Monthly Blended Ground Cover - Landsat and Sentinel-2, JRSRP Algorithm Version 3.0, Queensland Coverage
<p>The monthly blended ground cover product is a spatially explicit raster product that shows the proportion of bare ground, green and non-green ground cover at medium resolution (30 m per-pixel) for each calendar month across Queensland from 2017 to present. It is derived directly from both the Landsat-based fractional cover product and the Sentinel-2-based fractional cover product by Queensland's Remote Sensing Centre.<br>
A 3 band (byte) image is produced:<br>
band 1 - bare ground fraction (in percent),<br>
band 2 - green vegetation fraction (in percent),<br>
band 3 - non-green vegetation fraction (in percent).<br>
The no data value is 255.</p>
<p>This product is derived from the <a href=" https://portal.tern.org.au/metadata/TERN/8d3c8b36-b4f1-420f-a3f4-824ab70fb367 ">Monthly blended fractional cover - Landsat and Sentinel-2, JRSRP algorithm Version 3.0, Queensland coverage</a></p>
Simple
Identification info
- Date (Creation)
- 2022-01-01
- Date (Publication)
- 2024-09-25
- Date (Revision)
- 2024-09-25
- Edition
- 3.0
Publisher
Author
Department of Environment and Science (2017-2023), Queensland Government
41 Boggo Road, Dutton Park, Queensland, 4102, Australia
Dutton Park
Queensland
4102
Australia
Author
Joint Remote Sensing Research Program
Chancellors Place, St Lucia, Queensland, 4072, Australia
St Lucia
Queensland
4072
Australia
- Website
- https://www.tern.org.au/
- Purpose
- This product captures variability in ground cover at monthly time scales, forming a consistent time series from 2017 - present. The most recent two years are interim products, as there is a two year lag in finalising the persistent green product. The monthly ground cover product is useful for investigating more rapid changes than the 3-monthly seasonal products, for changes in ground cover and analysing regional comparisons. For applications that focus on all vegetation, the fractional cover product may be more suitable.<br> This product is based upon the JRSRP Fractional Cover 3.0 algorithm, which benefited from additional field validation and a new machine learning approach.
- Credit
- We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging.
- Credit
- <p></p>This dataset was produced by the Joint Remote Sensing Research Program using data sourced from US Geological Survey and the European Space Agency (ESA) Copernicus Sentinel Program.
- Status
- On going
Point of contact
Department of Environment and Science (2017-2023), Queensland Government - van den Berg, Deanna (Principal Scientist (Remote Sensing))
41 Boggo Road, Dutton Park, Queensland, 4102, Australia
41 Boggo Road
Dutton Park
Queensland
4102
Australia
- Topic category
-
- Imagery base maps earth cover
- Environment
Extent
- Description
- Queensland
N
S
E
W
))
Temporal extent
- Time period
- 2017-01-01
- Maintenance and update frequency
- Monthly
- GCMD Science Keywords
- ANZSRC Fields of Research
- TERN Platform Vocabulary
- TERN Parameter Vocabulary
- QUDT Units of Measure
- GCMD Horizontal Resolution Ranges
- GCMD Temporal Resolution Ranges
Resource constraints
- Use limitation
- The Creative Commons Attribution 4.0 International (CC BY 4.0) license allows others to copy, distribute, display, and create derivative works provided that they credit the original source and any other nominated parties. Details are provided at https://creativecommons.org/licenses/by/4.0/
- File name
- 88x31.png
- File description
- CCBy Logo from creativecommons.org
- File type
- png
- Title
- Creative Commons Attribution 4.0 International Licence
- Alternate title
- CC-BY
- Edition
- 4.0
- Access constraints
- License
- Use constraints
- Other restrictions
- Other constraints
- TERN services are provided on an "as-is" and "as available" basis. Users use any TERN services at their discretion and risk. They will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through TERN and any analysis performed using the TERN infrastructure. <br />Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN. <br /><br />Please advise any work or publications that use this data via the online form at https://www.tern.org.au/research-publications/#reporting
- Other constraints
- Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}.
- Other constraints
- Copyright 2010-2022. JRSRP. Rights owned by the Joint Remote Sensing Research Project (JRSRP).
- Other constraints
- While every care is taken to ensure the accuracy of this information, the Joint Remote Sensing Research Project (JRSRP) makes no representations or warranties about its accuracy, reliability, completeness or suitability for any particular purpose and disclaims all responsibility and all liability (including without limitation, liability in negligence) for all expenses, losses, damages (including indirect or consequential damage) and costs which might be incurred as a result of the information being inaccurate or incomplete in any way and for any reason.
- Other constraints
- It is not recommended that these data sets be used at scales more detailed than 1:100,000.
Resource constraints
- Classification
- Unclassified
- Supplemental Information
- Data are available as cloud optimised GeoTIFF (COG) files. COG files are easier and more efficient for users to access data corresponding to particular areas of interest without the need to download the data first.
