Alteryx Spatial Tools - Part 3 - Spatial Match & Trade Area (additional example)

by Liu Zhang

More example for the tool introduced in the previous blog.

We will introduce a new data set for this session, information about main road within central London.

Input data

The spatial object is attracted within the input file, where the spatial object is a Line object that presents the road in London.

Map view

Notice the line segments are not necessary straight lines, underlyingly, line objects are made from point objects within Alteryx, so we can make all kind of shapes from a collection of points.

We aim to find knowledge about maxspeed around the schools (as from previous blog)

To make the calculation more manageable and easy to view in the map, we will filter the school with postcode contain SE16. Among the remaining schools, we will again create a TradeArea around each with a 200m radius.

TradeArea added columns in the end

Now we have an area, we can use them to match the roads by using Spatial Match tool.

Same configuration as previous blog

We repeat what we have done in the previous blog, by using Target Intersects Universe setting to use school trade areas to capture the road line segments.

Notice the duplicate entries

It is not obvious about why all duplicates in the results pane, we will need to view it on the map to see the reason.

Map view
Detailed map view

Turns out for each street/road there are multiple segments within it, due to road crossing, traffic lights etc. hence the appeared duplication rows. If we want to measure the length of the road (see next blog) then we will need each individual row, but here, we only want to find out about maxspeed which is constant for each segments of the same street/road, then we can remove the duplication.

Note: There are cases of unmatched results
Unique tool configuration

As long as we are not selecting the last column Street Location (the line spatial object), we will able to remove duplicate rows.

From the results, we can ask What is average maxspeed around each school? And to answer this question, we can use a Summarize tool.

Summarize tool configuration
Results table

(We can sort the results by Avg_Max_Speed if needed)

This shows us that in SE16 postcode, the schools that have high maxspeed around it's surroundings. It is a result that people can use to act on.

Final workflow

Looking for more guides, tips and tricks in Tableau or Alteryx? Go check out the other blog posts from the Data School.

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