Identification

Field	Value
Title	State Vegetation Type Map: Central West / Lachlan Region Version 1.4. VIS_ID 4468
Alternative title(s)	CentWestLachSVM_v1p4_PCT_E_4468
Abstract	This dataset was superseded by the State Vegetation Type Map (https://datasets.seed.nsw.gov.au/dataset/nsw-state-vegetation-type-map) on 24.06.2022. The NSW Office of Environment and Heritage (OEH) is producing a new map of the State’s native vegetation. This seamless map of NSW’s native vegetation types will enable government, industry and the community to better understand the composition and the relative significance of the native vegetation in their local area. The State Vegetation Type Map (SVTM) (http://www.environment.nsw.gov.au/vegetation/state-vegetation-type-map.htm ) is constructed from the best available imagery, site survey records, and environmental information. Existing vegetation mapping has been integrated in some locations. Each vegetation survey is assigned to a Plant Community Type (PCT) and this is used to create a model of the distribution of each type. Their place in the landscape is then attributed based on the visual interpretation of vegetation structure. The SVTM is designed to be dynamically improved and upgraded as new local information becomes available. Each quickview map is attributed with a code for all three tiers of the NSW vegetation type classification system: Formations, Classes, and Plant Community Types (PCTs). The following fields are available for all maps: PCTID: The unique identifier for the Plant Community Type. The PCT Id is captured as part of the mapping program. PCTName: A colloquial description of the plant community that can be understood by non-botanists. It may include common names of dominant plant species, names of a geographical region, a substrate, a soil type or a climatic zone. PCTIDMod1: The most likely Plant Community Type to occur in the polygon, identified by its PCT Id. This value is as derived from a spatial model that may provide one or more PCT alternatives. It provides an indication of PCT uncertainty, as several PCTs will usually have some probability of occurring at any particular location. PCTIDMod2: The second most likely Plant Community Type identifier as derived from a spatial model. PCTIDMod3: The third most likely Plant Community Type identifier as derived from a spatial model. mapSource: The various sources of information used in deriving the vegetation map, including spatial models, visual interpretation and existing map products. vegetationClass: Equivalence of a community to one of the Vegetation Classes as originally defined in the Keith (2004) Statewide Vegetation Map. vegetationFormation: Equivalence of a community to one of the Vegetation Classes as original defined in the Keith (2004) Statewide Vegetation Map. USER ACCURACY of Plant Community Type Models: These results should be interpreted as a reflection of the model user accuracy, not map accuracy. [Map Accuracy = API Accuracy (visual interpretation of ADS40) x Model Accuracy (PCT Model Results)]. The accuracy of the API produced landscape class map has not been assessed at this stage. The model user accuracy below was derived by cross validation for CWL and RIV and by an 80/20 split for BRGN. User accuracy using cross validation is an estimate of how well the model would perform on a new, unmapped location. PCT User Accuracy is represented as a % (percentage). The number of field survey samples is recorded in the field Number of sites per PCT. The summary table below shows the number of PCTs modelled in each study area and the number of sites available (RIV includes pseudo-sites). PCT User Accuracy is weighted by the Number of sites per PCT. Accuracy is not reported for PCTs with less than 5 records. For a full description per PCT of user accuracy, please see attached 'User_Accuracy_per_PCT_VIS_ID_4468.pdf' located below under 'Data and Resources'. Table 1: SVTM Number of PCTs, number of sites per PCT and PCT User Accuracy (weighted by number of sites) \|:Area::::::\| Number of PCTs \| Number of Sites \| PCT user accuracy weighted by number of sites \| +-----------+-----------------------+----------------------+---------------------------------------------------------------+ \|:NBRG:\| 268:::::::::::::::::::::::\| 2534:::::::::::::::::::\| 54.9::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::\| +-----------+-----------------------+----------------------+---------------------------------------------------------------+ \|:CWL::\| 198:::::::::::::::::::::::::\| 10463:::::::::::::::\| 62.2::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::\| +-----------+-----------------------+----------------------+---------------------------------------------------------------+ \|:RIV:::::::\| 130::::::::::::::::::::::::\| 10699:::::::::::::::\| 57.5:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::\| +-----------+-----------------------+----------------------+---------------------------------------------------------------+ \|:Total::::\| 596:::::::::::::::::::::::::\| 23696::::::::::::::::\| 58.2::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::\| Results based on 80/20 Cal/Val split Cross validation results** Quickview maps are simplified versions of the vegetation maps and only contain a subset of the attributes available. They are easier to navigate but still contain the top 3 most likely PCTs for each polygon. The quickview maps are available by request from the Data.Broker@environment.nsw.gov.au. The full datasets are available as 1:100,000 map tiles, also by request from the Data.Broker@environment.nsw.gov.au. A technical report is in press: State of New South Wales and Office of Environment and Heritage (2016) NSW State Vegetation Type Map – Central NSW, Part A: Summary, NSW Office of Environment and Heritage, Sydney, Australia. Meanwhile, for more technical detail about how the maps are created, or more detailed data, contact Bionet@environment.nsw.gov.au or visit http://www.environment.nsw.gov.au/vegetation/state-vegetation-type-map.htm. VIS_ID 4468
Resource locator
Data Quality Statement - Central West Lachlan VIS ID 4468	Name: Data Quality Statement - Central West Lachlan VIS ID 4468 Protocol: WWW:DOWNLOAD-1.0-http--download Description: DQS - Central West Lachlan SVM VIS ID 4468 Function: download
User_Accuracy_per_PCT_VIS_ID_4468	Name: User_Accuracy_per_PCT_VIS_ID_4468 Protocol: WWW:DOWNLOAD-1.0-http--download Description: User Accuracy per PCT: Central-West / Lachlan : VIS_ID_4468 Function: download
Download ZIP package	Name: Download ZIP package Protocol: WWW:DOWNLOAD-1.0-http--download Description: Download Spatial data and Reports Function: download
Technical Report	Name: Technical Report Protocol: WWW:DOWNLOAD-1.0-http--download Description: Download Technical Report Function: download
KMZ	Name: KMZ Protocol: WWW:DOWNLOAD-1.0-http--download Description: Connect to KML service (view in Google Earth) Function: download
WMS	Name: WMS Protocol: WWW:DOWNLOAD-1.0-http--download Description: Web Map Service (WMS). Connect to WMS for SVTM quickview 5 metre derived grid. Function: download
REST Service	Name: REST Service Protocol: WWW:DOWNLOAD-1.0-http--download Description: ArcGIS REST Services Directory – provides a variety of interfaces for web browsers, GIS users and developers, to view quickview maps (5 metre-derived grid). Function: download
Unique resource identifier
Code	6379ca22-72ad-4915-9e96-62df2848fd2c
Presentation form	Map digital
Edition	Not known
Dataset language	English
Metadata standard
Name	ISO 19115
Edition	2016
Dataset URI	https://datasets.seed.nsw.gov.au/dataset/6379ca22-72ad-4915-9e96-62df2848fd2c
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	curve
Geometric Object Count	1
Spatial reference system
Code identifying the spatial reference system	4283
Equivalent scale	1:None
Additional information source	A technical report is in press: State of New South Wales and Office of Environment and Heritage (2016) NSW State Vegetation Type Map – Central NSW, Part A:

