This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.
This raster dataset 'NVIS4_1_AUST_MVS_PRE_ALB' provides summary information on Australia's estimated pre-1750 native vegetation classified into Major Vegetation Subgroups. It is in Albers Equal Area projection with a 100 m x 100 m (1 Ha) cell size.
A comparable Extant (present) vegetation raster dataset is available:
State and Territory vegetation mapping agencies supplied a new version of the National Vegetation Information System (NVIS) in 2009-2011. Some agencies did not supply new data for this version but approved re-use of Version 3.1 data. Summaries were derived from the best available data in the NVIS extant theme as at June 2012.
This product is derived from a compilation of data collected at different scales on different dates by different organisations. Please refer to the separate key map showing scales of the input datasets. Gaps in the NVIS database were filled by non-NVIS data, notably parts of South Australia and small areas of New South Wales such as the Curlewis area.
Eighty-five (85) Major Vegetation Subgroups identified were created in v4.1 to summarise the type and distribution of Australia's native vegetation. The classification contains an emphasis on the structural and floristic composition of the dominant stratum (as with Major Vegetation Groups), but with additional types identified according to typical shrub or ground layers occurring with a dominant tree or shrub stratum.
In a mapping sense, the subgroups reflect the dominant vegetation occurring in a map unit from a mix of several vegetation types. Less-dominant vegetation subgroups which are also present in the map unit are not shown. For example, the dominant vegetation in an area may be mapped as dominated by eucalypt open forest with a shrubby understorey, although it contains pockets of rainforest, shrubland and grassland vegetation as subdominants.
A number of other non-vegetation and non-native vegetation land cover types are also represented as Major Vegetation Subgroups. These are provided for cartographic purposes, but should not be used for analyses.
This dataset has been provided to the BA Programme for use within the programme only. The current NVIS data products are available from http://www.environment.gov.au/land/native-vegetation/national-vegetation-information-system.
The input vegetation data were provided from over 100 individual projects representing the majority of Australia's regional vegetation mapping over the last 50 years. State and Territory custodians translated the vegetation descriptions from these datasets into a common attribute framework, the National Vegetation Information System (ESCAVI, 2003). Scales of input mapping ranged from 1:25,000 to 1:5,000,000. These were combined into an Australia-wide set of vector data. Non-terrestrial areas were mostly removed by the State and Territory custodians before supplying the data to the Environmental Resources Information Network (ERIN), Department of Sustainability Environment Water Population and Communities (DSEWPaC).
Each NVIS vegetation description was written to the NVIS XML format file by the custodian, transferred to ERIN and loaded into the NVIS database at ERIN. A considerable number of quality checks were performed automatically by this system to ensure conformity to the NVIS attribute standards (ESCAVI, 2003) and consistency between levels of the NVIS Information Hierarchy within each description. Descriptions for non-vegetation and non-native vegetation mapping codes were transferred via CSV files.
The NVIS vector (polygon) data for Australia comprised a series of jig-saw pieces, each up to approx 500,000 polygons - the maximum tractable size for routine geoprocesssing. The spatial data was processed to conform to the NVIS spatial format (ESCAVI, 2003; other papers). Spatial processing and attribute additions were done mostly in ESRI File Geodatabases. Topology and minor geometric corrections were also performed at this stage. These datasets were then loaded into ESRI Spatial Database Engine as per the ERIN standard. NVIS attributes were then populated using database tables provided by custodians, mostly using PL/SQL Developer or in ArcGIS using the field calculator (where simple).
Each spatial dataset was joined to and checked against a lookup table for the relevant State/Territory to ensure that all mapping codes in the dominant vegetation type of each polygon (NVISDSC1) had a valid lookup description, including an allocated MVS. Minor vegetation components of each map unit (NVISDSC2-6) were not checked, but could be considered mostly complete.
