{"id":1513,"date":"2016-11-03T23:29:11","date_gmt":"2016-11-03T23:29:11","guid":{"rendered":"http:\/\/blogs.lincoln.ac.nz\/gis\/?p=1513"},"modified":"2023-05-07T03:49:02","modified_gmt":"2023-05-07T03:49:02","slug":"the-evolution-of-a-map","status":"publish","type":"post","link":"https:\/\/blogs.lincoln.ac.nz\/gis\/the-evolution-of-a-map\/","title":{"rendered":"The Evolution of a Map"},"content":{"rendered":"

In the post, the ongoing process of developing a map with a colleague is documented.<\/em><\/p>\n

For many people, GIS is all about the map.\u00a0 And fair enough, too.\u00a0 Why use GIS if you’re not interested in a map?\u00a0 The final destinations for maps are many-fold but their main intent is to communicate the results of some analysis visually.\u00a0 While we tend to focus on the map output, the process of developing a map can be quite interesting in its own right.\u00a0 I’m frequently in the position of working with someone to develop a map for a specific purpose and a back and forth, iterative process is, more often than not, the way it evolves.\u00a0 So in this post I’ll step you through how a colleague and I recently worked through a map from beginning to end – the subject being a map of domestic tourism guest nights for 2016.<\/p>\n

The colleague in question is Jude Wilson from SSPRT.\u00a0 She rang the GIS hotline wanting to create a map for a report that showed the variation in guest nights for domestic tourists during 2016.\u00a0 My first comment: show me the data!\u00a0 Jude sent me a spreadsheet of what they were wanting to map.\u00a0 Data had been collected from tourism operators that broke down their guest nights by domestic and international tourists.\u00a0 One interesting challenge for this map was that the data were collected within RTO areas, which are areas in which regional tourism operators work.\u00a0 They are mostly composed of either regions or districts (TLAs or territorial local authorities).\u00a0 We don’t have an existing layer specifically for RTOs so my first task was to create a new layer that showed these areas.<\/p>\n

Luckily, Bernie from Statistics NZ had done this within the spreadsheet.\u00a0 There was a column on one sheet that had the RTOs broken down and linked to (mostly) existing TLAs.\u00a0 Here’s a screenshot of part of that sheet:<\/p>\n

\"rtosfromspreadsheet\"<\/a><\/p>\n

We,ve already got a layer of the TLAs, shown below:<\/p>\n

\"tlalayer\"<\/a><\/p>\n

To convert this over to an RTO layer, I added a new text field to the attribute table called “RTO” (from the table menu > Add Field of type text with a size of 50 characters).\u00a0 Next, I used a Select by Attribute query to select all the TLAs that make up a each RTO (below is an example for the Northland RTO)<\/p>\n

\"northlandquery\"<\/a><\/p>\n

With those records selected, I then used the Field Calculator to add the RTO name to the right field\u00a0 for the selected records (being a text field I had to enclose the name in quotation marks):<\/p>\n

\"calculatefield\"<\/a><\/p>\n

I did this for each RTO.\u00a0 Once done, I needed to create a new layer that used the RTO names to group the districts together.\u00a0 For this I used the Dissolve<\/a> tool.\u00a0 In essence, what this operation does is take all the records that have the same value in the RTO field and merges them together into a new polygon for each RTO.\u00a0 So now I’ve got the spatial layer I need for the map.\u00a0 In the process, the data went from 158 TLA polygons down to 32 RTO polygons.<\/p>\n

Next I’ve got to link the polygons to the values to be mapped from the spreadsheet.\u00a0 There are two options for this: first, since I’ve only got 32 records, I could go through and add the data for each record one by one\u00a0 This is feasible but leaves the process open to human error, something I’m certainly capable of (as we’ll see).\u00a0 Another option is to use a table join to do this automatically since I’ve already got the data in the spreadsheet.\u00a0 I opted for this approach so as to reduce the possibility of me adding the wrong information in.<\/p>\n

Back in the Excel spreadsheet, let’s look at those data – here’s a screenshot:<\/p>\n

\"data3\"<\/a><\/p>\n

Column H has the data I’d like to map.\u00a0 We can see the RTO area name in column A – I’m going to take advantage of this to link this sheet to my RTO layer.\u00a0 What’s in column H is the % of domestic nights for the year ending March, 2016.\u00a0 Columns E and F have the raw data and column G gives us the totals.\u00a0 Before joining I need to do a few key steps:<\/p>\n