Namoi Receptor Impact Variables (Pilliga)

Created 11/12/2018

Updated 20/11/2019

Abstract

This dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

This is a spatial layer that is used to produce a risk composite map for the potential ecological impacts on Pilliga region landscape classes.

It essentially categorises the different values of the receptor impact variables (RIV) in to three risk categories: 'no or minimal risk', 'some risk' or 'more at risk' using thresholds defined for each RIV (See Namoi 3.4 for more details).

Dataset History

This is version 01 of the data layer. It was created using landscape classification, receptor impact modelling results and the risk thresholds defined in the Namoi 3-4 report dealing with landscape classes.

Dataset Citation

Bioregional Assessment Programme (2017) Namoi Receptor Impact Variables (Pilliga). Bioregional Assessment Derived Dataset. Viewed 11 December 2018, http://data.bioregionalassessments.gov.au/dataset/ad7c2fdc-794c-4a9e-8a0d-8d5d95e3574d.

Dataset Ancestors

Files and APIs

This dataset has no data

Tags

Additional Info

Field Value
Title Namoi Receptor Impact Variables (Pilliga)
Language eng
Licence Limited access. Requests to the Bioregional Assesment Programme http://www.bioregionalassessments.gov.au/data
Landing Page https://devweb.dga.links.com.au/data/dataset/3b366582-189d-47bd-b74d-16e243a489a0
Contact Point
Bioregional Assessment Program
bioregionalassessments@environment.gov.au
Reference Period -
Geospatial Coverage POLYGON ((0 0, 0 0, 0 0, 0 0))
Data Portal data.gov.au

Data Source

This dataset was originally found on data.gov.au "Namoi Receptor Impact Variables (Pilliga)". Please visit the source to access the original metadata of the dataset:
https://devweb.dga.links.com.au/data/dataset/ad7c2fdc-794c-4a9e-8a0d-8d5d95e3574d

No duplicate datasets found.