A shape-based heuristic for the detection of urban block artifacts in street networks

TL;DR

This paper introduces a computational heuristic to identify non-urban block geometries in street networks, aiding automated preprocessing for various urban analysis tasks.

Contribution

It presents the first shape-based heuristic method for detecting face artifacts in street networks, improving urban network data quality.

Findings

Successfully identified face artifacts in 89% of 131 cities

Revealed regional differences in city development patterns

Provides a foundation for automated street network simplification

Abstract

Street networks are ubiquitous components of cities, guiding their development and enabling movement from place to place; street networks are also the critical components of many urban analytical methods. However, their graph representation is often designed primarily for transportation purposes. This representation is less suitable for other use cases where transportation networks need to be simplified as a mandatory pre-processing step, e.g., in the case of morphological analysis, visual navigation, or drone flight routing. While the urgent demand for automated pre-processing methods comes from various fields, it is still an unsolved challenge. In this article, we tackle this challenge by proposing a cheap computational heuristic for the identification of "face artifacts", i.e., geometries that are enclosed by transportation edges but do not represent urban blocks. The heuristic is based on combining the frequency distributions of shape compactness metrics and area measurements of street network face polygons. We test our method on 131 globally sampled large cities and show that it successfully identifies face artifacts in 89\% of analyzed cities. Our heuristic of detecting artifacts caused by data being collected for another purpose is the first step towards an automated street network simplification workflow. Moreover, the proposed face artifact index uncovers differences in structural rules guiding the development of cities in different world regions.