Border Rivers Gwydir / Namoi Regional Native Vegetation Map Version 2.0. VIS_ID 4204

## **Abstract** 

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.



The Border Rivers Gwydir and Namoi Regional Vegetation Map is a subset of the statewide vegetation mapping and classification program undertaken by the NSW Office of Environment and Heritage (OEH Regional Scale State Vegetation Map) and covers the two former Catchment Management Authority Regions.\\n\\nThe 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.\\n\\nThe full dataset comprises the following data layers as delivered in an ArcGIS 9.3 File Geo-database:\\n\\nPLANT COMMUNITY TYPE: The primary map of Plant Community Types developed from an ensemble of visual interpretation of high resolution imagery and spatial distribution models.\\n\\nWOODY EXTENT LAYER: A map of woody vegetation derived from classification of 5m SPOT-5 imagery.\\n\\nKEITH CLASS: A map based on aerial photo interpretation and spatial distribution models.\\n\\nMAP SOURCE: A map of the various sources of information used including spatial models, visual interpretation and existing map products.\\n\\nSURVEY DENSITY ALL: A map of the density of all survey sites used.\\n\\nSURVEY DENSITY FULL FLORISTICS: A map of the density of only full floristic survey sites used.\\n\\nMODELLING CONFIDENCE: A map of the confidence outcomes achieved.\\n\\nWhile much of the aerial photo interpretation employed was undertaken at around 1:8000, PCT attribution is generally at a much coarser scale. The Map Source layer (as described above) can be used as a guide to how vegetation attribution was derived. We recommend that the highest resolution appropriate for this product be 1:15000.\\n\\nValidation Summary:\\n\\nPCT Map: Based on 100% of the survey data (modelling and hand mapping), the final mapped product has an accuracy in the range 68%-70% for prediction of the three most likely PCTs. Be aware that these accuracies are highly variable across each PCT. Some PCT's utilised more site data than others. Keith Class reached a 76% accuracy using the independent test data. Modelled PCT and modelled top 3 PCT overall accuracies were 53% and 68% respectively. Woody Extent received a 92% overall accuracy.\\n\\nAccompanying documents:\\nBRGNamoi Technical Notes.pdf - Technical Report \\nBRGN_PCT_KC_LUT.xls - A look-up table listing the relationship between PCT, Keith Class and Keith Formation classifications.\ \nBRGNv2_Spatial_Layer_Descriptors.txt\\nBRGN_V2.mxd\\nBorder Rivers Gwydir / Namoi Regional Native Vegetation Mapping\\nTechnical Notes Version 1.0. Reference: NSW Office of Environment and Heritage, 2015. BRG-Namoi Regional Native Vegetation Mapping. Technical Notes, NSW Office of Environment and Heritage, Sydney, Australia.\\n\\nThe download package contains a "quick view" map composite of the study area only. The quick view maps are of PCT, Keith Class, Keith Form, Map Source and Modelling Confidence. They also show the broad-scale line work. For more detailed line work and woody percent per polygon, please refer to the full dataset.\\n\\nFor access queries regarding the full dataset, please contact: data.broker@environment.nsw.gov.au\\n\\nBRG_Namoi_v2_0_E_4204.\\n\ \nVIS_ID 4204

## **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.

## **Dataset History** 

A summary of the product's lineage is below. Please refer to the Technical Notes v1.0 for a detailed description of the methodologies and source datasets.\\n\\nThe 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.\\n\ \nIn summary the process for PCT attribution involved the following: \\n\\n1. Vegetation Survey and Classification: Existing floristic plot data comprised 9054 existing sites after data cleaning. A large number of gaps in existing survey coverage were evident and required further survey information. Stratification based on archive broad vegetation type mapping (Regional Vegetation Types; Eco Logical Australia 2008b) and gap analysis was undertaken to select locations for additional plot data collection. A total of 6013 additional rapid data points were collected. 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. The existing plot data were allocated across 258 PCTs.\\n\\n2. 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.\\n\\n3. Visual attribution of Landscape Class: The purpose of attributing Landscape classes to polygons is to predetermine broad vegetation types for modelling 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.\\n\\n4. Modelling Envelopes:As a further constraint to modelling 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 Keith Class (Keith 2004) models were constrained to 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.\\n\\n5. Spatial Distribution Modelling of Keith Classes and Plant Community Types. Modelling of Keith Class and PCT used a combination (ensemble) of Generalised Dissimilarity Model (GDM), Boosted Regression Trees (BRT), and a simple Nearest Neighbour model.A suite of candidate environmental predictor variables, including climate, geology, soil, geophysical data, and terrain indices, were compiled for use in the GDM and BRT models. A comprehensive list of these predictor variables can be found in the Technical Notes v1.0.\\n\\n6. Uplifted API and Expert Editing: Vegetation communities from the Gwydir Wetlands and Floodplain Vegetation Map 2008 (Bowen & Simpson 2010) 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, modelling noise and inclusion of late site data. The extent of each attribution source is delineated by the Map Source data layer provided in this dataset.\\n\\nFor further details on methodology and validation please refer to the Border Rivers Gwydir / Namoi Regional Native Vegetation Mapping\\nTechnical Notes Version 1.0. Reference: NSW Office of Environment and Heritage, 2015. BRG-Namoi Regional Native Vegetation Mapping. Technical Notes, NSW Office of Environment and Heritage, Sydney, Australia.

## **Dataset Citation** 

NSW Office of Environment and Heritage (2015) Border Rivers Gwydir / Namoi Regional Native Vegetation Map Version 2.0. VIS_ID 4204. Bioregional Assessment Source Dataset. Viewed 11 December 2018, http://data.bioregionalassessments.gov.au/dataset/b3ca03dc-ed6e-4fdd-82ca-e9406a6ad74a.

Tags: Namoi subregion, New South Wales, biota, environment
Organization: Bioregional Assessment Program