Each NVIS vegetation description was allocated to a Major Vegetation Subgroup (MVS) by manual interpretation at ERIN and in consultation with data custodians. 12 new MVSs were created for version 4.1 to better represent open woodland formations, more understorey types and forests (in the NT) with no further data available. Also, a number of MVSs were redefined after creation of the new groups to give a clearer and precise description of of the Subgroup e.g. MVS 9 - 'Eucalyptus woodlands with a grassy understorey' became 'Eucalyptus woodlands with a tussock grass understorey' to distinguish it from MVS10 - 'Eucalyptus woodlands with a hummock grass understorey'.. NVIS vegetation descriptions were reallocated into these classes, if appropriate:
Warm Temperate Rainforest
Eucalyptus woodlands with a hummock grass understorey
Acacia (+/- low) open woodlands and sparse shrublands with a shrubby understorey
Mulga (Acacia aneura) open woodlands and sparse shrublands +/- tussock grass
Eucalyptus woodlands with a chenopod or samphire understorey
Open mallee woodlands and sparse mallee shrublands with a hummock grass understorey
Open mallee woodlands and sparse mallee shrublands with a tussock grass understorey
Open mallee woodlands and sparse mallee shrublands with an open shrubby understorey
Open mallee woodlands and sparse mallee shrublands with a dense shrubby understorey
Callitris open woodlands
Casuarina and Allocasuarina open woodlands with a tussock grass understorey
Casuarina and Allocasuarina open woodlands with a hummock grass understorey
Casuarina and Allocasuarina open woodlands with a chenopod shrub understorey
Casuarina and Allocasuarina open woodlands with a shrubby understorey
Melaleuca open woodlands
Other Open Woodlands
Other sparse shrublands and sparse heathlands
Data values defined as cleared or non-native by data custodians were attributed specific MVS values such as 42 - naturally bare, sand, rock, claypan, mudflat; 43 - salt lakes and lagoons; 44 - freshwater lakes and dams; 46 - seas & estuaries, 90, 91, 92 & 93 - Regrowth Subgroups; 98 - Cleared, non native, buildings; and 99 - Unknown. Note: some of these MVSs are only present in Extant vegetation.
As part of the process to fill gaps in NVIS, the descriptive data from non-NVIS sources was also stored in the NVIS database, but with blank vegetation descriptions. In general, the gap-fill data comprised (a) fine scale (1:250K or better) State/Territory vegetation maps for which NVIS descriptions were unavailable and (b) coarse-scale (1:1M and 1:5M) maps from Commonwealth and other sources. MVSs were then allocated to each description from the available descriptions in accompanying publications and other sources.
Each spatial dataset with joined lookup table (including MVS_NUMBER linked via NVISDSC1) was exported to a File Geodatabase as a feature class. These were reprojected into Albers Equal Area projection (Central_Meridian: 132.000000, Standard_Parallel_1: -18.000000, Standard_Parallel_2: -36.000000, Linear Unit: Meter (1.000000), Datum GDA94, other parameters 0).
In the original extant data, parts of New South Wales, South Australia, Tasmania and the ACT have areas of vector "NoData", thus appearing as an inland sea. Where there were gaps in the spatial coverage of Australia, "artificial" estimated pre-1750 layers were created from datasets available to the ERIN Veg Team. These were managed differently based on available information and complexity of work involved. Pre-1750 vector data for other states were supplied for 4.1 or previously, and did not require modelling. The purpose of this artificial pre-1750 modelling was to ensure that the pre-1750 and extant (present) datasets are comparable in the respective MVG and MVS classifications.
Pre1750 Vector Modelling
Large areas in the original South Australia and the ACT extant vector data had 'NoData'. Pre1750 vector layers were created by filling/cutting in these areas with estimated pre-1750 data from other sources such as the Geoscience Australia (AUSLIG,1990) "Natural" vector data layer. This procedure assumes that extant native vegetation has not changed its type since European settlement. Thus, effectively, only the non-native component was modelled/estimated for pre-1750 extent.
All feature classes were then rasterised to a 100m raster with extents to a multiple of 1000 m, to ensure alignment. In some instances e.g. NSW and TAS, areas of 'NoData' had to be modelled in raster (see below).
For large parts of NSW, the native component of NVIS extant data were cut into the Geoscience Australia (AUSLIG,1990) "Natural" raster data layer and in some smaller areas, existing pre1750 data layers (e.g. Tumut), using a complex series of raster operations. For Tasmania, the NVIS version 2.0 (i.e. the original NVIS with restructured attributes) pre-European layer was rasterised, and used to fill non-native areas of the extant NVIS vegetation layer, using raster operations, especially reclassing and merging. These procedures also assume that extant native vegetation has not changed its type since European settlement. Thus, effectively, only the non-native component was modelled/estimated for pre-1750 extent.
Final rasters were then merged into a 'state wide' raster. State rasters were then merged into this 'Australia wide' raster dataset.
Department of the Environment (2014) Estimated Pre-1750 Major Vegetation Subgroups. Bioregional Assessment Source Dataset. Viewed 07 February 2017, http://data.bioregionalassessments.gov.au/dataset/2208babe-8e88-4423-91e6-b9a3fa6f31b6.