logo
Data

Central Queensland Coast Bioregion Spatial BioCondition, 2021, Version 2.0 

Ver: 2.0
Status of Data: completed
Update Frequency: notPlanned
Security Classification: unclassified
Dataset Published: 2024-09-16
Dataset Last Modified: 2026-08-18
Metadata viewed 57 times
Dataset accessed 11 times
Metadata Created: 2024-08-30
Metadata Last Modified: 2026-08-19
How to cite this collection:
Verrall, B. & Hardtke, L. (2024). Central Queensland Coast Bioregion Spatial BioCondition, 2021, Version 2.0. Version 2.0. Terrestrial Ecosystem Research Network. Dataset. https://dx.doi.org/10.25901/eyer-1a70 
Data can be accessed from the following links:
HTTPCloud Optimised GeoTIFF - Spatial BioCondition 2021, CQC. v2
HTTPFactsheet - Spatial BioCondition 2021, v2
WMSSBC_CQC
HTTPLandscape Data Visualiser - Spatial BioCondition 2021, CQC. v2
HTTPPoint-of-truth metadata URL
HTTPro-crate-metadata.json
This is a spatial dataset comprising predictions of vegetation condition for biodiversity for the Central Queensland Coast bioregion. The dataset was created using a gradient boosting decision tree (GBDT) model based on 10 vegetation-specific remote sensing datasets and 7,938 training sites of known vegetation community and condition state across Southeast Queensland, Brigalow Belt and Central Queensland Coast bioregions. Condition score was modelled as a function of distance in the remote sensing (RS) space within homogeneous vegetation communities. The product is intended to represent predicted BioCondition for 2021 rather than any singe date. 
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
Spatial BioCondition (SBC) is a mapping framework that aligns with Queensland’s Regional Ecosystem (RE) and BioCondition frameworks, as 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 of a bioregion. 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. Following version 1.0, this version predicts the condition of vegetation for biodiversity in 2021 for the Central Queensland Coast bioregion. 
Lineage
Data not provided. 
Method DocumentationData not provided.
Procedure StepsData not provided.
Spatial Description
Central Queensland Coast bioregion 
Temporal Coverage
From 2021-01-01 to 2021-12-31 
Spatial Resolution

Data not provided.

Vertical Extent

Data not provided.

Data Quality Assessment Scope
Predicted Spatial BioCondition scores are validated against 270 independent field observations of BioCondition that are scored against Regional Ecosystem specific benchmarks. Stratified randomised sampling was used to ensure geographic spread of field sites as well as evenly distributed validation of predicted Spatial BioCondition condition scores. 
Data Quality Report
Data not provided. 
Data Quality Assessment Outcome
Based on 270 independent field observations collected between 2022 and 2024, predicted Spatial BioCondition scores had a Mean Absolute Error (MAE) of 13.4 and an R squared of 0.70. 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. 
ANZSRC - FOR
Ecology
Data Stream
Satellite Remote Sensing
GCMD Sciences
VEGETATION
VEGETATION - IMPORTANCE VALUE
Horizontal Resolution
30 meters - < 100 meters
Parameters
vegetation condition
Project
TERN Landscapes
Temporal Resolution
one off
Topic
environment
imageryBaseMapsEarthCover
Author
Verrall, Brodie
Co-Author
Hardtke, Leonardo
Owner
Department of Environment, Science and Innovation (2023-2024), Queensland Government
Contact Point
Tindall, Dan
Neldner, Victor
Eyre, Teresa
Verrall, Brodie
Terrestrial Ecosystem Research Network
Publisher
Terrestrial Ecosystem Research Network
By Parent record
Queensland Spatial BioCondition Data Collection
Terrestrial Ecosystem Research Network
80 Meiers Road, Indooroopilly, Queensland, 4068, Australia.
Contact Us
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/ 
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}.