We run a series of queries on overpass turbo to get the most important features per city

running a query on overpass

We create a buffer around the new points and we dissolve the layer into a single multipolygon

we have different layers showing the most important city features

We calculate the distance from the closest polygon and label them by customer segment

we have different layers showing the public spaces

We calculate correlation between features

correlation between features and distances

feature and spot overlapping

Population density

We enrich poi information with official statistical data like:

population density

men/women asymmetry

foreigner percentage

flat density

land use

age asymmetry

We don’t know a priori which parameter is relevant for learning and we might have surprisingly perfomances from features that do not seem to have connection with the metric.

distribution of official census data

To obtain the value of population density we interpolate over the neighboring tiles with official census data using a stiff multiquadratic function.

Distribution of expense power across the city

expense power

determination of the density value coming from the neighboring tiles of the official statistics

We than obtain an approximation on smaller geometries

population density interpolation

And obtain an estimation on percentage of foregners, flat use, land use…

foreign distribution

Degeneracy

Degeneracy is a measure of sparsity or replication of states, in this case we use the term to define the recurrency of pois in a spatial region.

The operative definition is to calculate the distribution of other pois at a certain distance. To reduce the complexity of the metric we perform a parabolic interpolation and define the degeneracy as the intercept of the parabola fitting the radial density distribution.

spatial degeneracy, only the intercept is taken into consideration

Isochrone

For each location we download the local network and calculate the isochrones

isochrone, selected nodes and convex hulls

prediction

In the literature there are different examples of spatial forecast prediction property values.