The street network used to calculate the number of intersections act as a proxy to show the potential mobility of pedestrians within the neighbourhood (it is acknowledged that this is an abstraction of how pedestrians might move through a neighbourhood, but it is readily achievable with available data and past research has shown that it is significantly associated with walking for transport).

Data Sources

See the “Advanced” section in the Neighbourdood Generator tool page for more information.
If the Generate Neighbourhood tool is used to create neighbourhood polygons then the network used in that process should be used in the Connectivity Tool. If users upload their own shapefiles of neighbourhood polygons, these should be used to calculate connectivity within AURIN’s Connectivity Tool.

Analysis Process

Connectivity is measured as the count of three (or more) way street intersections over the area of the participant’s neighbourhood. The units of the denominator are in square kilometres. The section that follows describes how to create a measure of connectivity.


Clicking on the Connectivity tool in the Walkability toolbox opens up the following parameter input box

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There are only three parameters that need to be selected for connectivity analyses:

    • Name: Output name of the resulting polygon layer
    • Street Network: The road or path network that you want to measure connectivity along
    • Neighbourhoods: The digital neighbourhoods that you want to measure connectivity in. These would have been generated using the neighbourhood generator tool.

Once you have selected your parameters, click Add and Run to execute the tool.


Once you have executed the tool, it should appear in your Data panel entitled: Output: walkability-006-connectivity… . You will also get a dialogue box pop up which will allow you to display the outputs in table form (shown below)

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This table contains the calculated connectivity measures:

    •  Connectivity – the number of connections per square kilometre
    •  Area – the square metres of each neighbourhood polygon
    •  Connections  – the number of intersections between three or more paths
    •  Connectivity_ZScore  – the connectivity score normalised to a Z score by the following formula

\(Z_{i} = {X_{i} – \overline{X}\over s}\)

where \(X_{i}\) is the non normalised score of observation \(i\), \(\overline{X}\) is the sample mean and \(s\) is the sample standard deviation. The Z score will tell you how much higher or lower than the rest of the neighbourhoods that a single neighbourhood is (where the mean is 0)

You can also visualise the outputs as neighbourhoods. To do this, click on the spanner symbol next to the connectivity output in your Data panel, and select Display on Map. Once you have selected the colours you want for the neighbourhoods, click Updated and Display. This should cause the neighbourhoods to appear on your map (with a row in you Visualise panel as well). Hovering over a neighbourhood will bring up its connectivity attributes (shown below).

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Alternatively, you can colour the neighbourhoods by one of the attributes. To do this, click the Maps, Charts and Graphs button under Visualise and select Map Visualisations → Choropleth. Select your connectivity output data set as the dataset you want to map, and select the attribute you’d like to display (such as Connectivity, Area, Connections or Connectivity Z Score). Clicking Add and Display will cause the map to come up on your screen (make sure to turn off the other layers you may have displayed to make sure you get a good image. You should get something like what’s shown below:

Walkability Catchments Moonee Ponds

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