arXiv subjects

Geoff Boeing

Publications and source records attributed to Geoff Boeing.

At least 19 recordsLinked to original sources

arXiv2026

Urban Science Beyond Samples: Up-to-Date Street Network Models and Indicators for Every Urban Area in the World

Urban planners need up-to-date, global, and consistent street network models and indicators to measure resilience and performance, model accessibility, and target local quality-of-life interventions. This article presents up-to-date street network models and indicators for every urban area in the world. It uses 2025 urban area boundaries from the Global Human Settlement Layer, allowing users to join these data to hundreds of other urban attributes. Its workflow ingests 180 million OpenStreetMap nodes and 360 million OpenStreetMap edges across 10,351 urban areas in 189 countries. The code, models, and indicators are publicly available for reuse. These resources unlock worldwide urban street network science beyond samples as well as local analyses in under-resourced regions where models and indicators are otherwise less-accessible.

physics.soc-ph↗

arXiv2026

Travel Time Prediction from Sparse Open Data

Travel time prediction is central to transport geography and planning's accessibility analyses, sustainable transportation infrastructure provision, and active transportation interventions. However, calculating accurate travel times, especially for driving, requires either extensive technical capacity and bespoke data, or resources like the Google Maps API that quickly become prohibitively expensive to analyze thousands or millions of trips necessary for metropolitan-scale analyses. Such obstacles particularly challenge less-resourced researchers, practitioners, and community advocates. This article argues that a middle-ground is needed to provide reasonably accurate travel time predictions without extensive data or computing requirements. It introduces a free, open-source minimally-congested driving time prediction model with minimal cost, data, and computational requirements. It trains and tests this model using the Los Angeles, California urban area as a case study by calculating naive travel times from open data then developing a random forest model to predict travel times as a function of those naive times plus open data on turns and traffic controls. Validation shows that this interpretable machine learning method offers a superior middle-ground technique that balances reasonable accuracy with minimal resource requirements.

physics.soc-ph↗

arXiv2025

Universal Model of Urban Street Networks

Analyzing 9,000 urban areas' street networks, we identify properties, including extreme betweenness centrality heterogeneity, that typical spatial network models fail to explain. Accordingly we propose a universal, parsimonious, generative model based on a two-step mechanism that begins with a spanning tree as a backbone then iteratively adds edges to match empirical degree distributions. Controlled by a single parameter representing lattice-equivalent node density, it accurately reproduces key universal properties to bridge the gap between empirical observations and generative models.

physics.soc-ph↗

arXiv2025

Modeling and Analyzing Urban Networks and Amenities with OSMnx

OSMnx is a Python package for downloading, modeling, analyzing, and visualizing urban networks and any other geospatial features from OpenStreetMap data. A large and growing body of literature uses it to conduct scientific studies across the disciplines of geography, urban planning, transport engineering, computer science, and others. The OSMnx project has recently developed and implemented many new features, modeling capabilities, and analytical methods. The package now encompasses substantially more functionality than was previously documented in the literature. This article introduces OSMnx's modern capabilities, usage, and design -- in addition to the scientific theory and logic underlying them. It shares lessons learned in geospatial software development and reflects on open science's implications for urban modeling and analysis.

physics.soc-ph↗

arXiv2025

Surfacic networks

Surfacic networks are structures built upon a two-dimensional manifold. Many systems, including transportation networks and various urban networks, fall into this category. The fluctuations of node elevations imply significant deviations from typical plane networks and require specific tools to understand their impact. Here, we present such tools, including lazy paths that minimize elevation differences, graph arduousness which measures the tiring nature of shortest paths, and the excess effort, which characterizes positive elevation variations along shortest paths. We illustrate these measures using toy models of surfacic networks and empirically examine pedestrian networks in selected cities. Specifically, we examine how changes in elevation affect the spatial distribution of betweenness centrality. We also demonstrate that the excess effort follows a non-trivial power law distribution, with an exponent that is not universal, which illustrates that there is a significant probability of encountering steep slopes along shortest paths, regardless of the elevation difference between the starting point and the destination. These findings highlight the significance of elevation fluctuations in shaping network characteristics. Surfacic networks offer a promising framework for comprehensively analyzing and modeling complex systems that are situated on or constrained to a surface environment.

