Identification

Field	Value
Title	Central West / Lachlan Regional Native Vegetation Map (NSW Formation and Class) Version 1.0. VIS_ID 4214
Alternative title(s)	CentWestLach_v1_0_Keith_E_4214
Abstract	This version (v1.0) is released for interim review for 3 months from release date. A subsequent official release will be published after review and subsequent alterations. Please note, Central West / Lachlan Regional Native Vegetation Map (NSW Formation and Class) Version 1.0. VIS_ID 4214 web service and zipped dataset will be archived and will no longer be available on line after 31st March 2025. The primary thematic data layer in this dataset is a map of regional scale Plant Community Types (PCT's). The map was developed from a process using vegetation surveys, remote sensing derivations, visual interpretation and spatial distribution models. The download package includes a merged and simplified version of the full dataset. The full dataset comprises the following data layers as delivered in an ArcGIS 9.3 File Geo-database: MAP SHEET DATA: (CWLpct_v1p0.gdb\PCTv1) provided as 100k map sheets comprising detailed vegetation line-work with the following attributions per polygon: FIELDS: !CWLpct_v1! - Plant Community Type (PCT) Codes !CommName! - Plant Community Type Common Names !KeithClass! - The mapped PCT's associated Keith Class !KeithForm! - The maplped PCT's assocated Keith Formation !Cover! - Percent woody cover per polygon (0 - 1.0) derived from the NSW Woody Vegetation Extent 2011 dataset. !EnvPCT1! - Most likely modelled PCT !EnvPCT2! - Second most likely modelled PCT !EnvPCT3! - Third most likely modelled PCT !confcat! - Categorical modelling confidence levels of EnvPCT1 (High > 60%, Medium 30%-60%, Low < 30%, None). None = non-modelling attribution (either manual expert API or pre-existing mapping) !cwlscv1up! - Expert Manual API code of structural class. Look up table below. !hectares! - Size of polygon in hectares While much of the aerial photo interpretation employed was undertaken at around 1:8000, PCT attribution is generally at a much coarser scale. We recommend that the highest resolution appropriate for this product be 1:15000. VALIDATION SUMMARY: Pending Technical Report. ACCOMPANYING DATASETS: KEITH CLASS QUICK-VIEW DISSOLVE: CWLpct_v1p0.gdb\KCv1\CWL_KC This is a dissolved (internal attribute polygon boundaries removed) and CWL-wide merged version of the Keith Class as found in the complete linework sheets of 100K Map sheet Data. CWl BOUNDARY: CWLpct_v1p0.gdb\Boundaries\CWL_Boundary: A polygon boundary of the Central-West Lachlan v1 Regional Vegetation Map CWL 100K SHEET BOUNDARIES: CWLpct_v1p0.gdb\Boundaries\CWL_100k Polygon boundaries of the 100k sheet extents within the CWL v1 extent. SURVEY SITES: CWLpct_v1p0.gdb\Surveys\CWL_Sites_PCT_20150528 Point locations of on-ground rapid or full floristic vegetation surveys. Pertinent Fields: !SURVEYID! - code identifying for which project the sites were commissioned. !SITENUMBER! - Unique site code identifier. !PCT_1_0528! - Attributed PCT Code classification !PCT_1_0528! - Alternative PCT Code classification LOOK UP TABLE: PCT Code, Name, Keith class & Keith Formation look-up: CWLpct_v1p0.gdb\CWL_LUT MXD: CWLpct_v1p0.mxd ACCESS QUERIES: For access queries regarding the full dataset, please contact: data.broker@environment.nsw.gov.au VIS_ID 4214
Resource locator
Data Quality Statement	Name: Data Quality Statement Protocol: WWW:DOWNLOAD-1.0-http--download Description: Data quality statement for Central West / Lachlan Regional Native Vegetation Map (NSW Formation and Class) Version 1.0. VIS_ID 4214 Function: download
Unique resource identifier
Code	c4c8e030-647c-4f81-b678-d7d6a61d7359
Presentation form	Map digital
Edition	unknown
Dataset language	English
Metadata standard
Name	ISO 19115
Edition	2016
Dataset URI	https://datasets.seed.nsw.gov.au/dataset/c4c8e030-647c-4f81-b678-d7d6a61d7359
Purpose	This dataset was developed as part of the OEH State Vegetation Map to provide government and community with regional -scale information about native vegetation.
Status	On going
Spatial representation
Type	vector
Geometric Object Type	complex
Geometric Object Count	1
Spatial reference system
Code identifying the spatial reference system	4283
Equivalent scale	1:None
Additional information source	General Notes: For details on methodology and validation please refer to the CWL Technical Notes. Technical Notes Pending. NSW Office of Environment and Heritage, 2015. BRG-Namoi Regional Native Vegetation Mapping. Technical Notes, NSW Office of Environment and Heritage, Sydney, Australia. Central West /Lachlan Regional Native Vegetation Mapping Please note related dataset: CentWestLach_v1_0_PCT_E_4358. This dataset also includes PCT classification.

