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Seasonal persistent green - Landsat, JRSRP algorithm, Australia coverage


An estimate of persistent green cover per season. This is intended to estimate the portion of vegetation that does not completely senesce within a year, which primarily consists of woody vegetation (trees and shrubs), although there are exceptions where non-woody cover remains green all year round. It is derived by fitting a multi-iteration minimum weighted smoothing spline through the green fraction of the seasonal fractional cover (dim) time series.

This dataset was produced by the Joint Remote Sensing Research Program using data sourced from US Geological Survey.

This product captures variability in persistent green cover at seasonal (ie 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 changes in persistent vegetation cover. The statistical process used to create this product means there is a 2 year lag in producing it. 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. Note: A new fractional cover algorithm will be implemented during 2021, based on additional field validation and a new machine learning approach. This will lead to a new version of the persistent green product.


Summary of processing: Landsat surface reflectance data > multiple single-date fractional cover datasets > seasonal composite of fractional cover > seasonal persistent green product.
Further details are provided in the Methods section.

Temporal coverage

From 1989-12-01


  • Date modified


Citation information

How to cite this collection:

Department of Environment and Science, Queensland Government (2021): Seasonal persistent green - Landsat, JRSRP algorithm, Australia coverage. Version 1.0.0. Terrestrial Ecosystem Research Network (TERN). Dataset.

Access data

This data can be accessed from the following websites

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Source Metadata URL

Rights and Licensing

Creative Commons Attribution 4.0 International Licence

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.
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.

Please advise any work or publications that use this data via the online form at

It is not recommended that these data sets be used at scales more detailed than 1:100,000.

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  • Additional information Show


      Research Groups

      Distributed by


      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
      The bare soil, green vegetation and non-green vegetation endmembers for the combination of Landsat-5 TM and Landsat-7 are calculated using models linked to an intensive field sampling program whereby more than 1500 sites covering a wide variety of vegetation, soil and climate types were sampled to measure overstorey and ground cover following the procedure outlined in Muir et al (2011).A constrained linear spectral unmixing is applied to the image archive using the derived endmembers and has an overall model Root Mean Squared Error (RMSE) of 11.6%. Values are reported as percentages of cover plus 100. The fractions stored in the 4 image layers are: Band1 - bare (bare ground, rock, disturbed), Band2 - green vegetation, Band3 - non green vegetation (litter, dead leaf and branches), Band4 - Model fitting error.
      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 plus 100. 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) + 100


      Data Quality

      • 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 1500 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. 2) The fractional cover model achieved an overall model Root Mean Squared Error (RMSE) of 11.6% against field reference sites.
    • Keywords Show


      • persistent green vegetation fraction (Percent)
      • vegetation area fraction (Percent)


      • LANDSAT-5
      • LANDSAT-7
      • LANDSAT-8


      • TM
      • ETM+
      • OLI

      Temporal Resolution

      • Weekly - < Monthly

      GCMD Science


      ANZSRC - FOR


      User Defined

      • environment
      • imageryBaseMapsEarthCover
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