Rapid Urban Analysis

Assuming you want to do a study of an urban area, we will go through a process of how you might reveal some of the patterns evident using underlying datasets available via the AURIN portal.

Mapping Land Use

This analysis is more focussed on the locality. In the Area Selection browser, find the area you want to study. We want to capture enough of the context of the area, but also be aware that the meshblock data is pretty heavy (lots of polygons).
Now, open the dataset browser and load the Meshblocks for your area: (MB Mesh Block 2011 Census for Australia), with all attributes selected. The dataset will appear in your data panel. You will notice the data contains a field called “MB_Category” – this classifies the meshblock according to their land use. Go to ‘Maps, Charts and Graphs’ and match these parameters:
Land use categories

Urban Density

The meshblocks also contain attributes for the number of people and dwellings contained within them. Of course, we can just make a map showing the total numbers, but this is misleading- naturally, the larger a meshblock, the more people it would contain. A better measure is to map the persons per unit of area. To do this, match the following settings in the walkability tool:
Screenshot 2015-03-23 12.32.33

Now, we can create a choropleth map of the density (in persons per Hectare)

These settings make a map of the Z-score. The Z-score sets the mean to zero- so we choose a palette with 5 colours (so there is a ‘middle’) and set ‘diverging’ so negative scores are red, and positive scores are green:
Screenshot 2015-03-23 12.35.20

Similarly, we can map the density column as a simple continuum:

Screenshot 2015-03-23 12.34.47

Undertaking a location quotient analysis

Location Quotient workflow– use Victoria instead of WA.
(Also see Shift-share)
These datasets already have election data set to LQ:

  • Location Quotient (LQ) by PB for 2013 Australian federal election
  • Location Quotient (LQ) by PBC for 2013 Australian federal election

Employment cluster analysis

Analysing Industry Clustering– use a Victorian LGA