• TERN Geospatial Catalogue
  •   Search
  •   Map

Queensland Brigalow Belt Bioregion Spatial BioCondition, 2019, Version 1.0

Version 1 of the Brigalow Belt Bioregion Spatial BioCondition dataset is superseded by the Version 2 dataset that can be found at: https://doi.org/10.25901/rnqz-cn10 .<br><br>


Version 1 was an initial demonstration version. The version 1 data has been removed from publication to negate temporal comparisons between v1 (2019) and v2 (2021), as this is a future goal for the product but still in development phase.


This was a spatial dataset comprising predictions of vegetation condition for biodiversity for the brigalow belt bioregion. The dataset was created using a gradient boosting decision tree (GBDT) model based on eight vegetation specific remote sensing (RS) datasets and 17,000 training sites of known vegetation community and condition state. Condition score was modelled as a function of the difference in the RS space within homogeneous vegetation communities. The product was intended to represent predicted BioCondition for year 2019 rather than any single date.

Simple

Identification info

Date (Creation)
2023-07-17
Date (Publication)
2023-08-01
Date (Revision)
2025-12-11
Edition
1.0

Publisher

Terrestrial Ecosystem Research Network
Building 1019, 80 Meiers Rd
Indooroopilly
QLD
4068
Australia
+61 7 3365 9097

Owner

Department of the Environment, Tourism, Science and Innovation, Queensland Government
41 Boggo Road, Dutton Park, 4102, Queensland, Australia
Dutton Park
Queensland
4102
Australia

Author

Queensland Herbarium - Pennay, Chris ()
Brisbane Botanic Gardens, Mt Coot-tha Road, Toowong, Queensland, 4066, Australia
Toowong
Queensland
4066
Australia

Co-author

Department of Environment and Science (2017-2023), Queensland Government - Morales, Lucia ()
41 Boggo Road, Dutton Park, 4102, Queensland, Australia
Dutton Park
Queensland
4102
Australia

Co-author

Joint Remote Sensing Research Program - Hardtke, Leonardo ()
Chancellors Place, St Lucia, Queensland, 4072, Australia
St Lucia
Queensland
4072
Australia
Website
https://www.tern.org.au/

Purpose
Spatial BioCondition (SBC) is a mapping framework that aligns with Queensland’s Regional Ecosystem (RE) and BioCondition frameworks. It integrates site-based vegetation condition assessment methods and remote sensing (RS) to provide predictions of the condition of vegetation for biodiversity across most terrestrial ecosystems in Queensland. There is an increasing requirement for new vegetation information to support current and emergent drivers in natural resource management. The SBC framework has been developed to support reforms to the Queensland Vegetation Management Act 1999 that aim to provide more holistic reporting on vegetation extent and condition in Queensland. This initial demonstration version provides predictions of the condition of vegetation for biodiversity in 2019 for the brigalow belt bioregion.
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.
Status
Superseded

Point of contact

Department of Environment and Science (2017-2023), Queensland Government - Pennay, Chris ()
41 Boggo Road, Dutton Park, 4102, Queensland, Australia
41 Boggo Road
Dutton Park
Queensland
4102
Australia

Point of contact

Queensland Herbarium - Neldner, Victor ()
Brisbane Botanic Gardens, Mt Coot-tha Road, Toowong, Queensland, 4066, Australia
Brisbane Botanic Gardens, Mt Coot-tha Road
Toowong
Queensland
4066
Australia

Point of contact

Department of the Environment, Tourism, Science and Innovation, Queensland Government - Data Enquiries, Earth Observation and Social Sciences (EOSS) ()
41 Boggo Road, Dutton Park, 4102, Queensland, Australia
41 Boggo Road
Dutton Park
Queensland
4102
Australia

