Queensland Southeast Queensland Bioregion Spatial BioCondition, 2019, Version 1.0
Version 1 of the Southeast Queensland Bioregion Spatial BioCondition dataset is superseded by the Version 2 dataset that can be found at: https://doi.org/10.25901/r976-1v8 5.<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 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.
Simple
Identification info
- Date (Creation)
- 2023-06-20
- Date (Publication)
- 2024-10-22
- Date (Revision)
- 2024-10-22
- Edition
- 1.0
Publisher
Owner
Department of Environment and Science (2017-2023), Queensland Government
41 Boggo Road, Dutton Park, Queensland, 4102, 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, Queensland, 4102, 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 version provides predictions of the condition of vegetation for biodiversity in 2019 for the southeast Queensland 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
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 Environment and Science (2017-2023), Queensland Government - Tindall, Dan ()
41 Boggo Road, Dutton Park, Queensland, 4102, Australia
41 Boggo Road
Dutton Park
Queensland
4102
Australia
Point of contact
Queensland Herbarium - Pennay, Chris ()
Brisbane Botanic Gardens, Mt Coot-tha Road, Toowong, Queensland, 4066, Australia
Brisbane Botanic Gardens, Mt Coot-tha Road
Toowong
Queensland
4066
Australia
Spatial resolution
- Spatial resolution
- 30
- Topic category
-
- Environment
Extent
- Description
- Southeast Queensland bioregion.
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S
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W
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Temporal extent
- Time period
- 2019-01-01
- Maintenance and update frequency
- Not planned
- GCMD Science Keywords
- ANZSRC Fields of Research
- TERN Platform Vocabulary
- TERN Instrument Vocabulary
- TERN Parameter Vocabulary
- QUDT Units of Measure
- GCMD Horizontal Resolution Ranges
- GCMD Temporal Resolution Ranges
- 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
- Title
- Creative Commons Attribution 4.0 International Licence
- Alternate title
- CC-BY
- Edition
- 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
Distributor
Distributor
Terrestrial Ecosystem Research Network
Building 1019, 80 Meiers Rd, Indooroopilly, QLD, Australia, 4068
Indooroopilly
QLD
4068
Australia
- Distribution format
-
- 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 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.
- Title
- Positional Accuracy 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 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 Program 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
-
https://www.qld.gov.au/__data/assets/pdf_file/0015/230019/spatial-biocondition-vegetation-condition-map-for-queensland.pdf
Method documentation
- Title
- Spatial BioCondition website
- Website
-
https://www.qld.gov.au/environment/plants-animals/biodiversity/spatial-biocondition
Method documentation
Process step
- Description
- This dataset was created using the Spatial BioCondition modelling workflow. 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 Southeast Queensland 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> percentile 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/2c33325c-1dd5-4674-918a-1cd5bfc1a6e3
- Title
- TERN GeoNetwork UUID
- Language
- English
- Character encoding
- UTF8
Point of contact
- Title
- Queensland Spatial BioCondtion Data Collection
Identifier
- 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/2c33325c-1dd5-4674-918a-1cd5bfc1a6e3
Point-of-truth metadata URL
- Date info (Creation)
- 2023-06-19T00:00:00
- Date info (Revision)
- 2024-10-22T00:00:00
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
Overviews
Spatial extent
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Provided by
Associated resources
Not available