PORTAL USER GUIDE

Line Map

 

The Line Map tool is useful for creating visualisations of a lines dataset. It is helpful if you want to distinguish and represent different categories or hierarchies within the same dataset.

This tool is different to Display on Map in the Data pane (Data pane → Dataset → Spanner → Display on Map), which only allows you visualise the dataset as a whole (one single colour), but not differentiate the information within the data table.

SET UP

 

For this worked example, we will look at the different road typologies in Portland.

To do this:

  • Select Portland SA2  (Australia → Victoria → Rest of Victoria → Warrnambool and South West → Glenelg – Southern Grampians → Portland) as your area.
  • Select OpenStreetMap – Lines (Australia) 2017 as your dataset, selecting all attributes.

Now you are are ready to create a Line Map – follow the inputs instructions below to see how to do this.

Inputs

 

Now that you have added your dataset, you are ready to create a lines map.

To do this, open the Line Map tool (Interactive Maps & Charts → Mapping Lines Line Map) in the Visualise pane. This will bring up a range of fields that need to be populated. Enter your parameters as you see them below.

  • Select a dataset: Here you can choose which of the datasets you would like to display as a map. Select OpenStreetMap – Lines (Australia) 2018.
  • Select an attribute: This is the field that you want to map. If you want your map to make sense, and actually display the variable you are interested in, it is important to make sure you have selected the right attribute to map together with right classifier. Select Highway.
  • Select a classifier: Here we define how we break up our range of values in the attribute. Select Pre-classified. The other options are listed below:
    • Jenks (Natural Breaks): This breaks your data up into intuitive groups based on the shape of the distribution of values.
    • Quantiles: This breaks your groups up into quantiles of your attribute.
    • Equal Intervals: Like above, but breaks the numbers up into equal divisions of your attribute.
    • If your attribute is categorical – that is, if it is a description or a word (such as a land-use zone, or a name, or any kind of “string”) then the parameter will automatically set to Pre-classified.
  • Number of Classes: This slider allows you to define the number of breaks in your data (minimum of 3, maximum of 12). The number that you choose should depend on the distribution of your values, the number of data points (areas) and the information that you are trying to portray with your data. Select 12.
  • Select a palette type: Here you can choose the type of colour scheme for your data – Sequential, which shifts from a shade of one colour to another;  Qualitative, where the colours are unique along the palette (used for Pre-classified); and Diverging, where colours shift to two colours from a central point along a natural spectrum. Select Qualitative.
  • Palette: This allows you to choose the actual colours of your palette (you can switch the ends of the palette around by clicking the Reverse Palette box at the bottom of the box. AURIN uses colours generated by Colour Brewer. Select Paired.
  • Default Opacity: This slider allows you to define how opaque your map is over the base map. 0.00 indicates completely transparent, 1.00 indicates completely opaque. Select 0.50.
  • Hover Opacity: This slider defines the opacity of the line when you run your cursor over it. Like above, 0.00 indicates completely transparent, 1.00 indicates completely opaque. Select 0.85.
  • Stroke/Line Width: This slider allows you to define how wide the lines will be. Select 1.
  • Reverse palette: This reverses the order of the colour in its palette which may be useful if you want its colours on opposing ends. Untick this box.
  • Hide Null Values: This will not give a class to any null values if they exist in your dataset. Untick this box.
  • Save Visualisation as: The default for this field is “[Attribute] -1” It’s a good idea to change the name of this to something that reflects the data, particularly if you plan on having multiple choropleth maps from different datasets. The name that you choose here will also be displayed in the legend automatically generated for your map. Type Road Typologies.

Once you have selected your parameters click Add.

Outputs

 

Once you click Add on the input box, a map will appear automatically in your viewer which should look something like the map shown below. This map shows the different types of roads in Portland, for example, trunk, tertiary, residential, footway, etc.

This type of analysis can provide a better understanding of accessibility, road hierarchy, type of traffic, including speed limits and can be very useful for urban planning and development, as well as policy creation.

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