physics.soc-ph↗

arXiv2024

A review of the structure of street networks

We review measures of street network structure proposed in the recent literature, establish their relevance to practice, and identify open challenges facing researchers. These measures' empirical values vary substantially across world regions and development eras, indicating street networks' geometric and topological heterogeneity.

physics.soc-ph↗

arXiv2024

Topological Graph Simplification Solutions to the Street Intersection Miscount Problem

Street intersection counts and densities are ubiquitous measures in transport geography and planning. However, typical street network data and typical street network analysis tools can substantially overcount them. This article explains the three main reasons why this happens and presents solutions to each. It contributes algorithms to automatically simplify spatial graphs of urban street networks -- via edge simplification and node consolidation -- resulting in faster parsimonious models and more accurate network measures like intersection counts and densities, street segment lengths, and node degrees. These algorithms' information compression improves downstream graph analytics' memory and runtime efficiency, boosting analytical tractability without loss of model fidelity. Finally, this article validates these algorithms and empirically assesses intersection count biases worldwide to demonstrate the problem's widespread prevalence. Without consolidation, traditional methods would overestimate the median urban area intersection count by 14\%. However, this bias varies drastically across regions, underscoring these algorithms' importance for consistent comparative empirical analyses.

physics.soc-ph↗

arXiv2024

Resilient by Design: Simulating Street Network Disruptions across Every Urban Area in the World

Street networks allow people and goods to move through cities, but they are vulnerable to disasters like floods, earthquakes, and terrorist attacks. Well-planned network design can make a city more resilient and robust to such disruptions, but we still know little about worldwide patterns of vulnerability, or worldwide empirical relationships between specific design characteristics and resilience. This study quantifies and measures the vulnerability of the street networks of every urban area in the world then models the relationships between vulnerability and street network design characteristics. To do so, we simulate over 2.4 billion trips across more than 8,000 urban areas in 178 countries, while also simulating network disruption events representing floods, earthquakes, and targeted attacks. We find that disrupting high-centrality nodes severely impacts network function. All else equal, networks with higher connectivity, fewer chokepoints, or less circuity are less vulnerable to disruption's impacts. This study thus contributes a new global understanding of network design and vulnerability to the literature. We argue that these design characteristics offer high leverage points for street network resilience and robustness that planners should emphasize when designing or retrofitting urban networks.

physics.soc-ph↗

arXiv2024

Urban Street Network Design and Transport-Related Greenhouse Gas Emissions around the World

This study estimates the relationships between street network characteristics and transport-sector CO2 emissions across every urban area in the world and investigates whether they are the same across development levels and urban design paradigms. The prior literature has estimated relationships between street network design and transport emissions -- including greenhouse gases implicated in climate change -- primarily through case studies focusing on certain world regions or relatively small samples of cities, complicating generalizability and applicability for evidence-informed practice. Our worldwide study finds that straighter, more-connected, and less-overbuilt street networks are associated with lower transport emissions, all else equal. Importantly, these relationships vary across development levels and design paradigms -- yet most prior literature reports findings from urban areas that are outliers by global standards. Planners need a better empirical base for evidence-informed practice in under-studied regions, particularly the rapidly urbanizing Global South.

physics.soc-ph↗

arXiv2023

Local Inequities in the Relative Production of and Exposure to Vehicular Air Pollution in Los Angeles

Vehicular air pollution has created an ongoing air quality and public health crisis. Despite growing knowledge of racial injustice in exposure levels, less is known about the relationship between the production of and exposure to such pollution. This study assesses pollution burden by testing whether local populations' vehicular air pollution exposure is proportional to how much they drive. Through a Los Angeles, California case study we examine how this relates to race, ethnicity, and socioeconomic status -- and how these relationships vary across the region. We find that, all else equal, tracts whose residents drive less are exposed to more air pollution, as are tracts with a less-White population. Commuters from majority-White tracts disproportionately drive through non-White tracts, compared to the inverse. Decades of racially-motivated freeway infrastructure planning and residential segregation shape today's disparities in who produces vehicular air pollution and who is exposed to it, but opportunities exist for urban planning and transport policy to mitigate this injustice.

