Characterisation of spatial network-like patterns from junctions' geometry

TL;DR

This paper introduces a geometric method to analyze spatial network patterns, distinguishing hierarchical from homogeneous networks by examining junction angles and growth order, applicable to various natural and urban patterns.

Contribution

A novel quantitative approach combining geometric and topological analysis to characterize spatial network patterns and identify growth-related organization.

Findings

Hierarchical networks show large-scale organization and sequential growth.

Homogeneous networks exhibit local but not global organization.

A sharp dichotomy exists between hierarchical and homogeneous classes.

Abstract

We propose a new method for quantitative characterization of spatial network-like patterns with loops, such as surface fracture patterns, leaf vein networks and patterns of urban streets. Such patterns are not well characterized by purely topological estimators: also patterns that both look different and result from different morphogenetic processes can have similar topology. A local geometric cue -the angles formed by the different branches at junctions- can complement topological information and allow to quantify the large scale spatial coherence of the pattern. For patterns that grow over time, such as fracture lines on the surface of ceramics, the rank assigned by our method to each individual segment of the pattern approximates the order of appearance of that segment. We apply the method to various network-like patterns and we find a continuous but sharp dichotomy between two classes of spatial networks: hierarchical and homogeneous. The first class results from a sequential growth process and presents large scale organization, the latter presents local, but not global organization.