Data

Area of Applicability Summary, Landsat Seasonal Fractional Cover Version 3.0, Australia Coverage

Terrestrial Ecosystem Research Network
Joint Remote Sensing Research Program ; Department of the Environment, Tourism, Science and Innovation, Queensland Government
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=http://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/b02f7a17-1f95-4bca-bb4b-df949b13f241&rft.title=Area of Applicability Summary, Landsat Seasonal Fractional Cover Version 3.0, Australia Coverage&rft.identifier=http://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/b02f7a17-1f95-4bca-bb4b-df949b13f241&rft.publisher=Terrestrial Ecosystem Research Network&rft.description=The Area of Applicability (AOA) describes the area to which a predictive model can reliably be applied, based on the predictor space covered by the underlying training data. It was evaluated following the approach proposed by Meyer and Pebesma (2021). The JRSRP seasonal surface reflectance composites between winter 2014 and winter 2024 were used as a proxy for the range of representative surface reflectance values likely to be encountered across the continent under varying environmental conditions from which fractional cover predictions are made. The AOA of the FCv3 model was computed for each seasonal surface reflectance composite, then summarised as a frequency map representing the proportion of seasons that a location was outside the AOA. For each state, five files are provided: an annual product summarising the AOA across all seasons, and four showing seasonal AOA frequencies for summer, autumn, winter, and spring.The training data for the FC3 model (SLATS Star Transects – Australian field sites), consisting of approximately 4000 field observations of fractional cover collected across Australia between 1997 to 2018, were matched to the nearest date, clear Landsat 5 TM,7 ETM+ or 8 OLI overpass, and the surface reflectance values calculated using the procedures described in Flood et. al. (2013), for a 3x3 pixel window. Using the approach described in Meyer and Pebesma (2021), minimum distances between weighted predictors in the training data were calculated. An AOA threshold defined as the outlier removed maximum dissimilarity index (DI) of the training data was derived via cross-validation. The value of this threshold was found to be 0.128. A DI image was then calculated to quantify the dissimilarity between each seasonal surface reflectance composite and the reflectance values of the FC3 model calibration data. The final AOA summary data was then calculated by stacking all seasonal DI images and recording the number of times the AOA threshold was exceeded. The count and percentage of AOA threshold exceedance was stored as band 1 and band 2 respectively in the output raster. Finally, ocean pixels were masked and set to the no data value of 255.Progress Code: completedMaintenance and Update Frequency: notPlanned&rft.creator=Joint Remote Sensing Research Program &rft.creator=Department of the Environment, Tourism, Science and Innovation, Queensland Government &rft.date=2025&rft.edition=1&rft.relation=http://dx.doi.org/10.3390/rs5126481&rft.relation=https://doi.org/10.3390/rs5010083&rft.relation=http://dx.doi.org/10.1111/2041-210X.13650&rft.coverage=Australia&rft.coverage=northlimit=-10.314919; southlimit=-44.490237; westlimit=111.972656; eastLimit=154.652342; projection=EPSG:3577&rft_rights=Creative Commons Attribution 4.0 International Licence http://creativecommons.org/licenses/by/4.0&rft_rights=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&rft_rights=Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}.&rft_subject=environment&rft_subject=VEGETATION COVER&rft_subject=Environmental Management&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=ENVIRONMENTAL SCIENCE AND MANAGEMENT&rft_subject=LANDSAT-7&rft_subject=LANDSAT-8&rft_subject=LANDSAT-9&rft_subject=area of applicability (Percent)&rft_subject=Percent&rft_subject=30 meters - < 100 meters&rft_subject=Decadal&rft.type=dataset&rft.language=English Access the data

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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

Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}.

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Contact Information

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Brief description

The Area of Applicability (AOA) describes the area to which a predictive model can reliably be applied, based on the predictor space covered by the underlying training data. It was evaluated following the approach proposed by Meyer and Pebesma (2021).

The JRSRP seasonal surface reflectance composites between winter 2014 and winter 2024 were used as a proxy for the range of representative surface reflectance values likely to be encountered across the continent under varying environmental conditions from which fractional cover predictions are made. The AOA of the FCv3 model was computed for each seasonal surface reflectance composite, then summarised as a frequency map representing the proportion of seasons that a location was outside the AOA.

For each state, five files are provided: an annual product summarising the AOA across all seasons, and four showing seasonal AOA frequencies for summer, autumn, winter, and spring.

Notes

Data Usage
The Area of Applicability summary dataset contains two bands. Band 1 values are the count of seasons a pixel was outside the AOA. Band 2 values are the percentage of seasons a pixel was outside the AOA. No data is represented by a value of 255.

Lineage

The training data for the FC3 model (SLATS Star Transects – Australian field sites), consisting of approximately 4000 field observations of fractional cover collected across Australia between 1997 to 2018, were matched to the nearest date, clear Landsat 5 TM,7 ETM+ or 8 OLI overpass, and the surface reflectance values calculated using the procedures described in Flood et. al. (2013), for a 3x3 pixel window.

Using the approach described in Meyer and Pebesma (2021), minimum distances between weighted predictors in the training data were calculated. An AOA threshold defined as the outlier removed maximum dissimilarity index (DI) of the training data was derived via cross-validation. The value of this threshold was found to be 0.128.

A DI image was then calculated to quantify the dissimilarity between each seasonal surface reflectance composite and the reflectance values of the FC3 model calibration data. The final AOA summary data was then calculated by stacking all seasonal DI images and recording the number of times the AOA threshold was exceeded. The count and percentage of AOA threshold exceedance was stored as band 1 and band 2 respectively in the output raster.

Finally, ocean pixels were masked and set to the no data value of 255.

Progress Code: completed
Maintenance and Update Frequency: notPlanned

Notes

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
This dataset is a summary of the Area of Applicability (AOA) of the JRSRP Fractional Cover version 3.0 model, for the period winter 2014 to winter 2024.

Created: 2025-04-30

Issued: 2025-08-10

Modified: 2025-12-10

Data time period: 2014-06-01 to 2024-08-31

This dataset is part of a larger collection

154.65234,-10.31492 154.65234,-44.49024 111.97266,-44.49024 111.97266,-10.31492 154.65234,-10.31492

133.312499,-27.402578

text: Australia

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Other Information
Point-of-truth metadata URL

uri : https://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/b02f7a17-1f95-4bca-bb4b-df949b13f241

Meyer H, Pebesma E (2021) Predicting into unknown space? Estimating the area of applicability of spatial prediction models. Methods in Ecology and Evolution 12(9), 1620-1633.

uri : https://www.researchgate.net/publication/352050132_Predicting_into_unknown_space_Estimating_the_area_of_applicability_of_spatial_prediction_models