Spatial resolution

Spatial resolution
30
Topic category
  • Environment

Extent

Description
Brigalow Belt bioregion.
N
S
E
W


Temporal extent

Time period
2019-01-01
Maintenance and update frequency
Not planned
GCMD Science Keywords
  • VEGETATION
ANZSRC Fields of Research
  • Image processing
  • Stochastic analysis and modelling
  • Ecology
TERN Platform Vocabulary
  • LANDSAT-7
  • LANDSAT-8
  • LANDSAT-9
  • Sentinel-2A
  • Sentinel-2B
TERN Instrument Vocabulary
  • MSI
TERN Parameter Vocabulary
  • vegetation condition
  • Unitless
QUDT Units of Measure
  • Unitless
GCMD Horizontal Resolution Ranges
  • 1 meter - < 30 meters
GCMD Temporal Resolution Ranges
  • one off
Keywords (Discipline)
  • gradient boosting decision tree

Resource constraints

Use limitation
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/
File name
88x31.png
File description
CCBy Logo from creativecommons.org
File type
png
Linkage
https://w3id.org/tern/static/cc-by/88x31.png

Title
Creative Commons Attribution 4.0 International Licence
Alternate title
CC-BY
Edition
4.0
Website
https://creativecommons.org/licenses/by/4.0/

Access constraints
License
Use constraints
Other restrictions
Other constraints
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
Other constraints
Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}.

Resource constraints

Classification
Unclassified

Distribution Information

Distribution format

Distributor

Distributor

Terrestrial Ecosystem Research Network
Building 1019, 80 Meiers Rd, Indooroopilly, QLD, Australia, 4068
Indooroopilly
QLD
4068
Australia
OnLine resource
ro-crate-metadata.json

Data quality info

Hierarchy level
Dataset
Other
The model Mean Absolute Error (MAE) for predicted BioCondition scores is 15.0. This MAE is based on 231 independent field observations collected during 2022. The estimated rate of error for predicted BioCondition scores is lowest at high and low scores (<40 and >60) and has higher estimated error for mid-range scores.
Title
Positional Accuracy Report
Website
https://sentinels.copernicus.eu/documents/247904/685211/Sentinel-2-L2A-Data-Quality-Report

Abstract
Positional Accuracy Report

Report

Result

Statement
The data set was generated from Sentinel-2 imagery. In July 2018 ESA reported a geometric accuracy of 12&nbsp;m (95% confidence).

Resource lineage

Statement
<br>The Spatial BioCondition 2019 version 1.0 dataset (SBC) was produced by the Queensland Herbarium and Biodiversity Science and the Remote Sensing Sciences business units in the Queensland Department of Environment and Science.</br> <br>The pixel values in SBC dataset represent the predicted condition of vegetation for biodiversity in 2019. The range is 0-100, where lower values indicate poorer condition. No data is represented by a value of 255. No data include:<ul style="list-style-type: disc;"> <li>Regional Ecosystems (RE) with insufficient training and reference data to apply the framework</li> <li>Marine, intertidal, native grassland and predominantly unvegetated ecosystems defined in RE preclearing</li> <li>Urban, suburban, commercial, and industrial areas as defined by the Queensland Land Use Mapping dataset (https://qldspatial.information.qld.gov.au/catalogue/custom/detail.page?fid=%7B273F1E50-DD95-4772-BD6C-5C1963CAA594%7D).</li></ul> Condition of vegetation for biodiversity may be influenced by agricultural practices, grazing land management, inappropriate fire regimes, urban development, incursion of non-native species, industrial logging, and mining. Queensland has a site-based vegetation condition assessment framework ‘BioCondition’ which assesses the relative capacity of an ecosystem to support the suite of species expected to occur in its relatively undisturbed (reference) state. This is measured using a set of compositional, structural, and functional vegetation attributes which are compared against a reference. The greater the difference from the reference state the worse the condition. The reference state characteristics (the benchmark) are derived from a set of sites in the same vegetation community that are known to be in the best available condition. SBC moves the assessment of vegetation condition for biodiversity from a site-based approach to a predictive modelling approach that can be applied at the regional or state scale. It is based on the premise that the greater the difference (measured as distance in multi-dimensional RS space) from the RS reference, the worse the condition. The model is developed using the remote sensing datasets as predictor variables and training sites with known RE and condition state as the response variable. The resulting model is applied to all vegetated areas to produce predictions of condition.</br> <br>The dataset comprises three bands. Band 2 is the predicted BioCondition score 0-100, with higher values representing better vegetation condition for biodiversity. B1 and B3 show the upper and lower boundary of the 90% prediction interval, that is the likely range in which the true value of the prediction will be.</br>
Hierarchy level
Dataset
Title
Spatial BioCondition website
Website
https://www.qld.gov.au/environment/plants-animals/biodiversity/biocondition

