Towards a classification of planar maps
Alexandre Diet, Marc Barthelemy

TL;DR
This paper introduces a novel method using Gini coefficient profiles to classify and analyze the structural diversity of planar maps, with applications to real-world street networks and their evolution.
Contribution
It proposes a new clustering approach based on Gini profiles derived from recursive area merging, enabling classification and comparison of planar maps.
Findings
Gini profiles effectively distinguish different types of planar maps
Application to real street networks reveals structural similarities and differences
Method captures structural changes over time in urban layouts
Abstract
Planar graphs and their spatial embedding -- planar maps -- are used in many different fields due to their ubiquity in the real world (leaf veins in biology, street patterns in urban studies, etc.) and are also fundamental objects in mathematics and combinatorics. These graphs have been well described in the literature, but we do not have so far a clear way to cluster them in different families. A typology of planar maps would be very useful and would allow to monitor their changes, to compare them with each other, or to correlate their structure with other properties. Using an algorithm which merges recursively the smallest areas in the graph with the largest ones, we plot the Gini coefficient of areas of cells and obtain a profile associated to each network. We test the relevance of these `Gini profiles' on simulated networks and on real street networks of Barcelona (Spain), New York…
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