- Date (Creation)
- Date (Publication)
- Date (Revision)
Department of Environment and Science, Queensland Government
41 Boggo Road, Dutton Park, QLD, 4102, Australia
- This product captures variability in persistent green cover at seasonal (i.e. three-monthly) time scales, forming a consistent time series from 1989 to the present season (minus 2 years). It is useful for investigating inter-annual and longer term changes in persistent vegetation cover. The statistical process used to create this product means there is a 2 year lag in producing it. </br> 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.</br> This product is based upon the JRSRP Fractional Cover 3.0 algorithm.
- 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.
- This dataset was produced by the Joint Remote Sensing Research Program using data sourced from US Geological Survey.
- 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
- Spatial resolution
- Topic category
- Imagery base maps earth cover
- Time period
- Maintenance and update frequency
- GCMD Science Keywords
- ANZSRC Fields of Research
- TERN Platform Vocabulary
- TERN Instrument Vocabulary
- TERN Parameter Vocabulary
- QUDT Units of Measure
- GCMD Horizontal Resolution Ranges
- GCMD Temporal Resolution Ranges
- 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
- File description
- CCBy Logo from creativecommons.org
- File type
- Creative Commons Attribution 4.0 International Licence
- Alternate title
- Access constraints
- 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.
- Supplemental Information
- Filenames for the seasonal persistent green product conforms to the AusCover standard naming convention. The standard form of this convention is:</br> <satellite category code><instrument code><product code>_<where>_<when>_<processing stage code>_<additional dataset specific tags></br> For this dataset are (comma-separated):</br> Data Naming Element, Possible Code(s), Descriptor Standard Elements</br> satellite category, lz, Landsat - all possible</br> instrument, tm, thematic mapper</br> product, re, reflective</br> where, qld,nsw,vic,tas,sa,nt,wa, state</br> when, myyyymmyyyymm, season start date (1st day of month) and season end date (last day of month)</br> processing stage, dp7, seasonal persistent green cover</br> data projection, a2, Australian Albers Equal Area</br> Raster data values represent percentages of persistent green cover, with a no data value of 255
Data quality info
- Hierarchy level
- 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.</br> 2) The fractional cover model was compared to samples drawn from approximately 4000 field reference sites.
- 1) The USGS aims to provide image-to-image registration with an accuracy of 12m. Refer to the L8 Data Users Handbook for more detail.</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>
- Summary of processing: Landsat surface reflectance data > multiple single-date fractional cover datasets > seasonal composite of fractional cover > seasonal persistent green product. <br />Further details are provided in the Methods section.
- Hierarchy level
- 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).
- Fractional Cover Model: 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). 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%
- 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).
- Persistent Green Fractional Cover: Smoothing splines are fitted in multiple iterations per pixel through the full time series of seasonal fractional cover (green fraction only). At each iteration, zero weight is given to observations that lie above the spline, and observation below the line are weighted proportion to the size of the residual. Observations greater than 3 standard deviations from the residual mean are given zero weight, and those between 2 and 3 standard deviations are given less weight, this avoids contamination by outliers. Persistent green fractional cover for each season is estimated from the final spline iteration at each seasonal time step. Values reported are as for fractional cover, ie. percentages of cover. Areas with frequent seasonal fractional cover data gaps due to cloud may produce unreliable estimates of persistent green cover. A single band (byte) image is produced: persistent green vegetation cover (in percent).
Reference System Information
- Reference system identifier
- Reference system type
- Geodetic Geographic 2D
- Metadata identifier
- TERN GeoNetwork UUID
- Character encoding
Point of contact
Type of resource
- Resource scope
- Date info (Creation)
- Date info (Revision)
- ISO 19115-1:2014/AMD 1:2018 Geographic information - Metadata - Fundamentals
- ISO/TS 19115-3:2016
- ISO/TS 19157-2:2016
- Terrestrial Ecosystem Research Network (TERN) Metadata Profile of ISO 19115-3:2016 and ISO 19157-2:2016
- Date (published)