This key layer is the index to the input datasets collated into the estimated Pre-1750 (pre-clearing, pre-European) theme of the NVIS Version 5.1 dataset (from which the NVIS Major Vegetation Groups and Subgroups were derived).
The layer is intended to document and describe the input datasets and assist in dynamic analyses of data quality and gaps in the NVIS Pre-1750 theme dataset. Important information in the spatial feature class includes the dataset spatial extent (i.e. its "footprint"), dataset number and the source of the underlying dataset. Where more than one dataset have been combined within a region (mainly NSW & NT), a complex of footprints is the result.
A lookup table provides important information, such as dataset title, scale and the on-ground range of dates of the vegetation survey. Attributes in the lookup table NVIS5_1_LUT_KEY_DSETn (from the NVIS DATASET and VERSION_USAGE Oracle tables, where n = an incremental number for minor version updates) need to be attached to this spatial data via DATA_SET_NUMBER. See metadata for this LUT for more details.This data has been licensed under the Creative Commons Attribution 4.0 International Licence. More information can be found at https://creativecommons.org/licenses/by/4.0/
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Suitable for understanding and mapping various NVIS data source and quality attributes.
Applications involving futher use of the data may need to resolve the minor, but numerous, sliver and overlap issues.
In an attempt to mitigate this issue, artificial vector layers were created for SA and ACT by cutting present native vegetation into the Carnahan estimated pre-1750 data for these areas. This assumes no change in vegetation type - just whether the type remains (i.e. hasn't been cleared).
No vector estimated pre-1750 layers are available for NSW and Tasmania. However, estimated pre-1750 layers have been developed under the Major Vegetation Group and Major Vegetation Subgroup products, using the same logic as above.
© Commonwealth of Australia (Department of the Environment and Energy) 2018