SA Wilderness Inventory (Human Industrial Footprint Index and Ecological Intactness Index)

Dataset Number 2726
Dataset Title SA Wilderness Inventory (Human Industrial Footprint Index and Ecological Intactness Index)
Status Published
Metadata Maintained by DEW SMK

Description

Category Biological Conservation
Theme Wilderness
Keywords and Qualifiers ECOLOGY Landscape
LAND
LAND Use
VEGETATION
Dataset Type Spatial
Description The South Australian wilderness inventory analysis comprises of two datasets: the Human Industrial Footprint Index (HII) and the Ecological Intactness Index (EII).

The HII dataset maps modern industrial level pressures at a fine resolution for the State and was developed by analysing a suite of terrestrial pressure layers, with each pressure layer weighted according to their impact on wilderness. The pressure layers used in this analysis include built environments, crop lands, pastureland, human population density, night-time lights, roads, railways, navigable waterways, dams and reservoirs, forestry, mining, oil and gas. A HII index was produced by summing all the weighted pressure layers together, with the final dataset created at a resolution of 300m. Thresholds were used as proxy for categorising an area as wilderness: with wilderness (HII values <1), intact lands (HII values < 4), and degraded lands (HII Values >= 7).

The EII dataset maps the intactness of ecosystems by measuring changes in habitat area, quality and fragmentation, and can be calculated at large spatial scales (i.e. ecosystem types, bioregions, etc.). The EII dataset has been developed using the HII as a proxy for habitat quality, and is based on a continuous, grid-based (raster) representation of variable habitat quality.

Details of the analysis are documented in the South Australian Human Industrial Footprint and Intactness Assessment technical report.
Dataset Use The HII and EII datasets can be used to generate wilderness maps of South Australia to illustrate the continuum of human modification of the natural environment. These wilderness maps can be overlayed with other information to provide a clear idea of how threatened different environments and biodiversity can be.
SDE Feature Class Name LANDSCAPE.HumanIndustrialFootprintIndex
LANDSCAPE.EcologicalIntactnessIndex
Projection/ Coordinate System LAMBERT

Custodian

Data Authority

Data Authority Department for Environment and Water
Data Authority Name Jason Irving
Manager - National Parks and Protected Areas
Data Manager Kathryn Nicolai
Manager National Parks and Protected Area Program
Department for Environment and Water
kathryn.nicolai@sa.gov.au
08 8463 6923
Subject Matter Expert Isabella Schultz
Senior Policy Officer
Department for Environment and Water
isabella.schultz@sa.gov.au
08 8429 7622
Data Integrity Officer Blair Pellegrino
Senior Environmental Information Officer
Department for Environment and Water
Blair.Pellegrino@sa.gov.au
08 8124 4911

Data Provider

Data Provider Department for Environment and Water

Data Quality

Lineage The HII and EII datasets are the product of the Wilderness Inventory research collaboration between DEW and the University of Queensland.

The HII dataset was created using a suite of 12 weighted pressure layers sourced from a range of DEW data bases. Built environments, crop lands, pasture land, forestry, mining data came from the South Australian Land Use data (2008-2017); human population density data came from the Australian population grid (2016); night-time lights data came from VIIRS Annual Night Lights version 2.1 (2016); roads data came from State-wide Road Network, complemented with data from Open Streets Map (2022); railways data came from State-wide Rail Network (2022); navigable waterways data was generated for this study, following methods in Venter et al (2016); and oil and gas data came from Petroleum production licenses and Petroleum Pipeline Facilities and Licenses (2023).

The EII dataset incorporates habitat area, quality, and fragmentation of habitat and was developed using the methodology of Beyer et al. (2020). It uses the HII as a proxy for habitat quality, and is based on a continuous, grid-based (raster) representation of variable habitat quality.

Refer to South Australian Human Industrial Footprint and Intactness Assessment technical report to full details of the analysis methodology.
Completeness Data is available for the terrestrial extent of South Australia.
Positional Accuracy All data is modelled using a 300 m grid across the state. Accuracy will be influenced by the resolution of the input layers.
Method / Capture Scale
MethodCapture ScaleComment
GenerateNot relevantModelling outputs (see report for resolution of input layers)

Tables

Table Name
LANDSCAPE.HumanIndustrialFootprintIndex
LANDSCAPE.EcologicalIntactnessIndex

Field Description

TableNameField AliasData Type% Complete% AccuracyDescription
LANDSCAPE.EcologicalIntactnessIndexValue Integer>95>95Ecological intactness index. Divide value by 1000 to get values indicated in report, i.e. data value of 450 = EII value of 0.45.
LANDSCAPE.HumanIndustrialFootprintIndexValue Integer>95>95Human industrial footprint index. Divide value by 1000 to get values indicated in report, i.e. data value of 3200 = HII value of 3.2.

Geographic Extent

Extent NameSouth Australia
Min Easting or Longitude129
Min Northing or Latitude-38.25
Max Easting or Longitude141
Max Northing or Latitude-26

Dataset Status

Initially Acquired May 2023
Last Updated May 2023
Update Frequency As required
Maintenance Method Datasets are updated as required using adopted methodology created by the collaboration partners. The current data is the first version that uses this methodology, and is documented in the South Australian Human Industrial Footprint and Intactness Assessment technical report.
Metadata Created 18-DEC-2023
If copied, source dataset
Metadata updated 19/DEC/23 env\bpellegrino
Authorised 19/DEC/23 env\bpellegrino
Metadata Retired

Security Classification

ISMF Classification OFFICIAL
ISMF Integrity I2 - MODERATE Requirement
ISMF Availability A2 - MODERATE Requirement
AusGOAL Licensing Classification CC BY (Attribution)
Attribution
Further considerations for supply of dataset No

Operator Notes

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