our ocean and distinguish different surface water bodies and their associated water quality characteristics (e.g., Petus et al., 2019, in prep.).The six colour classes (CC) were defined by their colour properties across an Intensity-Hue-Saturation gradient (Alvarez-Romero et al., 2012) and were regrouped into three optical water types: Primary (CC1-4), Secondary (CC5) and Tertiary (CC6). They were produced using the WSC scale classification toolbox (Petus et al., 2019). The WSC scale classification toolbox is a semi-automated toolbox using a suit of R and Python (ArcGIS) scripts that has been developed originally for the Great Barrier Reef (GBR) through Marine Monitoring Program (MMP) funding (Alvarez-Romero et al., 2013). The toolbox spectrally enhance (Red-Green-Blue, RGB to Intensity-Hue-Saturation, IHS) MODIS true colour imagery and cluster the MODIS pixels into “cloud” (from the RGB image), “ambiant water” and six Wet Season Colour classes (from the IHS image) through a supervised classification using typical apparent surface colour signatures of flood waters in the GBR (Alvarez-Romero et al., 2013, Figure 1, right and Figure 2). Discrimination of colour classes has been based on the GBR flood plume typology as defined originally in e.g., Devlin et al. (2011). It has been calibrated and validated with satellite and in-situ water quality data, respectively (Alvarez-Romero et al., 2013; Devlin et al., 2015, Petus et al., 2016). Technical details about the WSC scale classification have been published in e.g. Alvarez-Romero et al., 2013, Devlin et al., 2015; Petus et al., 2016, 2019 and GBRMPA, 2020 and Waterhouse et al., in prep. In the GBR WSC scale, the brownish to brownish-green turbid water masses (colour classes 1 to 4, or primary water type) are typical for inshore regions of GBR river plumes or nearshore marine areas with high concentrations of resuspended sediments found during the wet season. These water bodies in flood waters typically contain high nutrient and phytoplankton concentrations, but are also enriched in sediment and dissolved organic matter resulting in reduced light levels. The greenish-to-greenish-blue turbid water masses (colour class 5, or Secondary water type) is typical of coastal waters rich in algae and also containing dissolved matter and fine sediment. This water body is found in the GBR open coastal waters as well as in the mid-water plumes where relatively high nutrient availability and increased light levels due to sedimentation favour coastal productivity. Finally, the greenish-blue water mass (colour class 6 or Tertiary water type) correspond to waters with above ambient water quality concentrations. This water body is typical for areas towards the open sea or offshore regions of river flood plumes (e.g. Petus et al., 2019).

Sentinel-3 OLCI water type maps One year (2019) of water type maps was also produced using daily Sentinel-3 Ocean and Land Color Instrument (S3 OLCI) Level-2 (hereafter S3) satellite data reclassified to 21 distinct ocean colour classes. The 21 colour classes (CC) were defined by their colour properties across a Hue gradient and were produced using the Forel-Ule colour (FU) scale classification toolbox. The FU classification toolbox is a semi-automated toolbox using a suit of Python, .bat and xml scripts that have been developed originally for the GBR through MMP funding. It allow processing multi-year databases of satellite images using the FU classification algorithm recently developed through the European Citclops project and implemented in the Science Toolbox Exploitation Platform (SNAP) (http://www.citclops.eu/home, Van der Woerd and Wernand, 2015, 2018). Technical details about the WSC scale classification have been published in e.g., Petus et al., 2019, in prep. and the Appendix B of Gruber et al., 2019. The FU satellite algorithm converts satellite normalised multi-band reflectance information into a discrete set of FU numbers using uniform colourimetric functions (Wernand et al., 2012). The derivation of the colour of natural waters is based on the calculation of Tristimulus values of the three primaries (X, Y, Z) that specify the colour stimulus of the human eye. The algorithm is validated by a set of hyperspectral measurements from inland, coastal and marine waters (Van der Woerd and Wernand 2018) and is applicable to global aquatic environments (lake, estuaries, coastal, offshore). Technical details about FU satellite algorithm, including detailed mathematical descriptions, are presented in e.g., Van der Woerd and Wernand (2015, 2016), Van der Woerd and Wernand (2018) and Wernand et al. (2013). A first comparative study in the GBR suggested that FU4-5, FU6-9 and FU ? 10 are similar to the Primary, Secondary and Tertiary water types in the WS colour scale, respectively (Petus et al., 2019).

Both satellites and colour scales provides qualitative estimation of water composition and spatial datasets that can used in conjunction with in-situ field measurements, satellite estimations and/or hydrodynamic modelling assessments of water quality concentrations (if available). By itself, they are particularly interesting in remote areas where in-situ water quality and optical data are scarce to inexistent as they both relies only on the apparent colour of the ocean. This datasets have been used in Petus et al., in prep. and Waterhouse et al., in review to: (i) map optical water masses in the study area; including the turbid Fly River plume, (ii) document long-term turbidity trends in the Gulf of Papua – Torres Strait region, (iii) determine seasonal changes in turbidity and seasonal plume patterns, and; (iii) assess the presence of ecosystems likely exposed to the Fly River plume, as well as their frequency of exposure. These datasets does not allow assessing the trace metals contaminants of the Fly River discharge or assessing the ecological impact of Fly River discharges on TS ecosystems.

Outputs: Daily datasets: MODIS-Aqua true colour images and six colour class maps: Database name: Daily_MAWS.gdb, Data format: a2008141 = year 2008, Julian day 141 Twelve years (mid-2008 to mid-2019) of daily MODIS true colour images of the GPTS region were downloaded from the NASA Rapid Response and EOSDIS worldview websites. The true colour images were spectrally enhanced (from red-green-blue to hue-saturation-intensity colour systems), and clustered into six colour class maps using methods described above (Álvarez-Romero et al., 2013) and post-processed in ArcGIS 10.3.

Weekly datasets: Sentinel-3 Forel Ule (21) colour class maps: Database name: Weekly_S3FU.gdb, Data format: T2019w01 = week 1 of 2019 One year (2019) of daily S3 OLCI imagery of the study area was downloaded on the EUMETSAT Copernicus Online Data Access website (https://coda.eumetsat.int/#/home). S3 data were atmospherically corrected and were processed with SNAP (Van der Woerd et al., 2016, Van der Woerd and Wernand 2018) and clustered into 21 FUC class maps using methods described above. Processed daily

This dataset contains paired high resolution orthorectified aerial photography provided by the Waikato Region Aerial Photography initiative, paired with Sentinel-2 satellite images. These images were collected as part of a satellite imagery super-resolution research project. The aerial photograph was down-sampled to a spatial resolution of 2.5m per pixel, while the satellite images were taken at a spatial resolution of 10m per pixel. The satellite images were taken from 8 fly-bys between 16th January to 2nd March 2019 so that it is temporally consistent with the aerial photographs taken in February of 2019.