TERN Geospatial Catalogue
Seasonal fractional cover - Landsat, JRSRP algorithm Version 3.0, Australia coverage
The seasonal fractional cover product shows representative values for the proportion of bare, green and non-green cover across a season. It is a spatially explicit raster product, which predicts vegetation cover at medium resolution (30 m per-pixel) for each 3-month calendar season. The green and non-green fractions may include a mix of woody and non-woody vegetation. A 3 band (byte) image is produced: band 1 – bare ground fraction (in percent), band 2 - green vegetation fraction (in percent), band 3 – non-green vegetation fraction (in percent). The no data value is 255.
Simple
Identification info
- Date (Creation)
- 2022-03-28
- Date (Publication)
- 2022-05-03
- Date (Revision)
- 2014-07-14
- Edition
- 1.0
Publisher
Author
Joint Remote Sensing Research Program
Chamberlain Building (35), Campbell Road, St Lucia, QLD, 4072, Australia
St Lucia
QLD
4072
Australia
Rights holder
Joint Remote Sensing Research Program
Chamberlain Building (35), Campbell Road, St Lucia, QLD, 4072, Australia
St Lucia
QLD
4072
Australia
- Website
- https://www.tern.org.au/
- Purpose
- This product captures variability in fractional cover at seasonal (i.e. three-monthly) time scales, forming a consistent time series from 1987 - present. It is useful for investigating inter-annual changes in vegetation cover and analysing regional comparisons. For applications that focus on non-woody vegetation, the ground cover product, derived from fractional cover, may be more suitable. For applications investigating rapid change during a season, monthly composite or single-date (available on request) fractional cover products may be more appropriate. This product is based upon the JRSRP Fractional Cover 3.0 algorithm.
- 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
- This dataset was produced by the Joint Remote Sensing Research Program using data sourced from US Geological Survey.
- Status
- On going
Point of contact
Department of Environment and Science, Queensland Government - van den Berg, Deanna ()
Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD, 4102, Australia
Ecosciences Precinct, 41 Boggo Road
Dutton Park
QLD
4102
Australia
Spatial resolution
- Spatial resolution
- 30
- Topic category
-
- Environment
- Imagery base maps earth cover
Extent
- Description
- Australia
N
S
E
W
))
Temporal extent
- Time period
- 1987-12-01
- Title
- Flood, N., Danaher, T., Gill, T. and Gillingham, S. (2013) An Operational Scheme for Deriving Standardised Surface Reflectance from Landsat TM/ETM+ and SPOT HRG Imagery for Eastern Australia. Remote Sens. 2013, 5(1), 83-109. doi:10.3390/rs5010083
- Website
-
Flood, N., Danaher, T., Gill, T. and Gillingham, S. (2013) An Operational Scheme for Deriving Standardised Surface Reflectance from Landsat TM/ETM+ and SPOT HRG Imagery for Eastern Australia. Remote Sens. 2013, 5(1), 83-109. doi:10.3390/rs5010083
Related documentation
- Title
- Zhu, Z. and Woodcock, C.E. (2012). Object-based cloud and cloud shadow detection in Landsat imagery Remote Sensing of Environment 118. doi:10.1016/j.rse.2011.10.028
- Website
-
Zhu, Z. and Woodcock, C.E. (2012). Object-based cloud and cloud shadow detection in Landsat imagery Remote Sensing of Environment 118. doi:10.1016/j.rse.2011.10.028
Related documentation
- Title
- Muir, J. et al (2011), Field measurement of fractional ground cover: supporting ground cover monitoring for Australia. ABARES. Canberra
- Website
-
Muir, J. et al (2011), Field measurement of fractional ground cover: supporting ground cover monitoring for Australia. ABARES. Canberra
Related documentation
- Title
- Flood, N. (2013) Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-dimensional Median). Remote Sens. 2013, 5(12), 6481-6500
- Website
-
Flood, N. (2013) Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-dimensional Median). Remote Sens. 2013, 5(12), 6481-6500
Related documentation
- Maintenance and update frequency
- Quarterly
- GCMD Science Keywords
- ANZSRC Fields of Research
- TERN Platform Vocabulary
- TERN Instrument Vocabulary
- TERN Parameter Vocabulary
- 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
- It is not recommended that these data sets be used at scales more detailed than 1:100,000.
