superblockify: A Python Package for Automated Generation, Visualization, and Analysis of Potential Superblocks in Cities

TL;DR

superblockify is a Python tool that automatically creates, visualizes, and analyzes Superblock neighborhoods in cities to assist urban planning focused on pedestrian and cyclist priorities.

Contribution

it introduces a Python package that automates the partitioning, visualization, and analysis of urban street networks into Superblocks for urban planning and data science applications.

Findings

enables efficient generation of Superblock blueprints

provides descriptive statistics for urban neighborhoods

supports data-driven urban planning processes

Abstract

superblockify is a Python package for partitioning an urban street network into Superblock-like neighborhoods and for visualizing and analyzing the partition results. A Superblock is a set of adjacent urban blocks where vehicular through traffic is prevented or pacified, giving priority to people walking and cycling. The Superblock blueprints and descriptive statistics generated by superblockify can be used by urban planners as a first step in a data-driven planning pipeline, or by urban data scientists as an efficient computational method to evaluate Superblock partitions. The software is licensed under AGPLv3 and is available at https://superblockify.city.