stat.AP↗

arXiv2022

Using Open Data and Open-Source Software to Develop Spatial Indicators of Urban Design and Transport Features for Achieving Healthy and Sustainable Cities

Benchmarking and monitoring urban design and transport features is critical to achieving local and international health and sustainability goals. However, most urban indicator frameworks use coarse spatial scales that only allow between-city comparisons or require expensive, technical, local spatial analyses for within-city comparisons. This study developed a reusable open-source urban indicator computational framework using open data to enable consistent local and global comparative analyses. We demonstrate this framework by calculating spatial indicators - for 25 diverse cities in 19 countries - of urban design and transport features that support health and sustainability. We link these indicators to cities' policy contexts and identify populations living above and below critical thresholds for physical activity through walking. Efforts to broaden participation in crowdsourcing data and to calculate globally consistent indicators are essential for planning evidence-informed urban interventions, monitoring policy impacts, and learning lessons from peer cities to achieve health, equity, and sustainability goals.

stat.AP↗

arXiv2022

Converting One-Way Streets to Two-Way Streets to Improve Transportation Network Efficiency and Reduce Vehicle Distance Traveled

Planning scholars have identified economic, safety, and social benefits of converting one-way streets to two-way. Less is known about how conversions could impact vehicular distances traveled - of growing relevance in an era of fleet automation, electrification, and ride-hailing. We simulate such a conversion in San Francisco, California. We find that its current street network's average intra-city trip is about 1.7% longer than it would be with all two-way streets, corresponding to 27 million kilometers of annual surplus travel. As transportation technologies evolve, planners must consider different facets of network efficiency to align local policy and street design with sustainability and other societal goals.

physics.soc-ph↗

arXiv2021

Tilted Platforms: Rental Housing Technology and the Rise of Urban Big Data Oligopolies

This article interprets emerging scholarship on rental housing platforms -- particularly the most well-known and used short- and long-term rental housing platforms - and considers how the technological processes connecting both short-term and long-term rentals to the platform economy are transforming cities. It discusses potential policy approaches to more equitably distribute benefits and mitigate harms. We argue that information technology is not value-neutral. While rental housing platforms may empower data analysts and certain market participants, the same cannot be said for all users or society at large. First, user-generated online data frequently reproduce the systematic biases found in traditional sources of housing information. Evidence is growing that the information broadcasting potential of rental housing platforms may increase rather than mitigate sociospatial inequality. Second, technology platforms curate and shape information according to their creators' own financial and political interests. The question of which data -- and people -- are hidden or marginalized on these platforms is just as important as the question of which data are available. Finally, important differences in benefits and drawbacks exist between short-term and long-term rental housing platforms, but are underexplored in the literature: this article unpacks these differences and proposes policy recommendations.

econ.GN↗

arXiv2021

A Generalized Framework for Measuring Pedestrian Accessibility around the World Using Open Data

Pedestrian accessibility is an important factor in urban transport and land use policy and critical for creating healthy, sustainable cities. Developing and evaluating indicators measuring inequalities in pedestrian accessibility can help planners and policymakers benchmark and monitor the progress of city planning interventions. However, measuring and assessing indicators of urban design and transport features at high resolution worldwide to enable city comparisons is challenging due to limited availability of official, high quality, and comparable spatial data, as well as spatial analysis tools offering customizable frameworks for indicator construction and analysis. To address these challenges, this study develops an open source software framework to construct pedestrian accessibility indicators for cities using open and consistent data. It presents a generalized method to consistently measure pedestrian accessibility at high resolution and spatially aggregated scale, to allow for both within- and between-city analyses. The open source and open data methods developed in this study can be extended to other cities worldwide to support local planning and policymaking. The software is made publicly available for reuse in an open repository.

