An open software environment to make spatial access metrics more accessible

Koschinsky, Julia; Acosta, Karina; Anguiano, Vidal; Anselin, Luc; Rey, Sergio J.

doi:10.1007/s42001-021-00126-8

Cited by 22 publications

(9 citation statements)

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“…Pandana (Foti et al, 2012; Pandana, 2021) is a Python library that enables to compute the accessibility of places by retrieving points of interest and street network data from OpenStreetMap (OpenStreetMap contributors, 2017b) and by efficiently computing shortest paths along the street network. Access (Saxon et al, 2021) is a Python library that computes a wide range of spatial accessibility metrics given as input a set of origins and destinations, as well as travel times or distances between them. Built on top of Pandana , UrbanAccess (Blanchard and Waddell, 2017) integrates the creation of multimodal transport networks (transit and pedestrian) using GTFS data and the computation of accessibility metrics.…”

Section: Open Data and Toolsmentioning

confidence: 99%

Multimodal urban mobility and multilayer transport networks

Orozco

Alessandretti

Saberi

et al. 2022

Environment and Planning B: Urban Analytics and City Science

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Transportation networks, from bicycle paths to buses and railways, are the backbone of urban mobility. In large metropolitan areas, the integration of different transport modes has become crucial to guarantee the fast and sustainable flow of people. Using a network science approach, multimodal transport systems can be described as multilayer networks, where the networks associated to different transport modes are not considered in isolation, but as a set of interconnected layers. Despite the importance of multimodality in modern cities, a unified view of the topic is currently missing. Here, we provide a comprehensive overview of the emerging research areas of multilayer transport networks and multimodal urban mobility, focusing on contributions from the interdisciplinary fields of complex systems, urban data science, and science of cities. First, we present an introduction to the mathematical framework of multilayer networks. We apply it to survey models of multimodal infrastructures, as well as measures used for quantifying multimodality, and related empirical findings. We review modeling approaches and observational evidence in multimodal mobility and public transport system dynamics, focusing on integrated real-world mobility patterns, where individuals navigate urban systems using different transport modes. We then provide a survey of freely available datasets on multimodal infrastructure and mobility, and a list of open-source tools for their analyses. Finally, we conclude with an outlook on open research questions and promising directions for future research.

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Section: Open Data and Toolsmentioning

confidence: 99%

Multimodal urban mobility and multilayer transport networks

Orozco

Alessandretti

Saberi

et al. 2022

Environment and Planning B: Urban Analytics and City Science

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“…In line with the increase in the number of open-source tools available for transportation planning (Lovelace, 2021), there are a variety of routing engines that can be used for accessibility analysis. This includes unimodal (e.g., 'gtfsrouter' (Padgham et al, 2021)) and multimodal (e.g., 'UrbanAccess' (Blanchard & Waddell, 2017)), 'osrm' (Huber & Rust, 2016), GraphHopper, and the 'access' (Saxon et al, 2021) Several constraints limited our ability to consider all these tools. First, several were not publicly available when this analysis began in December 2019.…”

Section: Assessment Of Place-based Accessibility Toolsmentioning

confidence: 99%

Calculating place-based transit accessibility: Methods, tools and algorithmic dependence

Higgins

Palm

DeJohn

et al. 2022

JTLU

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To capture the complex relationships between transportation and land use, researchers and practitioners are increasingly using place-based measures of transportation accessibility to support a broad range of planning goals. This research reviews the state-of-the-art in applied transportation accessibility measurement and performs a comparative evaluation of software tools for calculating accessibility by walking and public transit including ArcGIS Pro, Emme, R5R, and OpenTripPlanner using R and Python, among others. Using a case study of Toronto, we specify both origin-based and regional-scale analysis scenarios and find significant differences in computation time and calculated accessibilities. While the calculated travel time matrices are highly correlated across tools, each tool produces different results for the same origin-destination pair. Comparisons of the estimated accessibilities also reveal evidence of spatial clustering in the ways paths are calculated by some tools relative to others at different locations around the city. With the growing emphasis on accessibility-based planning, analysts should approach the calculation of accessibility with care and recognize the potential for algorithmic dependence in their calculated accessibility results.

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“…Pandana [118,119] is a Python library that enables to compute the accessibility of places by retrieving points of interest and street network data from OpenStreetMap [120] and by efficiently computing shortest paths along the street network. Access [121] is a Python library that computes a wide range of spatial accessibility metrics from a set of origins and destinations, and travel times or distances between them. Built on top of Pandana, UrbanAccess [122] integrates the creation of multi-modal transport networks (transit and pedestrian) using GTFS data and the computation of accessibility metrics.…”

Section: Tools For Routing or Access On Transport Networkmentioning

confidence: 99%

Urban Mobility

Alessandretti¹,

Szell²

2022

Preprint

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In this chapter, we discuss urban mobility from a complexity science perspective. First, we give an overview of the datasets that enable this approach, such as mobile phone records, location-based social network traces, or GPS trajectories from sensors installed on vehicles. We then review the empirical and theoretical understanding of the properties of human movements, including the distribution of travel distances and times, the entropy of trajectories, and the interplay between exploration and exploitation of locations. Next, we explain generative and predictive models of individual mobility, and their limitations due to intrinsic limits of predictability. Finally, we discuss urban transport from a systemic perspective, including system-wide challenges like ridesharing, multimodality, and sustainable transport.

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An open software environment to make spatial access metrics more accessible

Cited by 22 publications

References 50 publications

Multimodal urban mobility and multilayer transport networks

Multimodal urban mobility and multilayer transport networks

Calculating place-based transit accessibility: Methods, tools and algorithmic dependence

Urban Mobility

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