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Data

Seasonal dynamic reference cover method - Landsat, JRSRP, Queensland and Northern Territory Coverage 

Ver: 2.0
Status of Data: superseded
Update Frequency: notPlanned
Security Classification: unclassified
Dataset Published: 2021-11-11
Dataset Last Modified: 2026-08-18
Metadata viewed 54789 times
Dataset accessed 22 times
Metadata Created: 2017-10-10
Metadata Last Modified: 2026-08-19
How to cite this collection:
Joint Remote Sensing Research Program, Department of the Environment, Tourism, Science and Innovation, Queensland Government & Bastin, G. (2021). Seasonal dynamic reference cover method - Landsat, JRSRP, Queensland and Northern Territory Coverage. Version 2.0. Terrestrial Ecosystem Research Network. Dataset. https://portal.tern.org.au/metadata/90b588e0-1220-4cee-8468-34879e44c1bd 
Data can be accessed from the following links:
HTTPseasonal_dynamic_reference_cover_image_landsat_file_4WaRgWp.txt
HTTPHTTP Download
HTTPPoint-of-truth metadata URL
HTTPro-crate-metadata.json
This product has been superseded and will not be processed from early 2023. Please find the updated version 3 of this product here Seasonal dynamic reference cover method - Landsat, JRSRP algorithm version 3.0, Queensland Coverage. The seasonal dynamic reference cover method images are created using a modified version of the dynamic reference cover method developed by Bastin et al (2012). This approach calculates a minimum ground cover image over all years to identify locations of most persistent ground cover in years with the lowest rainfall, then uses a moving window approach to calculate the difference between the window's central pixel and its surrounding reference pixels. The output is a difference image between the cover amount of a pixel's reference pixels and the actual cover at that pixel for the season being analysed. Negative values indicate pixels which have less cover than the reference pixels.
The main differences between this method and the original method are that this method uses seasonal fractional ground cover rather than the preceding ground cover index (GCI) and this method excludes cleared areas and certain landforms (undulating slopes), which are considered unsuitable for use as reference pixels. 
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. This dataset was produced using Landsat data sourced from US Geological Survey. 
Purpose
This product provides a way to compare ground cover across the landscape within a particular season. 
Lineage
Data not provided. 
Method DocumentationData not provided.
Procedure StepsData not provided.
Spatial Description
Queensland and Northern Territory 
Temporal Coverage
From 1986-06-01 to on going 
Spatial Resolution

Data not provided.

Vertical Extent

Data not provided.

Data Quality Assessment Scope
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.
The fractional cover model was compared to samples drawn from 1500 field reference sites.
The imagery has been corrected for height displacement using a 3" digital elevation model (DEM) based on the National Aeronautics and Space Administration (NASA), Shuttle Radar Topography Mission (SRTM). 
Data Quality Report
Data not provided. 
Data Quality Assessment Outcome
The USGS aims to provide image-to-image registration with an accuracy of 12m. Refer to the L8 Data Users Handbook for more detail.
The fractional cover model achieved an overall model Root Mean Squared Error (RMSE) of 11.6% against field reference sites. 
ANZSRC - FOR
Climate change impacts and adaptation
Environmental management
Data Stream
Satellite Remote Sensing
GCMD Sciences
LAND USE/LAND COVER
VEGETATION - VEGETATION COVER
Horizontal Resolution
30 meters - < 100 meters
Parameters
vegetation area fraction
Platforms
LANDSAT-5
LANDSAT-7
LANDSAT-8
Project
TERN Landscapes
Temporal Resolution
Monthly - < Annual
Topic
environment
imageryBaseMapsEarthCover
Author
Joint Remote Sensing Research Program
Department of the Environment, Tourism, Science and Innovation, Queensland Government
Co-Author
Bastin, Gary
Contact Point
Data Enquiries, Earth Observation and Social Sciences (EOSS)
Publisher
Terrestrial Ecosystem Research Network
Bastin G., et al (2012) Separating grazing and rainfall effects at regional scale using remote sensing imagery: A dynamic reference-cover method. Remote Sensing of Environment.
Flood, N. (2013) Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-dimensional Median). Remote Sens. 2013, 5(12), 6481-6500;
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.
Supplemental Information
Output for this product is in the form of a two band TIFF image. Band 1 - the 'delta GC' image. Band 2 - the reference pixel image 
Resource Specific Usage
Data not provided. 
Environment Description
Data not provided. 
Terrestrial Ecosystem Research Network
80 Meiers Road, Indooroopilly, Queensland, 4068, Australia.
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Creative Commons Attribution 4.0 International Licence
https://creativecommons.org/licenses/by/4.0/
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/ 
Copyright 2010-2021. JRSRP. Rights owned by the Joint Remote Sensing Research Project (JRSRP). 
It is not recommended that these data sets be used at scales more detailed than 1:100,000. 
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. 
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