It’s time to do what we have been waiting for (well I have at least!). In this part, we are going to run our analyses and find out which offices fit our requirements. If you cannot remember from back part one, they were the following:
- An office actually exists at the location, e.g. there is an empty office building.
- The office is located in the central district of Amsterdam.
- The office has stations close by (250 meters) so it is easy for employees to get to work.
- The office has a park close by (250 meters) so that employees have the ability to enjoy their lunch outside.
How to run our analyses
We will do our analyses in a specific order.
- First, we will create buffers with a certain distance around parks and stations so that we can see which areas lie within these buffers (e.g. in a certain range of parks and stations).
- We can then intersect (find which areas lie within both buffers) these buffers to see which areas are located within the range of both stations and parks.
- Third, we need to remove those areas that do not lie within the central district of Amsterdam.
- Finally, we need to find out which offices are located in the final areas.
That should do the trick. Let us go through this together. It is not as hard as it might sound! If you are confused, I will explain things while going through this task.
It is time to create our two buffers.
- On the ribbon open the Analysis tab. Click on Buffer in the Tools group. Alternatively, you can click Tools to open the Geoprocessing Pane where you can search for buffer.
- The buffer tool will open in the geoprocessing pane. Now, we want to select which features are being used as input. In this case, this is our stations layers. For input features select TRAMMETRO_STATIONS.
- Let the output features class be as ArcGIS Pro suggests.
- Now we need to input how great the buffer distance is. As discussed before, this is 1000 meters in case of stations since we do not like walking too much to our tram or metro. So, for distance write 250 and Meters as the linear unit. Leave the rest of the fields as is. The fields should look like this:
- Press Run.
- The resulting layer should automatically be added to your map.
- Let’s do the same for parks. Your buffer tool is probably still open. If not, reopen it using the instruction from before. As input feature, select PARKS.
- Make sure the output feature class is set to PARKS_Buffer. You probably do not want to change the directory though.
- Press Run, and another layer gets added to your map. It should look like this:
Intersecting our buffer layers
That is it for our buffers. Now we need to use the intersect tool. This is because we are only interested in areas which lie both within 250 meters of parks, and 250 meters of stations. That is why we want to combine our previous buffer layers and intersect them so we get one remaining layer which only shows areas fulfilling both conditions. The process of doing this will feels very familiar.
- For input features, select both buffer layers from the previous steps. Unless you renamed them these are called PARKS_Buffer, and TRAMMETRO_STATIONS_Buffer.
- Change the output feature class name to Buffer_Intercept. Make sure you only change the file name, but not the local database it is saved in.
- Leave the rest as is. Your intersect tool pane should look like this:
- Press Run.
- The result should look similar to below.
We are getting close now. All we need to do limit our results to the central district, followed by finding which offices are located within these resulting areas.
Clipping our intersect layer
We have found areas that are both close to parks and stations. But we are only interested in those areas that are located within the central district. Luckily, we have used definition queries before on our district layer so that it only shows us the central district. We can use this layer to clip our intersect layer.
- Open the Clip tool pane, found on the Analysis tab.
- Set the input features equal to Buffer_Intercept.
- Set the clip features equal to DISTRICTS.
- You can keep the output feature class as default. Buffer_Intercept_Clip is alright since it is just an intermediate result. XY Tolerance as fine as is.
- Press Run. The result will look similar to this:
Select layer by location
All that is left is selecting those offices that are within the suitable areas. We can do this in different ways, but here we will use the Select layer by location tool. We will simply use it to see which office points are located within the Buffer_Intercept_Clip layer from before. Let’s get started.
- On the Analysis tab, click Tools.
- Insert select layer by location in the text field, and press Enter to search for the tool. Select it in the results.
- As input feature layer select EMPTY_BUILDINGS.
- For relationship select Within.
- Finally, select Buffer_intercept_Clip as selecting features.
- Make sure that the selection type is set to New selection. In contrast to the previous tools, the result of running this tool is a selection of features in the EMPTY_BUILDINGS layer, instead of a new layer.
- Press Run.
- In the bottom right you can see that 4 features are selected. If you open the EMPTY_OFFICES attribute table (right click layer, select Attribute table) you can see these four. In addition, you can see the four markers being select on the map. We would like to save these final four offices as a new layer.Right-click the EMPTY_OFFICES layer, hover over selection, and press Make layer from selection.
- This has created a new layer that is automatically added to the map (EMPTY_BUILDINGS selection). Turn off any buffer layers, and the old EMPTY_OFFICES layer so that your map is less cluttered. If you open the EMPTY_BUILDINGS selection’s attribute table you can see the four chosen offices listed.
And that’s it! We found four offices meeting our requirements. We went from a dataset with all sorts of buildings, filtered out 166 offices, and then finally found 4 offices that we are interested in with the help of several analyses. Great job! I hope you learned a lot while doing this, and let me know what you liked and what you did not like.