Brief description
Version 1 of the Southeast Queensland Bioregion Spatial BioCondition dataset is superseded by the Version 2 dataset that can be found at: https://doi.org/10.25901/r976-1v85.Version 1 was an initial demonstration version.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.
Lineage
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.
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:
- Regional Ecosystems (RE) with insufficient training and reference data to apply the framework
- Marine, intertidal, native grassland and predominantly unvegetated ecosystems defined in RE preclearing
- 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).
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.
Data Creation
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.
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.
Masked areas, pixels without predictions, and pixels outside the bioregion are classified as No Data (DN = 255). Band 1 is the 5th percentile of the prediction interval, Band 2 is the predicted BioCondition score and Band 3 is the 95th percentile of the prediction interval.
Notes
CreditWe 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.
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.
Data Quality Assessment Scope
local :
dataset
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
uri :
https://sentinel.esa.int/documents/247904/685211/Sentinel-2_L1C_Data_Quality_Report
Data Quality Assessment Result
local :
Quality Result
The data set was generated from Sentinel-2 imagery. In July 2018 ESA reported a geometric accuracy of 12 m (95% confidence).
Created: 2023-06-20
Issued: 2024-10-22
Modified: 2024-10-22
Data time period: 2019-01-01
text: Southeast Queensland bioregion.
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Point-of-truth metadata URL
Spatial BioCondition
Spatial BioCondition website
uri :
https://www.qld.gov.au/environment/plants-animals/biodiversity/spatial-biocondition
- URI : geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/2c33325c-1dd5-4674-918a-1cd5bfc1a6e3
- global : 2c33325c-1dd5-4674-918a-1cd5bfc1a6e3