cs.CY↗

arXiv2021

Urban Analytics: History, Trajectory, and Critique

Urban analytics combines spatial analysis, statistics, computer science, and urban planning to understand and shape city futures. While it promises better policymaking insights, concerns exist around its epistemological scope and impacts on privacy, ethics, and social control. This chapter reflects on the history and trajectory of urban analytics as a scholarly and professional discipline. In particular, it considers the direction in which this field is going and whether it improves our collective and individual welfare. It first introduces early theories, models, and deductive methods from which the field originated before shifting toward induction. It then explores urban network analytics that enrich traditional representations of spatial interaction and structure. Next it discusses urban applications of spatiotemporal big data and machine learning. Finally, it argues that privacy and ethical concerns are too often ignored as ubiquitous monitoring and analytics can empower social repression. It concludes with a call for a more critical urban analytics that recognizes its epistemological limits, emphasizes human dignity, and learns from and supports marginalized communities.

cs.CY↗

arXiv2021

We Live in a Motorized Civilization: Robert Moses Replies to Robert Caro

In 1974, Robert Caro published The Power Broker, a critical biography of Robert Moses's dictatorial tenure as the "master builder" of mid-century New York. Moses profoundly transformed New York's urban fabric and transportation system, producing the Brooklyn Battery Tunnel, the Verrazano Narrows Bridge, the Westside Highway, the Cross-Bronx Expressway, the Lincoln Center, the UN headquarters, Shea Stadium, Jones Beach State Park and many other projects. However, The Power Broker did lasting damage to his public image and today he remains one of the most controversial figures in city planning history. On August 26, 1974, Moses issued a turgid 23-page statement denouncing Caro's work as "full of mistakes, unsupported charges, nasty baseless personalities, and random haymakers." Moses's original typewritten statement survives today as a grainy photocopy in the New York City Parks Department archive. To better preserve and disseminate it, I have extracted and transcribed its text using optical character recognition and edited the result to correct errors. Here I compile my transcription of Moses's statement, alongside Caro's reply to it.

econ.GN↗

arXiv2021

GIS and Computational Notebooks

Researchers and practitioners across many disciplines have recently adopted computational notebooks to develop, document, and share their scientific workflows - and the GIS community is no exception. This chapter introduces computational notebooks in the geographical context. It begins by explaining the computational paradigm and philosophy that underlie notebooks. Next it unpacks their architecture to illustrate a notebook user's typical workflow. Then it discusses the main benefits notebooks offer GIS researchers and practitioners, including better integration with modern software, more natural access to new forms of data, and better alignment with the principles and benefits of open science. In this context, it identifies notebooks as the glue that binds together a broader ecosystem of open source packages and transferable platforms for computational geography. The chapter concludes with a brief illustration of using notebooks for a set of basic GIS operations. Compared to traditional desktop GIS, notebooks can make spatial analysis more nimble, extensible, and reproducible and have thus evolved into an important component of the geospatial science toolkit.

cs.CY↗

arXiv2020

Off the Grid... and Back Again? The Recent Evolution of American Street Network Planning and Design

This morphological study identifies and measures recent nationwide trends in American street network design. Historically, orthogonal street grids provided the interconnectivity and density that researchers identify as important factors for reducing vehicular travel and emissions and increasing road safety and physical activity. During the 20th century, griddedness declined in planning practice alongside declines in urban form compactness, density, and connectivity as urbanization sprawled around automobile dependence. But less is known about comprehensive empirical trends across US neighborhoods, especially in recent years. This study uses public and open data to examine tract-level street networks across the entire US. It develops theoretical and measurement frameworks for a quality of street networks defined here as griddedness. It measures how griddedness, orientation order, straightness, 4-way intersections, and intersection density declined from 1940 through the 1990s while dead-ends and block lengths increased. However, since 2000, these trends have rebounded, shifting back toward historical design patterns. Yet, despite this rebound, when controlling for topography and built environment factors all decades post-1939 are associated with lower griddedness than pre-1940. Higher griddedness is associated with less car ownership - which itself has a well-established relationship with vehicle kilometers traveled and greenhouse gas emissions - while controlling for density, home and household size, income, jobs proximity, street network grain, and local topography. Interconnected grid-like street networks offer practitioners an important tool for curbing car dependence and emissions. Once established, street patterns determine urban spatial structure for centuries, so proactive planning is essential.

physics.soc-ph↗