Heatmap - Connectivity

The Heatmap - Connectivity indicator, produces a color-coded map to visualize the connectivity of locations within an area of interest (AOI).

1. Explanation

The heatmap uses a color-coded hexagonal grid to show how well-connected different areas are. It takes an Area of Interest (AOI), a routing type (walking, cycling, etc.), and a travel time limit as inputs. Considering real-world transport and street networks, it calculates the connectivity of each hexagon within the AOI.

info

Heatmap computation is available across over 30 European countries for Walk, Bicycle, Pedelec, and Car. For Public Transport, Germany, Switzerland, and the Haut-Rhin region of France are supported. If you need analyses beyond these regions, feel free to contact us and we'll discuss further options.

2. Example use cases

• Does the existing transport network provide equitable access across the AOI?
• How well connected is the street, footpath, or cycle lane network in a specific area?
• How do locations within an AOI compare in terms of connectivity across the different modes of transport?
• Are there barriers, gaps, or islands within the street network that hinder connectivity?

3. How to use the indicator?

1

Click on Toolbox .

2

Under the Accessibility Indicators menu, click on Heatmap Connectivity.

Routing

3

Pick the Routing Type you would like to use for the heatmap.

Mode	Considers	Speed assumed
Walk	All paths accessible by foot	5 km/h
Bicycle	All paths accessible by bicycle (surface, smoothness, slope)	15 km/h
Pedelec	All paths accessible by pedelec (surface, smoothness)	23 km/h
Car	All paths accessible by car (speed limits, one-way restrictions)	—

4

Choose a Travel Time Limit for your heatmap. This will be used in the context of your previously selected Routing Type.

Hint

Need help choosing a suitable travel time limit for various common amenities? The "Standort-Werkzeug" of the City of Chemnitz can provide helpful guidance.

5

Select the Reference Layer (layer containing your AOI) for which you would like to calculate the heatmap. This can be any polygon feature layer.

Result Layer

6

Set the Result layer name for the output heatmap layer.

7

Click Run to start the calculation of the heatmap.

Results

Once the calculation is complete, a result layer will be added to the map. This Heatmap Connectivity layer will contain your color-coded heatmap. Clicking on any of the heatmap's hexagonal cells will reveal the computed connectivity value for this cell.

Tip

Want to style your heatmaps and create nice-looking maps? See Styling.

4. Technical details

Calculation

For each hexagon in the grid within the Area of Interest (AOI), the tool identifies all surrounding hexagons that can reach it. These surrounding hexagons can be outside the AOI but must be within the specified travel time and using the chosen travel method.

Connectivity formula:

The connectivity formula calculates the total area (in square meters) from which a destination cell within the Area of Interest (AOI) can be reached. It does this by considering the number of cells that can reach the destination cell within each travel time step i up to the specified travel time limit n. The sum of all these reachable areas gives the final connectivity value for that cell.

Grid cells

Heatmaps in GOAT utilize Uber's H3 grid-based solution for efficient computation and easy-to-understand visualization. Behind the scenes, a pre-computed travel time matrix for each routing type utilizes this solution and is queried and further processed in real-time to compute accessibility and produce a final heatmap.

The resolution and dimensions of the hexagonal grid used depend on the selected routing type:

Mode	Resolution	Average hexagon area	Average hexagon edge length
Walk	10	11,285.6 m²	65.9 m
Bicycle	9	78,999.4 m²	174.4 m
Pedelec	9	78,999.4 m²	174.4 m
Car	8	552,995.7 m²	461.4 m

Hint

For further insights into the Routing algorithm, visit Routing. In addition, you can check this Publication.

Visualization

For visualization, the result form the connectivity analysis, uses a classification method based on quantiles by default. However, various other classification methods may be used instead. Read more in the Data Classification Methods section of the Attribute-based Styling page.