Aurin portal user guide

Diversity index tool

Introduction

A diversity index measures the degree of specialisation or alternatively the degree of diversity across attributes within a spatial unit. This allows spatial units to be compared as to the mix of the characteristics being measured.

The diversity index for a particular region can range from 0 to 1, where a score approaching 0 indicates an increasing degree of diversity and a score approaching 1 indicates an increasing degree of specialisation. Determination of whether a region has a high or low diversity index is done by comparing the diversity index scores across all regions.

Set Up

For this worked example we will calculate the diversity of dwelling structures for for SA2s across Melbourne

To do this:

Select Greater Melbourne (gccsa_2016/2GMEL) as your area
Select the following datasets and variables:

Dataset	Variables
*SA2-G32 Dwelling Structure-Census 2016*	SA2 Code 2016
	SA2 Name 2016
	Occupied private dwellings Separate house Dwellings
*NATSEM - Social and Economic Indicators - Synthetic Estimates SA2 2016*	Occupied private dwellings Semi detached row or terrace house townhouse etc with Total Dwellings
	Occupied private dwellings Other dwelling Improvised home tent sleepers out Dwellings
	Occupied private dwellings Other dwelling House or flat attached to a shop office etc Dwellings
	Occupied private dwellings Other dwelling Caravan Dwellings
	Occupied private dwellings Other dwelling Cabin houseboat Dwellings
	Occupied private dwellings Flat or apartment In a three storey block Dwellings
	Occupied private dwellings Flat or apartment In a one or two storey block Dwellings
	Occupied private dwellings Flat or apartment In a four or more storey block Dwellings
	Occupied private dwellings Flat or apartment Attached to a house Dwelling

Once you have added these datasets, you are ready to use the Diversity Index tool – click the Inputs tab above to see how to do this

Inputs

Once you have added this dataset to your cart, open the Diversity Index tool (Tools → Indices → Diversity Index) and enter the parameters as shown in the image below (these are also shown under the image)

To do this click the Tools button in the Analyse panel, click Indices and then Diversity Index. Enter your parameters as shown in the image below and click the Add and Run button. These parameters are also explained below

Diversity Index Tool Parameters

Dataset Input: the dataset that contains the variables you would like to include. In this instance, select SA2-G32 Dwelling Structure-Census 2016
Key Column: the column containing the unique identifier for each area. In this instance, select SA2 Code 2016
Variables: the variables you would like to be included in the calculation of the index. In this instance, select all of the dwelling counts that you have included.

Outputs

Once the tool has run, a pop up box will appear asking you to display your results (shown below). Click Display to open the output table. You will see that there has been an entirely new table created (also shown below), which now has an additional column at the end (Diversity Index) which represents the Diversity Index Score. If you sort the table, you will note that there are rows that have a diversity index score of zero. These are rows with zero counts for all different kinds of dwellings and will need to be removed with the next step. Before that, you should now rename this datasets to something meaningful and easy to recognise

Filter Dataset Inputs

This tool allows you to keep some parts of a dataset based on their values.

To do this click the Tools button in the Analyse panel, click Data Manipulation and then Dataset Attribute. Enter your parameters as shown in the image below and click the Add and Run button. These parameters are also explained below

DATASET ATTRIBUTE FILTER TOOL PARAMETERS

Dataset Input: The dataset that you would like to run the filter over. In this instance, we are using Dwelling Diversity Index
Attribute: The attribute that you would like to use to filter based on its values. In this instance we are using Diversity Index
Operator: the rule for describing the data that you want to keep. In this instance, we are selecting Greater Than
Attribute Value: The ‘value’ for applying to the attribute. In this instance we are selecting 0.

Outputs

Once you have run the tool, click on the Display button. This will open up the new dataset now shown in your Data panel named Output: geojson_filter XXX (you should rename this something meaningful). If you open the dataset and sort lowest to highest, you will note that there are no SA2s in this dataset with a zero Diversity Index. You are now ready to map this

Recall that the Diversity Index ranges from 0 to 1 and that scores close to 0 indicate higher diversity. This means that when you create your choropleth for this particular variable, you should click the reverse palette options (shown below)