Accessibilities

The following two examples use the layers.compute_accessibilities method to compute accessibilities to land uses. In general, the same network pre-processing steps can be followed as shown for these network preparation steps or for the network centrality steps. A data set is their necessary for identifying the locations of different land uses and it is the impossible to compete accessibilities over the network using the layers.compute_accessibilities method.

This method requires:

• A geopandas GeoDataFrame parameter containing landuse data;
• A landuse_column_label identifying the corresponding column which contains the landuse labels;
• The target accessibility keys indicating which landuse types to compute accessibilities for (from the available landuse types in the landuses column).

The output GeoDataFrame will contain new columns for each landuse in the following three forms.

• A count of reachable instances of a given landuse (within the specified distance thresholds)
• Similarly, a distance-weighted count of reachable locations
• The distance to the nearest instance of a given landuse.

The last example follows a similar approach, but computes mixed land-uses using the layers.compute_mixed_uses method.

Landuse accessibility from geopandas data

Calculate landuse accessibilities from a geopandas GeoDataFrame.

Notebook

Landuse accessibility from OSM data

Calculate landuse accessibilities from OpenStreetMap.

Notebook

Calculating mixed-uses

Calculate mixed land-uses.

Notebook