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Vegetation Formations and Classes of NSW (version 3.03 - 200m Raster) - David A. Keith and Christopher C. Simpson. VIS_ID 3848

Created 05/05/2025

Updated 05/05/2025

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This vegetation map shows the extant distributions of vegetation formations and classes throughout NSW, and provides users with information about the resolution, currency and uncertainties in the underlying data that were used to assemble the map. Data represents NSW native vegetation extent, compiled from various vegetation maps using methods outlined in Simpson et al. (2011) and in Keith and Simpson (2010). The NSW vegetation map (version 2.2, Keith and Simpson 2006) was revised by interpreting additional candidate maps as vector layers and synthesising these into a single raster-based data set. This involved eight steps: developing a comprehensive ‘standard’ classification of vegetation classes for NSW; collating and standardising the projection and format of candidate source maps; assigning vegetation units of source maps to NSW vegetation classes; assessing the spatial resolution, currency and reliability of candidate source maps; assembling a composite map from candidate source maps to maximise reliability; applying a spatial mask to represent extant native vegetation; adjusting spatial resolution by dissolving small polygons and converting to 200 m raster; attributing the spatial resolution, currency and reliability of the underlying source data sets. The classification of 106 vegetation classes described by Keith (2004) was adopted as the framework for preparation of version 3.03 of the NSW vegetation map. Polygons from the “Estuarine macrophytes CCA” dataset of less than 0.1 ha were eliminated. For all other datasets polygons of less than 2 ha were eliminated. The map incorporates data from a statewide woody vegetation mask from the NSW Woody Vegetation Change Detection Program (Kitchen et al. 2010). The map is presented as a raster within an ESRI ArcGIS (9.3) geodatabase. Supersedes Keith and Simpson (2006), Keith (2004) and Pressey et al. (2000). Pressey et al. (2000) was the native veg extent product used to calculate native veg cover values for the Over-Cleared Landscapes Database prior to July 2006. References: Keith D. A. (2004) Ocean Shores to Desert Dunes: The native vegetation of New South Wales and the ACT. Department of Environment and Conservation, Sydney. Keith, D. A. and Simpson, C. C. (2010) Vegetation Formations of NSW (version 3.0): A seamless map for modelling fire spread and behaviour. Report to the Rural Fire Service. NSW Department of Environment and Climate Change. October 2010. Keith, D. A. and Simpson, C. C. (2006). A protocol for assessment and integration of vegetation maps, with an application to spatial data sets from south-eastern Australia. Austral Ecology 33, 761–774. Pressey, R.L., Hager, T.C., Ryan, K.M., Schwarz, J., Wall, S., Ferrier, S. and Creaser, P.M. (2000). Using abiotic data for conservation assessments over extensive regions: quantitative methods applied across New South Wales, Australia. Biological Conservation 96, 55-82

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Title Vegetation Formations and Classes of NSW (version 3.03 - 200m Raster) - David A. Keith and Christopher C. Simpson. VIS_ID 3848
Language English
Licence Creative Commons Attribution 3.0 Australia
Landing Page https://devweb.dga.links.com.au/data/dataset/4b6f1b3f-f33a-4e56-a6dd-5b052f28a361
Remote Last Updated 28/08/2024
Contact Point
NSW Department of Climate Change, Energy, the Environment and Water
test@email.loc
Reference Period 01/01/1940 - 06/01/2012
Geospatial Coverage {"type": "Polygon", "coordinates": [[[154.0, -38.0], [154.0, -28.0], [141.0, -28.0], [141.0, -38.0], [154.0, -38.0]]]}
Data Portal data.gov.au

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This dataset was originally found on DataNSW "Vegetation Formations and Classes of NSW (version 3.03 - 200m Raster) - David A. Keith and Christopher C. Simpson. VIS_ID 3848". Please visit the source to access the original metadata of the dataset:
https://data.nsw.gov.au/data/dataset/vegetation-classes-of-nsw-version-3-03-200m-raster-david-a-keith-and-christopher-c-simpc0917

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No duplicate datasets found.