Classification of spatial data and services

Field	Value
Topic category

Keywords

Field	Value
Keyword set
keyword value	Central West Lachlan CWL PCT Plant Community Types Regional Scale Vegetation Mapping
Originating controlled vocabulary
Title	ANZLIC Search Words
Reference date	2008-05-16
Geographic location
West bounding longitude	143.82802
East bounding longitude	150.362018
North bounding latitude	-34.74714
South bounding latitude	-30.11553
Vertical extent information
Minimum value	-100
Maximum value	2228
Coordinate reference system
Authority code	urn:ogc:def:cs:EPSG::
Code identifying the coordinate reference system	5711
Temporal extent
Begin position	2015-10-09
End position	N/A
Dataset reference date
Resource maintenance
Maintenance and update frequency	As needed
Contact info
Contact position	Data Broker
Organisation name	NSW Department of Climate Change, Energy, the Environment and Water
Telephone number	131555
Email address	data.broker@environment.nsw.gov.au
Web address	https://www.nsw.gov.au/departments-and-agencies/dcceew
Responsible party role	pointOfContact

Quality and validity

Field	Value
Lineage	A summary of the product's lineage is below. This may change after product review. Please refer to pending technical notes for a detailed description of the methodologies and source datasets. The PCT map was derived primarily using a spatial modeling approach augmented with high resolution aerial imagery (50cm ADS40) for visual interpretation and automated line-work derivation. In summary the process for PCT attribution involved the following: Vegetation Survey and Classification: Existing floristic plot data comprised over 11000 existing sites after data cleaning. A large number of gaps in existing survey coverage were evident and required further survey information. To allocate survey sites to PCTs, full floristic plots were analysed using a UPGMA clustering approach in Primer with significant groups identified using SIMPROF and species contributions for each resulting group calculated using SIMPER. Pattern Derivation: A multi-resolution segmentation algorithm was used to create image objects with low internal variation. Image objects represent patches of vegetation that can later be classified based on attributes such as crown cover, spectral response, or soil type. The segmentation parameters and scale was derived iteratively based on visual inspection. Vegetation patterns from existing stereoscopic aerial photo interpretation and those recognised in high spatial resolution imagery (ADS40) were used as a reference point. Segmentation was performed using ADS40, SPOT 5 and SRTM derived topographic indices. This process provided the line work for subsequent PCT attribution. Visual attribution of Landscape Class: The purpose of attributing Landscape classes to polygons is to predetermine broad vegetation types for modeling purposes using remote sensing. These classes reduce the PCT options for any one polygon making the modeling more effective in its attribution with commensurate less computing effort/time. A landscape class was attributed to every polygon in the study area. Landscape classes were aided by reference to existing mapping. Corrections were made based on ADS40 with on-screen attribution. Every polygon was visually checked by an expert interpreter. Modeling Envelopes: As a further constraint to modeling outcomes, spatial envelopes were used to constrain PCTs to a certain geographic range, reducing the amount of types competing within the model at any particular location. The constraints used were applied at different stages in the mapping process. The constraints were derived from particular IBRA (Interim Bioregionalisation of Australia v7; Commonwealth of Australia 2012) subregions, selected based on review of the literature and expert opinion. The type models were constrained to particular ranges of a topographic position index, again based on literature review and expert opinion. Not all types were constrained by topographic envelopes, as some were considered to be less correlated with particular topographic positions. Spatial Distribution Modeling of Plant Community Types. Modeling of PCT used Boosted Regression Trees (BRT). A suite of candidate environmental predictor variables, including climate, geology, soil, geophysical data, and terrain indices, were compiled for use in BRT models. A comprehensive list of these predictor variables will be found in the Technical Notes. Uplifted API and Expert Editing: Vegetation communities from the MacquarieMarshesVeg2008_VIS3920 (Bowen, S. & Simpson, S. (2009)) were spatially translated into the current line-work via a majority extent per polygon algorithm. The vegetation community mapping resulting from the aforementioned procedures was extensively edited on screen to correct attribution where there may have been for example existing API, missed vegetation, ecological anomalies, incorrect assignments, modeling noise and inclusion of late site data. For further details on methodology and validation please refer to the pending Central West Regional Native Vegetation Mapping Technical Notes Version 1.0.

Field

Value

Lineage

A summary of the product's lineage is below. This may change after product review. Please refer to pending technical notes for a detailed description of the methodologies and source datasets.

The PCT map was derived primarily using a spatial modeling approach augmented with high resolution aerial imagery (50cm ADS40) for visual interpretation and automated line-work derivation.

