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qld_woody_extent_2019
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2121658.293500
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ISO19139
qld_woody_extent_2019
Feature Class
5376710
Woody vegetation
Department of Environment and Science
OBJECTID
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woody_extent_2019
woody_extent_2019
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Woody vegetation
Department of Environment and Science
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1
woody
Department of Environment and Science
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dataset
Andrew Morgan
Department of Environment and Science
Senior Scientist
0731705688
AU
andrew.morgan@des.qld.gov.au
Rosalie Buck
Department of Environment and Science
Senior Scientist
0731705688
AU
Rosalie.buck@des.qld.gov.au
20230606
ArcGIS Metadata
1.0
Enterprise Geodatabase Feature Class
2.8.3
DNRM, Open Data
Department of Resources
Senior Product Officer
2022-07-01T00:00:00
Open the Queensland Spatial Catalogue (QSpatial). Select the large SEARCH button and all available records are displayed. Select one of the four filter options provided and then the further options within the filter. The resultant search is then displayed. Select your record and complete the order.
Queensland Spatial Catalogue
2.0
FGDB
Whole of dataset
300
http://qldspatial.information.qld.gov.au/catalogue/custom/search.page?q=%22Statewide Landcover And Trees Study (SLATS) Sentinel-2 - 2020 woody vegetation extent - Queensland - whole of state%22
Statewide Landcover And Trees Study (SLATS) Sentinel-2 - 2019 woody vegetation extent - Queensland
Statewide Landcover And Trees Study (SLATS) Sentinel-2 - 2019 woody vegetation extent - Queensland
2022-06-28T02:39:20
2022-07-22
Dan Tindall - Science Leader
Department of Environment and Science
Science Leader
0731705688
AU
dan.tindall@des.qld.gov.au
The SLATS 2019 Woody extent dataset shows the presence/absence of woody vegetation throughout Queensland. The scale of the woody extent dataset is intended to capture features visible at a nominal map scale of 1:10,000: stands of woody vegetation greater than 0.5 ha with a canopy density greater than 10% crown cover will be classified as woody. A minimum width of 20 metres applies to linear features.
A 2019 Woody Vegetation Extent for ongoing vegetation monitoring and reporting.
© State of Queensland (Department of Environment and Science) 2022
Andrew Morgan
Department of Environment and Science
Senior Remote Sensing Officer
0731705688
AU
andrew.morgan@des.qld.gov.au
Andrew Morgan
Department of Environment and Science
Senior Scientist
0731705688
AU
andrew.morgan@des.qld.gov.au
Andrew Morgan
Department of Environment and Science
Senior Scientist
0731705688
AU
andrew.morgan@des.qld.gov.au
Queensland
VEGETATION COVER
LAND USE/LAND COVER
VEGETATION
Vegetation clearing
land cover change
Queensland
VEGETATION COVER
LAND USE/LAND COVER
VEGETATION
Vegetation clearing
land cover change
To be used to the scale of Sentinel-2 satellite imagery.
© State of Queensland (Department of Environment and Science) 2022
Creative Commons Attribution 4.0 International
OFFICIAL-PUBLIC
ISO 19115 (mapped from Qld Govt Information Security Standard IS18)
RSC.QLD_WOODY_EXTENT_2020
2022-07-01
2022-07-01
10
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137.244841
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The classes are categorised in the "Woody_extent_2019" field as 1 - Woody, 2 - Non-Woody. Features were categorised as either woody or non-woody based on a set of decision rules informed by visual inspection of the data, the needs of existing datasets/programs, and expert knowledge. These decisions were based on considerations for the SLATS and Spatial BioCondition programs, and other vegetation monitoring applications, as well as ecological characteristics of the vegetation. No distinction was made between native and non-native vegetation; woody vegetation such as woody weeds and horticultural crops are included as woody in the final classification.
The dataset has been clipped to the Qld Coastline and state border boundary layer. The data is subdivided into a 25x25km grid to aid in drawing and editing performance.
Public
Metadata Access Level
The data is to a standard determined as fit for the purpose for which it was collected.
The data set has a Minimum Mapping Unit of 0.5HA. The minimum width of linear woody features, e.g. narrow corridors of woody vegetation and nonwoody features, e.g. roads or power-line easements, is 20m. Both woody and nonwoody features smaller than these sizes have been filtered out of the data set.
The absolute accuracy has not been validated.
2022-07-01T00:00:00
Woody vegetation
2022-07-01
2022-07-01
The data is to a standard determined as fit for the purpose for which it was collected.
true
The data is to a standard determined as fit for the purpose for which it was collected.
The absolute accuracy has not been validated. Ongoing quality assessment and refinement was a core part of the data set development, to ensure consistency of mapping across the statewide product.
Woody vegetation
2022-07-01
2022-07-01
The data is to a standard determined as fit for the purpose for which it was collected.
true
The data is to a standard determined as fit for the purpose for which it was collected.
The data set was generated from Pan-sharpened 80cm DMC3 Triplesat imagery acquired from Earth-I UK with a specified positional accuracy of 10m (90% confidence).
2022-07-01T00:00:00
Woody vegetation
2022-07-01
2022-07-01
The data is to a standard determined as fit for the purpose for which it was collected.
true
The Earth-I mosaics were resampled from 80cm to 1m using Cubic Convolution.
A U-net convolutional neural network classification was fitted on the Earth-I data to produce an initial binary woody presence/absence classification, as described in Flood et al (2019).
The classification was down-sampled to 10m and subsequently manually revised and edited by a team of remote sensing scientists, and quality checked by senior scientists.
The dataset was updated using SLATS clearing data for the 2018-2019 reporting to produce a 2019 woody extent.
The data was clipped to the Queensland coastline and land borders using the Australian_NAT_Framework geopolitical data set.
References.
Flood, N., Watson, F., Collett, L., 2019, Using a U-net convolutional neural network to map woody vegetation extent from high resolution satellite imagery across Queensland, Australia, International Journal of Applied Earth Observation and Geoinformation, Volume 82, ISSN 0303-2434, https://doi.org/10.1016/j.jag.2019.101897.
A set of pan-sharpened, pre-processed image mosaics acquired between April and November 2017 over Queensland at a resolution of 80cm was purchased from Earth-I UK.
5376710
EPSG
6.12(9.3.0.0)