Data Processing Tour: Types of Shapefiles

Download video

There are three different types of shapefiles:

Each element is an individual space

You can think of a shapefile with suburbs, or a shapefile with all power plants in the city. Every item on the map represents a different reference space. They have a clear and logical individual name and identity. You can imagine writing a description or uploading a photo for these individual spaces.

Elements should be grouped together

These shapefiles contain some sort of a classification of different types of items. For instance, they could contain the land use in the city, or mineral deposits or vegetation types. In all of these cases, we want to group them together by type, so that even if the areas are individual items in the shapefile, they are seen as the same type by the system.

The entire shapefile represents a single entity

This is often the case with networks. For instance, when you have a shapefile with the road network, gas pipe network, or water reticulation system. All of these files will contain many individual segments, but it does not really make sense to see them as individual types. Instead, we want to simply join them all together and see them as a single entity.

Exception: if you have some sort of a network that can be subdivided in different types or groups. If that is the case, use the previous category. Example: the train line network which can be separated by line/route.

Outline of the video

  • Types of shapefiles and the way to process them depending on their nature of content.
  • 3 types: Each element is an individual space, Elements should be grouped together, The entire shapefile represents a single entity
  • M0:13, first and most common type: Each element is an individual space
  • Example: city with individual suburbs, each neighbourhood represents a different space;
  • After the work item is assigned to you, in the next step, the system asks how this should be processed. In this case, we want to make 10 individual spaces, because the file has 10 items. Now the column with the name of the space has to be selected and clicked on next step, before completing the processing as learned before.
  • M1:30, example of land use for the second type of shapefile: Elements should be grouped together
  • This is not a different identity, but in the way in which they are classified. In this case, it is 3 main groupings into which the file should be split up.
  • The way it works, in step 2 of processing this file, you select "group spaces by name". Type of land use is the correct column to choose in that example. Once saved and published, it distinguishes the 3 types: urban expansion, urban and rural.
  • Classification systems are used for land use, soil type, mineral deposits, vegetation type.
  • M5:00, third type of shapefile, which is The entire shapefile represents a single entity
  • Example of a network, where we don't care about the individual items, but the network as a whole, e.g. transmission lines, water and sewer pipes, gas pipes; It helps to consider how it is named.
  • In this example, we need to save it as "group into one single space". The table disappears because it is no longer relevant.
  • Saving and publishing it brings us to the entire network. The geospatial information is not lost, but it records it as one network.
  • M7:41, we have seen three different types, but we have to be careful, because the ones that represent a network can sometimes be grouped. Example: Network of the train network. Segments are part of a certain line. In that case, it makes sense to split them up and group them by names, in this case, the name of the train line.
  • The 52 different segments come out into 5 different lines.
  • This may make sense for train lines, but also road networks, but only if you have the big highways. The entire road network of a city is too detailed and in that case it makes sense to upload as one road network. Important to think critically about what would be done with it.
  • M10:10, recap of three different types