Alternative title(s)

MurrayCMA_east_type_E_3808; MurrayCMA_east_data_E_3809; MurrayCMA_west_type_E_3810; MurrayCMA_west_data_E_3811

Abstract

Native vegetation was delineated into stands using feature recognition software. A hybrid classification method that combined spatial modelling and visual interpretation was used to combine the features and create a vegetation map.

SPOT 5 and Landsat satellite imagery was used in the creation of image objects. The spectral response of individual SPOT 5 scenes varied widely across the catchment so it was not used in the classification of vegetation type. Spatial layers used in the classification included a Digital Elevation Model (DEM), Landsat reflectance data, radiometric data and soil and climate layers, all of which are available for the entire State. Over 340 new full floristic survey sites were commissioned and the results were combined with 900 existing survey site records to create training areas for spatial modelling. Each survey site was assigned a New South Wales Vegetation Classification and Assessment (NSWVCA) vegetation type.

The relationship between survey sites and spatial layers was explored by using machine learning software and vegetation type was classified using an object-based nearest neighbour approach. The catchment was divided into three discrete spatial models with separate training and validation survey sites. Model performance was assessed on the basis of the number of NSWVCA types mapped correctly in five classes of precision. The percentage of correctly modelled vegetation types ranged between 58% and 68%.

Several vegetation community types were not able to be modelled (e.g. chenopods) or were poorly modelled due to lack of sample data. These communities were added or amended based on the visual interpretation of remotely sensed data. The amended map was assessed against a limited subset of independent survey data. The percentage of correctly mapped vegetation types in five classes of precision ranged between 72% and 78%.

The mapping was presented in a geodatabase, which allows for user-generated updates so that the product can evolve as more field data are collected.

ROFF, A., SIVERTSEN, D., AND DENHOLM, B. 2010. The Native Vegetation of the Murray Catchment Management Authority Area, NSW Department of Environment, Climate Change and Water, Sydney, Australia.

VIS_ID 3808 VIS_ID 3809 VIS_ID 3810 VIS_ID 3811

Presentation form

Map digital

Edition

Not known

Dataset language

English

Dataset URI

https://datasets.seed.nsw.gov.au/dataset/3b1efa13-6b94-44af-b3d2-82b649eeea39

Purpose

To create a vegetation map of the Murray Catchment Management Authority Area.

Status

Completed

Spatial representation

Spatial reference system

Equivalent scale

1:None

Additional information source

ROFF, A., SIVERTSEN, D., AND DENHOLM, B. 2010. The Native Vegetation of the Murray Catchment Management Authority Area, NSW Department of Environment, Climate Change and Water, Sydney, Australia.

Originating controlled vocabulary

Dataset reference date

Scope

dataset

DQ Completeness Commission

DQ Completeness Omission

DQ Non Quantitative Attribute Correctness

Responsible party

Metadata point of contact

Metadata date

2024-08-28T02:01:39.983516

Metadata language