Resource constraints
- Classification
- Unclassified
- Supplemental Information
- A 3 band (byte) image is produced: band 1 – bare ground fraction (bare ground, rock, disturbed) in percent, band 2 - green vegetation fraction in percent, band 3 – non-green vegetation fraction (litter, dead leaf and branches) in percent. The no data value is 255.
Distribution Information
Distributor
Distributor
- OnLine resource
- Differences between Fractional Cover version 2 and version 3
Distribution Information
Distributor
Distributor
Terrestrial Ecosystem Research Network
Building 1019, 80 Meiers Rd, Indooroopilly, QLD, Australia, 4068
Indooroopilly
QLD
4068
Australia
- OnLine resource
- Seasonal Fractional Cover via HTTP
- OnLine resource
- Vegmachine Timeseries Viewer
- OnLine resource
- GitLab Code for Fractional Cover version 3
Data quality info
- Hierarchy level
- Dataset
- Other
- 1) The input imagery was processed to level L1T by the USGS. Geodetic accuracy of the product depends on the image quality and the accuracy, number, and distribution of the ground control points. 2) The fractional cover model was compared to samples drawn from approximately 4000 field reference sites.
Report
Result
- Statement
- 1) The USGS aims to provide image-to-image registration with an accuracy of 12 m. Refer to the L8 Data Users Handbook for more detail. 2) The fractional cover model predicts the vegetation cover fractions with MAE/wMAPE/RMSE of: bare - 6.9%/34.9%/14.5% PV - 4.6%/37.9%/10.6% NPV - 9.8%/25.2%/16.9%.
Resource lineage
- Statement
- Summary of processing: Landsat surface reflectance data > multiple single-date fractional cover datasets > medoid calculation for seasonal composite of fractional cover <br />Further details are provided in the Methods section.
- Hierarchy level
- Dataset
Process step
- Description
- Image Pre-Processing: All input Landsat TM/ETM+/OLI imagery was downloaded from the USGS EarthExplorer website as level L1T imagery. Images which the EarthExplorer site rated as having greater than 80% cloud cover were not downloaded. The imagery has been corrected for atmospheric effects, and bi-directional reflectance and topographic effects, using the methods detailed by Flood et al (2013). The result is surface reflectance standardised to a fixed viewing and illumination geometry. Cloud, cloud shadow and snow have been masked out using the Fmask automatic cloud mask algorithm. Topographic shadowing has been masked using the Shuttle Radar Topographic Mission DEM at 30 m resolution. Water has been masked out using the methods outlines in Danaher & Collett (2006).
Process step
- Description
- Fractional Cover Model (Version 3.0): 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, and were collected between 1997 and 2018 following the procedure outlined in Muir et al (2011). The model was assessed to predict the vegetation cover fractions with MAE/wMAPE/RMSE of: bare - 6.9%/34.9%/14.5% PV - 4.6%/37.9%/10.6% NPV - 9.8%/25.2%/16.9%.
Process step
- Description
- Seasonal Compositing: The method of compositing used selection of representative pixels through the determination of the medoid (multi-dimensional equivalent of the median) of three months (a season) 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. The value selected is a specific data point and not an averaged or blended value. It is robust against extreme values, inherently avoiding the selection of outliers, such as occurs when cloud or cloud shadow goes undetected. At least three pixels from the time-series of imagery for the season must be available. 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/0997cb3c-e2e2-45be-ac82-f5e13d24331c
- 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/0997cb3c-e2e2-45be-ac82-f5e13d24331c
Point-of-truth metadata URL
- Date info (Creation)
- 2022-03-28T00:00:00
- Date info (Revision)
- 2022-11-21T04:41:20
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