Task 5: Identifying critical road segments

Task 5: Identifying critical road segments#

For this task, we imagine that the city of Heidelberg is partially affected by flooding of the Neckar. Such scenarios are becoming increasingly likely in the future due to climate change. The flood has a major impact on the city’s infrastructure. In this exercise, you will use QGIS to analyze the impact of the flood by determining the betweenness centrality of multiple nodes in the city before and after the flooding event.

Download all datasets here. Save the folder on your computer. Unzip the .zip file. The unzipped folder is structured according to the recommended folder structure for QGIS projects. Under “data > input” you find the following datasets:

highways.gpkg (points): Road netowrk of Heidelberg
flood_area.gpkg (polygons): Flood simulation of Heidelberg

STEP 1: Dissolve Layer#

First we want to dissolve the highways layer to combine all the LineString geometries to one LineString. This is important for determining the betweenness centrality in the future steps.

Open the Processing Toolbox and search for Dissolve. Select the highways layer as the Input Layer and leave all other settings at default.

STEP 2: Betweenness Centrality - Before Flood#

Make sure you installed the GRASS GIS provider Plugin. If you don’t know how to install Plugins, click here: Plugins

To determine the betweenness centrality open the Processing Toolbox, choose GRASS, then choose Vector and finally scroll down to v.net.centrality. Select the Dissolved Layer from Step 1 and leave all other settings at default. After the calculation you receive a new Point layer called Network Centrality.

Now you want to make the difference between the values visible for interpretation. Therefore click F7 to open the Layer Styling. There you can choose the new Network Centrality Layer and change Single Symbol to Graduated. You must select betweenness as your Value and finally click Classify.

Tip

To make the differences of the values more visible, you can change the Classification Mode from Equal Count (Quantile) to Natural Breaks (Jenks).

Question

Can you identify critical road segments of the city with higher centrality values by looking at the different nodes? What does this mean for the infrastructure of Heidelberg?

STEP 3: Betweenness Centrality - After Flood#

In a next step, we want to carry out the same analysis after the flood event in order to determine the impact of the flood on the infrastructure in Heidelberg. To do so, we first have to delete the part of the highways layer that is flooded.

Open the Processing Toolbox and search for Difference. Select the Dissolved layer as the Input Layer and the flood_area layer as the Overlay Layer. Leave all other settings at default. After the calculation you receive a new LineString layer called Difference.

Repeat the analysis from Step 2 to determine the betweenness centrality of the Difference Layer.

Tip

To make the values of the two Point Layers more comparable, right click on your second Network Centrality Layer, choose Styles, Copy Styles and then All Style Categories. Then right click on your first Network Centrality Layer, choose Styles, Paste Styles and then All Style Categories. Now the two layers share the same classification for comparison.

Question

Can you identify new critical road segments of the city with high centrality values? How did the range of the values change due to the flood? How did the flood event influence the infrastructure of Heidelberg in general?