Method documentation

Title
Spatial BioCondition
Website
https://www.qld.gov.au/__data/assets/pdf_file/0015/230019/spatial-biocondition-vegetation-condition-map-for-queensland.pdf

Method documentation

Process step

Description
This version was created using the Spatial BioCondition modelling workflow.

Process step

Description
The model uses the following datasets: Sentinel 2 based green and bare fractional cover statistics (2017-2019); Landsat derived fractional cover for the 2019 dry season; Sentinel 2 NDVI derived phenological metrics; Regional ecosystem pre-clearing dataset - version12.2; Selected vegetation field survey data held in departmental databases.

Process step

Description
The final model output was clipped to the IBRA7 Brigalow Belt bioregion boundary, and the following areas were masked: The pre-clearing extent of: natural grasslands; predominantly unvegetated ecosystems; regional ecosystems extra to the Brigalow Belt and Southeast Queensland bioregions defined by version 12.2 regional ecosystem mapping; Built environments and infrastructure (urban, suburban, commercial and industrial areas) defined by Queensland land use mapping.

Process step

Description
Masked areas, pixels without predictions, and pixels outside the bioregion are classified as No Data (DN = 255). Band 1 is the 5<sup>th</sup> of the prediction interval, Band 2 is the predicted BioCondition score and Band 3 is the 95<sup>th</sup> percentile of the prediction interval.

Reference System Information

Reference system identifier
EPSG/EPSG:3577

Reference system type
Geodetic Geographic 2D

Metadata

Metadata identifier
urn:uuid/40990eec-5cef-41fe-976b-18286419da0c

Title
TERN GeoNetwork UUID

Language
English
Character encoding
UTF8

Point of contact

Terrestrial Ecosystem Research Network
Building 1019, 80 Meiers Rd
Indooroopilly
QLD
4068
Australia
+61 7 3365 9097
Title
Queensland Spatial BioCondtion Data Collection

Identifier

Code
e79c49ae-ee0c-4352-b65b-76d6e76784c4
Codespace
https://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/
Description
Parent Metadata Record

Type of resource

Resource scope
Dataset
Metadata linkage
https://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/40990eec-5cef-41fe-976b-18286419da0c

Point-of-truth metadata URL

Date info (Creation)
2023-06-19T00:00:00.000000+00:00
Date info (Revision)
2025-12-11T22:58:13.268741+00:00

Metadata standard

Title
ISO 19115-1:2014/AMD 1:2018 Geographic information - Metadata - Fundamentals
Edition
1

Metadata standard

Title
ISO/TS 19115-3:2016
Edition
1.0

Metadata standard

Title
ISO/TS 19157-2:2016
Edition
1.0
Title
Terrestrial Ecosystem Research Network (TERN) Metadata Profile of ISO 19115-3:2016 and ISO 19157-2:2016
Date (published)
2021
Edition
1.0

Identifier

Code
10.5281/zenodo.5652221
Website
https://github.com/ternaustralia/TERN-ISO19115/releases/tag/v1.0

 
 

Overviews

Spatial extent

N
S
E
W


Keywords

ANZSRC Fields of Research
Ecology Image processing Stochastic analysis and modelling
GCMD Science Keywords
VEGETATION

Provided by

Share on social sites

Access to the portal
Read here the full details and access to the data.

Associated resources

Not available


  •   About
  •   Github
  •