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VAMPIRE 2011 for Australian Capital Cities

These datasets are the Vulnerability Indices for Mortgage, Petroleum and Inflation Risks and Expenditure (VAMPIRE). Each data set is represented as a set of geo-references zones which have a standard VAMPIRE score and a number of input variables (e.g. median household income). The VAMPIRE data sets developed at Griffith University's Urban Research Program provides a measure of socio-economic oil vulnerability in Australian cities, based on an analysis of socio-economic indicators from the ABS. The VAMPIRE data were produced for eight capital cities in Australia for the year 2001, 2006 and 2011, to assess socio-spatial structure of vulnerability from rising transport and housing costs in Australian cities. The standard geographical reference for the VAMPIRE data are SA1 (2011) and CCD (2006 and 2001).

Data and Resources

Additional Info

Field Value
Source https://portal.aurin.org.au
Last Updated September 5, 2019, 23:58 (UTC)
Created February 22, 2017, 02:21 (UTC)
License Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
AURIN Open API ID aurin:datasource-GU_URP-UoM_AURIN_gu_urp_vampire_2011
Aggregation Level sa1
Attribute List Geometry, Median Household Income, Proportion of Dwellings Being Purchased with Mortgage, Proportion of Dwellings with Two or More Cars, Proportion of People that Travel to Work by Car, SA1 Code, Standardised Value of Income, Standardised Value of Journey to Work Car, Standardised Value of Mortgage, Standardised Value of Two Cars, State Name, VAMPIRE Score
Attribution Li, T., Sipe, N. and Dodson, J. (2015). Vulnerability Assessment for Mortgage, Petroleum and Inflation Risks and Expenditure (VAMPIRE) 2011, AURIN Project L01/6, Australian Urban Research Infrastructure Network, Melbourne; accessed from AURIN on [date of access].
Coordinate Ref. System EPSG:4283 (GDA_1994)
Copyright Notice © Griffith University - Urban Research Program 2015
Geometry Field the_geom
Key sa1_main11
Type dataset
spatial {"type": "Polygon", "coordinates": [[[115.618, -43.0141], [153.318, -43.0141], [153.318, -12.3301], [115.618, -12.3301], [115.618, -43.0141]]]}