logo
Data

Data Discovery

Queensland Southeast Queensland Bioregion Spatial BioCondition, 2019, Version 1.0 

Ver: 1.0
Status of Data: superseded
Update Frequency: notPlanned
Security Classification: unclassified
Dataset Published: 2023-08-01
Dataset Last Modified: 2026-08-18
Metadata viewed 429 times
Dataset accessed 71 times
Metadata Created: 2023-06-19
Metadata Last Modified: 2026-08-19
How to cite this collection:
Pennay, C., Morales, L. & Hardtke, L. (2023). Queensland Southeast Queensland Bioregion Spatial BioCondition, 2019, Version 1.0. Version 1.0. Terrestrial Ecosystem Research Network. Dataset. https://portal.tern.org.au/metadata/2c33325c-1dd5-4674-918a-1cd5bfc1a6e3 
HTTPPoint-of-truth metadata URL
HTTPro-crate-metadata.json
Version 1 of the Southeast Queensland Bioregion Spatial BioCondition dataset is superseded by the Version 2 dataset that can be found at: https://doi.org/10.25901/r976-1v85.

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 Southeast Queensland 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. 
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, 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 version provides predictions of the condition of vegetation for biodiversity in 2019 for the southeast Queensland bioregion. 
Lineage
Data not provided. 
Method DocumentationData not provided.
Procedure StepsData not provided.
Spatial Description
Southeast Queensland bioregion. 
Temporal Coverage
From 2019-01-01 to on going 
Spatial Resolution

Distance of 30 Metres

Vertical Extent

Data not provided.

Data Quality Assessment Scope
The model Mean Absolute Error (MAE) for predicted BioCondition scores is 15.0. This RMSE 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. 
Positional Accuracy Report
Data Quality Assessment Outcome
The data set was generated from Sentinel-2 imagery. In July 2018 ESA reported a geometric accuracy of 12 m (95% confidence). 
ANZSRC - FOR
Ecology
Image processing
Spatial statistics
Data Stream
Satellite Remote Sensing
GCMD Sciences
VEGETATION
Horizontal Resolution
1 meter - < 30 meters
Instruments
MSI
Parameters
vegetation condition
Platforms
LANDSAT-7
LANDSAT-8
LANDSAT-9
Sentinel-2A
Sentinel-2B
Project
TERN Landscapes
Temporal Resolution
one off
Topic
environment
User Defined
gradient boosting decision tree
Author
Pennay, Chris
Co-Author
Morales, Lucia
Hardtke, Leonardo
Owner
Department of the Environment, Tourism, Science and Innovation, Queensland Government
Contact Point
Neldner, Victor
Pennay, Chris
Data Enquiries, Earth Observation and Social Sciences (EOSS)
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}.