In summary the process for PCT attribution involved the following: Vegetation Survey and Classification: Existing floristic plot data comprised over 11000 existing sites after data cleaning. A large number of gaps in existing survey coverage were evident and required further survey information. To allocate survey sites to PCTs, full floristic plots were analysed using a UPGMA clustering approach in Primer with significant groups identified using SIMPROF and species contributions for each resulting group calculated using SIMPER. Pattern Derivation: A multi-resolution segmentation algorithm was used to create image objects with low internal variation. Image objects represent patches of vegetation that can later be classified based on attributes such as crown cover, spectral response, or soil type. The segmentation parameters and scale was derived iteratively based on visual inspection. Vegetation patterns from existing stereoscopic aerial photo interpretation and those recognised in high spatial resolution imagery (ADS40) were used as a reference point. Segmentation was performed using ADS40, SPOT 5 and SRTM derived topographic indices. This process provided the line work for subsequent PCT attribution.

Visual attribution of Landscape Class: The purpose of attributing Landscape classes to polygons is to predetermine broad vegetation types for modeling purposes using remote sensing. These classes reduce the PCT options for any one polygon making the modeling more effective in its attribution with commensurate less computing effort/time. A landscape class was attributed to every polygon in the study area. Landscape classes were aided by reference to existing mapping. Corrections were made based on ADS40 with on-screen attribution. Every polygon was visually checked by an expert interpreter.

Modeling Envelopes: As a further constraint to modeling outcomes, spatial envelopes were used to constrain PCTs to a certain geographic range, reducing the amount of types competing within the model at any particular location. The constraints used were applied at different stages in the mapping process. The constraints were derived from particular IBRA (Interim Bioregionalisation of Australia v7; Commonwealth of Australia 2012) subregions, selected based on review of the literature and expert opinion. The type models were constrained to particular ranges of a topographic position index, again based on literature review and expert opinion. Not all types were constrained by topographic envelopes, as some were considered to be less correlated with particular topographic positions.

Spatial Distribution Modeling of Plant Community Types. Modeling of PCT used Boosted Regression Trees (BRT). A suite of candidate environmental predictor variables, including climate, geology, soil, geophysical data, and terrain indices, were compiled for use in BRT models. A comprehensive list of these predictor variables will be found in the Technical Notes.

Uplifted API and Expert Editing: Vegetation communities from the MacquarieMarshesVeg2008_VIS3920 (Bowen, S. & Simpson, S. (2009)) were spatially translated into the current line-work via a majority extent per polygon algorithm. The vegetation community mapping resulting from the aforementioned procedures was extensively edited on screen to correct attribution where there may have been for example existing API, missed vegetation, ecological anomalies, incorrect assignments, modeling noise and inclusion of late site data.

For further details on methodology and validation please refer to the pending Central West Regional Native Vegetation Mapping Technical Notes Version 1.0.

Constraints related to access and use

Field	Value
Limitations on public access

Data Quality

Field	Value
Scope	dataset
DQ Topological Consistency
Effective date	1901-01-01
Explanation	geometrically and topologically correct
DQ Absolute External Positional Accuracy
Effective date	1901-01-01

Responsible organisations

Field	Value
Responsible party
Contact position	Data Broker
Organisation name	NSW Department of Climate Change, Energy, the Environment and Water
Telephone number	131555
Email address	data.broker@environment.nsw.gov.au
Web address	https://www.nsw.gov.au/departments-and-agencies/dcceew
Responsible party role	pointOfContact

Metadata on metadata

Field	Value
Metadata point of contact
Contact position	Data Broker
Organisation name	NSW Department of Climate Change, Energy, the Environment and Water
Telephone number	131555
Email address	data.broker@environment.nsw.gov.au
Web address	https://www.nsw.gov.au/departments-and-agencies/dcceew
Responsible party role	pointOfContact
Metadata date	2024-10-09T02:17:59.324040
Metadata language

Identification

Title

Alternative title(s)

Abstract

Resource locator

Data Quality Statement

Unique resource identifier

Code

Presentation form

Edition

Dataset language

Metadata standard

Name

Edition

Dataset URI

Purpose

Status

Spatial representation

Type

Geometric Object Type

Geometric Object Count

Spatial reference system

Code identifying the spatial reference system

Equivalent scale

Additional information source

Classification of spatial data and services

Topic category

Keywords

Keyword set

keyword value

Originating controlled vocabulary

Title

Reference date

Geographic location

West bounding longitude

East bounding longitude

North bounding latitude

South bounding latitude

Vertical extent information

Minimum value

Maximum value

Coordinate reference system

Authority code

Code identifying the coordinate reference system

Temporal extent

Begin position

End position

Dataset reference date

Resource maintenance

Maintenance and update frequency

Contact info

Contact position

Organisation name

Telephone number

Email address

Web address

https://www.nsw.gov.au/departments-and-agencies/dcceew

Responsible party role

Quality and validity

Lineage

Constraints related to access and use

Limitations on public access

Data Quality

Scope

DQ Topological Consistency

Effective date

Explanation

DQ Absolute External Positional Accuracy