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Seasonal Fractional Cover - Sentinel-2, JRSRP Algorithm Version 3.0, Eastern and Central Australia Coverage

<p>The seasonal fractional cover product shows representative values for the proportion of bare, green and non-green cover, created from a time series of Sentinel-2 imagery. It is a spatially explicit raster product, which predicts vegetation cover at medium resolution (10 m per-pixel) for each 3-month calendar season across Eastern and Central Australia from 2016 to present. The green and non-green fractions may include a mix of woody and non-woody vegetation.</p>

<p>This model was originally developed for Landsat imagery, but has been adapted for Sentinel-2 imagery to produce a 10 m resolution equivalent product.</p>

<p>A 3 band (byte) image is produced:</p>

<ul>

<li>band 1 - bare ground fraction (in percent),</li>

<li>band 2 - green vegetation fraction (in percent),</li>

<li>band 3 - non-green vegetation fraction (in percent).</li>

</ul>

<p>The no data value is 255.</p>

Simple

Identification info

Date (Creation)
2022-03-28
Date (Publication)
2022-05-03
Date (Revision)
2025-12-10
Edition
3.0

Publisher

Terrestrial Ecosystem Research Network
Building 1019, 80 Meiers Rd
Indooroopilly
QLD
4068
Australia
+61 7 3365 9097

Author

Joint Remote Sensing Research Program
Chancellors Place, St Lucia, Queensland, 4072, Australia
St Lucia
Queensland
4072
Australia

Author

Department of the Environment, Tourism, Science and Innovation, Queensland Government
41 Boggo Road, Dutton Park, 4102, Queensland, Australia
Dutton Park
Queensland
4102
Australia
Website
https://www.tern.org.au/

Purpose
<p>This product captures variability in fractional cover at seasonal (i.e. three-monthly) time scales, forming a consistent time series from late 2015 - present. It is useful for investigating recent inter-annual changes in vegetation cover and analysing regional comparisons. For applications that focus on non-woody vegetation, the Landsat-derived ground cover product may be more suitable. For applications investigating rapid change during a season, the monthly composite or single-date (available on request) fractional cover products may be more appropriate.</p> <p>This product is based upon the JRSRP Fractional Cover 3.0 algorithm.</p>
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 the European Space Agency (ESA) Copernicus Sentinel Progam.
Status
On going

Point of contact

Department of the Environment, Tourism, Science and Innovation, Queensland Government - Data Enquiries, Earth Observation and Social Sciences (EOSS) ()
41 Boggo Road, Dutton Park, 4102, Queensland, Australia
41 Boggo Road
Dutton Park
Queensland
4102
Australia

Spatial resolution

Spatial resolution
10
Topic category
  • Environment
  • Imagery base maps earth cover

Extent

Description
Australia excluding Western Australia and South Australia
N
S
E
W


N
S
E
W


Temporal extent

Time period
2015-12-01
Title
Sentinel 2 Level 1C Processing
Website
Sentinel 2 Level 1C Processing

Related documentation

Title
Sentinel 2 Data Product Quality Reports
Website
Sentinel 2 Data Product Quality Reports

Related documentation

Title
Beutel, T. S., Trevithick, R., Scarth, P., & Tindall, D. (2019). VegMachine.net. online land cover analysis for the Australian rangelands. The Rangeland Journal, 41(4), 355–362. https://doi.org/10.1071/RJ19013
Website
Beutel, T. S., Trevithick, R., Scarth, P., & Tindall, D. (2019). VegMachine.net. online land cover analysis for the Australian rangelands. The Rangeland Journal, 41(4), 355–362. https://doi.org/10.1071/RJ19013

Related documentation

Maintenance and update frequency
Quarterly
GCMD Science Keywords
  • SOILS
  • VEGETATION COVER
  • LAND USE/LAND COVER
ANZSRC Fields of Research
  • Environmental management
  • Climate change impacts and adaptation
TERN Platform Vocabulary
  • Sentinel-2A
  • Sentinel-2B
TERN Instrument Vocabulary
  • MSI
  • MSI
  • MSI
TERN Parameter Vocabulary
  • bare soil fraction
  • Percent
  • photosynthetic vegetation fraction
  • Percent
  • non-photosynthetic vegetation fraction
  • Percent
QUDT Units of Measure
  • Percent
  • Percent
  • Percent
GCMD Horizontal Resolution Ranges
  • 1 meter - < 30 meters
GCMD Temporal Resolution Ranges
  • Seasonal

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
Linkage
https://w3id.org/tern/static/cc-by/88x31.png

Title
Creative Commons Attribution 4.0 International Licence
Alternate title
CC-BY
Edition
4.0
Website
https://creativecommons.org/licenses/by/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
<p>It is not recommended that these data sets be used at scales more detailed than 1:100,000.</p>

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

Distribution format
  • NetCDF

Distributor

Distributor

Terrestrial Ecosystem Research Network
Building 1019, 80 Meiers Rd
Indooroopilly
QLD
4068
Australia
OnLine resource
Differences between Fractional Cover version 2 and version 3

Distribution Information

Distribution format

Distributor

Distributor

Terrestrial Ecosystem Research Network
80 Meiers Road, Indooroopilly, Queensland, 4068, Australia
Indooroopilly
Queensland
4068
Australia
OnLine resource
Cloud Optimised GeoTIFFs - Seasonal Fractional Cover - Sentinel-2, v3.0