Distribution Information
Distributor
Distributor
Terrestrial Ecosystem Research Network
80 Meiers Road, Indooroopilly, Queensland, 4068, Australia
Indooroopilly
Queensland
4068
Australia
- Distribution format
-
- OnLine resource
- Cloud Optimised GeoTIFFs - Monthly Blended Ground Cover
- OnLine resource
-
Monthly Blended Ground Cover v3
monthly_ground_cover_v3
- OnLine resource
- Landscape Data Visualiser - Monthly Blended Ground Cover - Landsat and Sentinel-2, JRSRP Algorithm Version 3.0, Queensland Coverage
- OnLine resource
- ro-crate-metadata.json
Data quality info
- Hierarchy level
- Dataset
- Other
- Landsat 8 imagery rated as less than 80% cloud cover was downloaded from the USGS EarthExplorer website as level L1T imagery. Sentinel-2A data was downloaded from the ESA as Level 1C (version 02.04 system). Masks for cloud, cloud shadow, topographic shadow and water were applied as described in Flood (2017). <br> The monthly fractional cover model output was compared to roughly 4000 field sites.
Resource lineage
- Statement
- Summary of processing:<br> Landsat 8/Sentinel-2 surface reflectance data > multiple single-date fractional cover datasets > monthly composite of fractional cover > Landsat-based seasonal persistent green > monthly composite of ground cover.
- Hierarchy level
- Dataset
- Title
- Flood, N. (2013). Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-Dimensional Median). Remote Sensing, 5(12), 6481–6500. https://doi.org/10.3390/rs5126481
- Website
-
https://doi.org/10.3390/rs5126481
Method documentation
- Title
- Flood, N., Danaher, T., Gill, T., & Gillingham, S. (2013). An Operational Scheme for Deriving Standardised Surface Reflectance from Landsat TM/ETM+ and SPOT HRG Imagery for Eastern Australia. Remote Sensing, 5(1), 83–109. https://doi.org/10.3390/rs5010083
- Website
-
https://doi.org/10.3390/rs5010083
Method documentation
- Title
- Muir, J., Schmidt, M., Tindall, D., Trevithick, R., Scarth, P., & Stewart, J. B. (2011). Field measurement of fractional ground cover: A technical handbook supporting ground cover monitoring for Australia.
- Website
-
https://www.researchgate.net/publication/236022381_Field_measurement_of_fractional_ground_cover
Method documentation
- Title
- Trevithick, R., Scarth, P., Tindall, D., Denham, R. and Flood, N. (2014). Cover under trees: RP64G Synthesis Report. Department of Science, Information Technology, Innovation and the Arts. Brisbane.
- Website
-
https://www.publications.qld.gov.au/dataset/ad30c88c-185d-4d9a-9971-69968f958a70/resource/350aeffd-ff8f-4876-a12f-7eb8d4e6f991/download/coverundertreesreportrp64gfinal.pdf
Method documentation
Process step
- Description
- Fractional Cover Model:<br> The bare soil, green vegetation and non-green vegetation endmembers for the blended Landsat 8 and Sentinel-2 are calculated using models developed for seasonal fractional cover across Australia.
Process step
- Description
- When viewed from above, as by the satellite, mid- and over-storey vegetation obscures the ground layer fractions (bare ground, green ground cover and dry ground cover). The monthly fractional cover product, from which this ground cover product is derived, does not distinguish between these vegetation layers. As such, a high estimate in the green fraction may be due to green vegetation in any of the vegetation layers. To produce the ground cover product, the fractional cover product is adjusted using an estimate of the proportion of the pixel obscured by mid- and over-story foliage. This estimate of cover is an estimate of the combined persistent dry and persistent green layers. That is, all vegetation in the mid- and upper- stories. The mid and upper storage foliage is effectively removed from the estimates of cover and the ground cover estimate is therefore based only on the proportion of ground that was visible by the satellite.
Process step
- Description
- We assume that fractional cover fractions in each vegetation layer are independent, that is that the presence of mid and over-storey vegetation does not influence the distribution of the ground cover fractions. The algorithm to create the ground cover layer relies on two satellite products (seasonal fractional cover and seasonal persistent green), as well as an estimate of persistent dry derived from field data.
Process step
- Description
- A simplified description of the algorithm follows:<br> 1. Base imagery required is monthly fractional cover from both Landsat and Sentinel-2, and seasonal persistent green product derived from Landsat.<br> 2. Estimate of persistent dry is derived from field data relationship <br> 3. The ‘gap-fraction’ is calculated (total pixel area - pixel area composed of persistent dry - pixel area composed of persistent green)<br> 4. Adjust all three fractions for each pixel using persistent dry and persistent green estimates
Reference System Information
- Reference system identifier
- EPSG/EPSG:3577
- Reference system type
- Geodetic Geographic 2D
Metadata
- Metadata identifier
-
urn:uuid/95366f4c-3fd4-4900-a8c5-a6a286b30762
- Title
- TERN GeoNetwork UUID
- Language
- English
- Character encoding
- UTF8
Point of contact
Type of resource
- Resource scope
- Dataset
- Metadata linkage
-
https://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/95366f4c-3fd4-4900-a8c5-a6a286b30762
Point-of-truth metadata URL
- Date info (Creation)
- 2022-11-07T00:00:00
- Date info (Revision)
- 2024-09-25T00:00:00
Metadata standard
- Title
- ISO 19115-1:2014/AMD 1:2018 Geographic information - Metadata - Fundamentals
- Edition
- 1
Metadata standard
- Title
- ISO/TS 19115-3:2016
- Edition
- 1.0
Metadata standard
- Title
- ISO/TS 19157-2:2016
- Edition
- 1.0
- Title
- Terrestrial Ecosystem Research Network (TERN) Metadata Profile of ISO 19115-3:2016 and ISO 19157-2:2016
- Date (published)
- 2021
- Edition
- 1.0
Identifier
Overviews
Spatial extent
N
S
E
W
Provided by
Associated resources
Not available