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Seasonal cover deciles - Landsat, JRSRP algorithm, Australia Coverage

Ver: 1.0
Status of Data: superseded
Security Classification: unclassified
Viewed: 0
Accessed: 0

Description

This product has been superseded and will not be processed from early 2023.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/24070. Two fractional cover decile products, green cover and total cover, are currently produced from the historical timeseries of seasonal fractional cover images. These products compare, at the per-pixel level, the level of cover for the specific season of interest against the long term cover for that same season. For each pixel, all cover values for the relevant seasons within a baseline period (1988 to 2013) are classified into deciles. The cover value for the pixel in the season of interest is then classified according to the decile in which it falls.

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.

Purpose
These decile datasets are an excellent way of identifying areas of low or high cover, relative to what is typical for that location and season.

Lineage
Summary of processing: Seasonal composite of fractional cover > baseline statistics > seasonal cover deciles.
Further details are provided in the Methods section.

Data Creation
Rankings: The seasonal fractional cover timeseries for the period Autumn (Mar-May) 1988 to Summer (Dec-Feb) 2012/2013 is used as a baseline. Every season is ranked against every available seasonal value within the baseline period, for the corresponding season, on a per-pixel basis. Rankings are expressed as deciles, so a cover value which falls within the bottom 10% of values in the baseline period is given as decile 1, and a cover value which falls in the top 10% is given as decile 10. Two versions of this are created – one which ranks total cover (green + non-green), and one which ranks only the green fraction. Because the seasonal composites are used, the data are representative of the season, and robust against outliers. The baseline period is sampled evenly across the whole period, so there is no bias towards the years with more imagery available.
Example: For example, a total cover value for Spring 2013 is ranked against the total cover in all the Spring images in the baseline period. A green cover value in Spring 2013 is ranked against the green cover fractions in all the Spring images in the baseline period.
Seasonal fractional cover process: Refer to the Methods section in Seasonal fractional cover - Landsat, JRSRP algorithm, Australia coverage https://portal.tern.org.au/22026

Temporal coverage

From 12/1/1987

Dates

Creation date

11/25/2013

Publication date

4/15/2021

Revision date

10/23/2024

Citation information

How to cite this collection:

Department of Environment and Science (2017-2023), Queensland Government (2021): Seasonal cover deciles - Landsat, JRSRP algorithm, Australia Coverage. Version 1.0. Terrestrial Ecosystem Research Network. (Dataset). https://portal.tern.org.au/metadata/TERN/7d3cd98f-32da-40d4-9a3f-d89eb76347f9

Rights and Licensing

CC-BY

Creative Commons Attribution 4.0 International Licence
http://creativecommons.org/licenses/by/4.0

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 https://www.tern.org.au/research-publications/#reporting
It is not recommended that these data sets be used at scales more detailed than 1:100,000.

Keywords

Parameters
GCMD Science
ANZSRC - FOR
Horizontal Resolution
Temporal Resolution
Topic Categories

People and Organisation

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Data Quality

Data QualityData Quality
  • Data Quality Assessment Scope:
    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.
  • Data Quality Assessment Result:
    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.

Additional information

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