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Data

Seasonal ground cover statistics - Landsat, JRSRP algorithm, QLD coverage 

Ver: 1.0
Status of Data: superseded
Update Frequency: notPlanned
Security Classification: unclassified
Dataset Published: 2021-09-22
Dataset Last Modified: 2026-08-18
Metadata viewed 1044 times
Dataset accessed 84 times
Metadata Created: 2015-09-18
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 (2021). Seasonal ground cover statistics - Landsat, JRSRP algorithm, QLD coverage. Version 1.0. Terrestrial Ecosystem Research Network. Dataset. https://portal.tern.org.au/metadata/86c19d64-7cfe-4557-a874-479d024ac1b5 
Data can be accessed from the following links:
HTTPSeasonal ground cover statistics
HTTPseasonal_ground_cover_statistics_landsat_filenaming_Oc4tUUV.txt
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This product has been superseded and will not be processed from early 2023.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 at https://portal.tern.org.au/metadata/TERN/b9c2e3d3-0dc4-4599-a1dd-6affb0ad3f74. Long term temporal statistic products derived from the seasonal ground cover product for each fraction. Statistics include: 5th percentile minimum, mean, median, 95th percentile maximum, standard deviation and observation count. There is one raster image for each season and each bare and green fraction for the full time series of imagery available. Min/max (5th and 95th percentile) products are also made for each fraction using all seasonal ground cover images available. 
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 by the Joint Remote Sensing Research Program (https://www.jrsrp.org.au/) using data sourced from US Geological Survey. 
Purpose
These products display the variation of the seasonal ground cover fractions over long term temporal periods (e.g. 1990-2016). 
Lineage
Data not provided. 
Method DocumentationData not provided.
Procedure StepsData not provided.
Spatial Description
Queensland 
Temporal Coverage
From 1990-01-01 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. 
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
SOILS
VEGETATION - VEGETATION COVER
Horizontal Resolution
30 meters - < 100 meters
Instruments
ETM+
OLI
TM
Parameters
bare soil fraction
non-photosynthetic vegetation fraction
photosynthetic vegetation 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
Contact Point
Data Enquiries, Earth Observation and Social Sciences (EOSS)
Publisher
Terrestrial Ecosystem Research Network
de Vries, C., Danaher, T., Denham, R., Scarth, P. & Phinn, S. (2007). An operational radiometric calibration procedure for the Landsat sensors based on pseudo-invariant target sites, Remote Sensing of Environment, vol. 107, no. 3, pp. 414-429.
Armston, J. D., Danaher, T.J., Goulevitch, B. M., and Byrne, M. I., (2002). Geometric correction of Landsat MSS, TM, and ETM+ imagery for mapping of woody vegetation cover and change detection in Queensland.
Danaher, T., Scarth, P., Armston, J., Collet, L., Kitchen, J., and Gillingham, S. (2010). Ecosystem Function in Savannas: Measurement and Modelling at Landscape to Global Scales.
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
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.
Muir, J. et al (2011), Field measurement of fractional ground cover: supporting ground cover monitoring for Australia. ABARES. Canberra
Supplemental Information
Processing stage:
djl - bare min/max all seasons
djm - green min/max all seasons
djn - dry min/max all seasons


djo - summer stats
djp- autumn stats
djq- winter stats
djr- spring stats 
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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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/ 
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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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