OnLine resource
GitLab Code for Fractional Cover version 3

OnLine resource
sentinel_fractional_v3

Seasonal Fractional Cover - Sentinel-2, v3.0

OnLine resource
Landscape Data Visualiser - Seasonal Fractional Cover - Sentinel-2, JRSRP Algorithm Version 3.0, Eastern and Central Australia Coverage

OnLine resource
Vegmachine Timeseries Viewer

OnLine resource
ro-crate-metadata.json

Data quality info

Hierarchy level
Dataset
Other
1) All the data described here has been generated from the analysis of Sentinel-2 data, which has a spatial resolution of approximately 10&nbsp;m in the Blue, Green, Red and Near Infra-red (NIR) bands, and 20&nbsp;m in the two Short Wave Infra-red (SWIR) band. The 20&nbsp;m bands have been resampled to 10&nbsp;m using cubic convolution, to provide a consistent 10&nbsp;m data set. The imagery is rectified during processing by the European Space Agency (ESA), and not modified spatially beyond that.<br> 2) The fractional cover model was compared to samples drawn from approximately 4000 field reference sites.
Title
Sentinel 2 Performance and Data Quality Reports
Website
https://sentiwiki.copernicus.eu/web/document-library#DocumentLibrary-PerformanceandDataQualityReportsLibrary-S2-Performance-DQR

Abstract
Sentinel 2 Performance and Data Quality Reports

Report

Result

Statement
1) The Sentinel-2 Data Quality Report from ESA indicates that positional accuracy is on the order of 12 m.<br> 2) The fractional cover model predicts the vegetation cover fractions with MAE/wMAPE/RMSE of:<br> bare - 6.9%/34.9%/14.5%<br> PV - 4.6%/37.9%/10.6%<br> NPV - 9.8%/25.2%/16.9%.<br>

Resource lineage

Statement
<p>Summary of processing:<br> Sentinel 2 surface reflectance data > multiple single-date fractional cover datasets > seasonal composite of fractional cover <br />Further details are provided in the Methods section.</p>
Hierarchy level
Dataset
Title
Sentinel 2 Level 1C Algorithms and Products
Website
https://sentinels.copernicus.eu/web/sentinel/technical-guides/sentinel-2-msi/level-1c-algorithms-products

Method documentation

Title
Zhu, Z., & Woodcock, C. E. (2012). Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sensing of Environment, 118, 83–94. https://doi.org/10.1016/J.RSE.2011.10.028
Website
https://doi.org/10.1016/J.RSE.2011.10.028

Method documentation

Title
Flood, N. (2017). Comparing Sentinel-2A and Landsat 7 and 8 Using Surface Reflectance over Australia. Remote Sensing, 9(7). https://doi.org/10.3390/rs9070659
Website
https://doi.org/10.3390/rs9070659

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
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

Process step

Description
Image Pre-processing:<br> Sentinel-2 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).

Process step

Description
Fractional Cover Model:<br> A multilayer perceptron (MLP) model is used to estimate percentage cover in three fractions – bare ground, photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV) from surface reflectance, for every image captured within the season. The MLP model was trained with Tensorflow using Landsat TM, ETM+ and OLI surface reflectance and a collection of approximately 4000 field observations of overstorey and ground cover. The field observations covered a wide variety of vegetation, soil and climate types across Australia, collected between 1997 and 2018 following the procedure outlined in Muir et al (2011). As the model is trained on Landsat imagery, the Sentinel-2 reflectance values are slightly adjusted to more closely resemble Landsat imagery, then the fractional cover model is applied. The model was assessed to predict the vegetation cover fractions with MAE/wMAPE/RMSE of:<br> bare - 6.9%/34.9%/14.5%<br> photosynthetic vegetation (PV) - 4.6%/37.9%/10.6%<br> non-photosynthetic vegetation (NPV) - 9.8%/25.2%/16.9%.

Process step

Description
Data Compositing:<br> The method of compositing selected representative pixels through the determination of the medoid (multi-dimensional equivalent of the median) of at least three observations of fractional cover imagery. The medoid is the point which minimises the total distance between the selected point and all other points. Thus the selected point is “in the middle” of the set of points. It is robust against extreme values, inherently avoiding the selection of outliers, such as occurs when cloud or cloud shadow goes undetected. Unfortunately, due to the high level of cloud cover in some areas, often three cloud free pixels are not available, resulting in data gaps in the seasonal fractional cover image. For further details on this method see Flood (2013).

Reference System Information

Reference system identifier
EPSG/EPSG:3577

Reference system type
Geodetic Geographic 2D

Metadata

Metadata identifier
urn:uuid/13810293-c6b5-442b-bfcd-817700738e0d

Title
TERN GeoNetwork UUID

Language
English
Character encoding
UTF8

Point of contact

Terrestrial Ecosystem Research Network
Building 1019, 80 Meiers Rd
Indooroopilly
QLD
4068
Australia
+61 7 3365 9097

Type of resource

Resource scope
Dataset
Metadata linkage
https://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/13810293-c6b5-442b-bfcd-817700738e0d

Point-of-truth metadata URL

Date info (Creation)
2022-03-28T00:00:00.000000+00:00
Date info (Revision)
2025-12-10T10:17:25.483814+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

Code
10.5281/zenodo.5652221
Website
https://github.com/ternaustralia/TERN-ISO19115/releases/tag/v1.0

 
 

Overviews

Spatial extent

N
S
E
W


N
S
E
W


Keywords

ANZSRC Fields of Research
Climate change impacts and adaptation Environmental management
GCMD Science Keywords
LAND USE/LAND COVER SOILS VEGETATION COVER

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