Classification of spatial data and services

Field	Value
Topic category

Keywords

Field	Value
Keyword set
keyword value	Plant Community Type Vegetation
Originating controlled vocabulary
Title	ANZLIC Search Words
Reference date	2008-05-16
Geographic location
West bounding longitude	143.82802
East bounding longitude	150.36202
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	2015-01-01
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. 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.

Field

Value

Lineage

A summary of the product's lineage is below.

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.

Constraints related to access and use

Field	Value
Limitations on public access

Data Quality

Field	Value
Scope	dataset
DQ Completeness Commission
Effective date	1901-01-01
DQ Completeness Omission
Effective date	1901-01-01
DQ Conceptual Consistency
Effective date	1901-01-01
DQ Topological Consistency
Effective date	1901-01-01
Explanation	geometrically and topologically correct
DQ Absolute External Positional Accuracy
Effective date	1901-01-01
DQ Non Quantitative Attribute Correctness
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	2024-02-26T12:55:10.849959
Metadata language

Identification

Title

Alternative title(s)

Abstract

Resource locator

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

Responsible party role

Quality and validity

Lineage

Constraints related to access and use

Limitations on public access

Data Quality

Scope

DQ Completeness Commission

Effective date

DQ Completeness Omission

Effective date

DQ Conceptual Consistency

Effective date

DQ Topological Consistency

Effective date

Explanation

DQ Absolute External Positional Accuracy

Effective date

DQ Non Quantitative Attribute Correctness

Effective date

Responsible organisations

Responsible party

Contact position

Organisation name

Telephone number