Extending Processing Toolbox for assessing the logical consistency of OpenStreetMap data

Sehra, Sukhjit Singh; Singh, Jaiteg; Singh, Hardeep; Anand, Sarabjot Singh

doi:10.1111/tgis.12587

Cited by 23 publications

(8 citation statements)

References 64 publications

(126 reference statements)

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“…OSM destination and edge validation comprises a quantitative analysis to compare OSM-derived data against available local official data for evaluating the data quality, representation, and suitability for indicator calculation. In this process, the proportion of overlap between the OSMderived dataset (i.e., edges and destinations) and official dataset within 10-and 50-m buffer are Walkability index (sum of z-scores of population density, intersection density and daily living score) Between city, spatial average … all_cities_z_nh_population_density Local neighborhood population per square kilometer (z-score relative to all cities) all_cities_z_nh_intersection_density Local neighborhood intersections per square kilometer (z-score relative to all cities) all_cities_z_daily_living Daily living score (z-score relative to all cities) all_cities_walkability Walkability index (sum of z-scores relative to all cities) first evaluated, in line with other studies that address road networks' representation with specific thresholds (Sehra et al, 2020). Second, a suitability analysis is conducted to evaluate the accessibility method (i.e., hexagon grid validation), which does not distinguish between hexagon neighborhoods that have one destination or ten destinations: in either scenario, there is access to at least one destination.…”

Section: Osm Destination and Edge Validationsupporting

confidence: 62%

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

Liu

Higgs

Arundel

et al. 2021

Geographical Analysis

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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.

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Section: Osm Destination and Edge Validationsupporting

confidence: 62%

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

Liu

Higgs

Arundel

et al. 2021

Geographical Analysis

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“…One can query its database for street and intersection geometry data, along with attribute data about road types, names, and (when available) speeds, widths, and numbers of lanes (Jokar Arsanjani et al, 2015;Maier, 2014). It offers good global coverage and high geometric and topological data quality (Girres and Touya, 2010;Haklay, 2010;Corcoran et al, 2013;Zielstra et al, 2013;Barron et al, 2014;Basiri et al, 2016;Sehra et al, 2019). OpenStreetMap has more than 1 million contributors who have added over 6 billion nodes (points), 600 million ways (lines and boundaries), and attendant attribute data to its database.…”

Section: Global Street Network Datamentioning

confidence: 99%

Street Network Models and Indicators for Every Urban Area in the World

Boeing

2020

Preprint

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Cities worldwide exhibit a variety of street network patterns and configurations that shape human mobility, equity, health, and livelihoods. This study models and analyzes the street networks of each urban area in the world, using boundaries derived from the Global Human Settlement Layer. Street network data are acquired and modeled using the open-source OSMnx software and OpenStreetMap. In total, this study models over 150 million OpenStreetMap street network nodes and over 300 million edges across 9,000 urban areas in 178 countries. This paper presents the study's reproducible computational workflow, introduces two new open data repositories of processed global street network models and calculated indicators, and reports summary descriptive findings on street network form worldwide. It makes four contributions. First, it reports the methodological advances of using this open-source tool in spatial network modeling and analyses with open big data. Second, it produces an open data repository containing street network models for each of these urban areas, in various file formats, for public reuse. Third, it analyzes these models to produce an open data repository containing dozens of street network form indicators for each urban area. No such global urban street network indicator data set has previously existed. Fourth, it presents an aggregate summary descriptive analysis of global street network form at the scale of the urban area, reporting the first such worldwide results in the literature.

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“…One can query its database for street and intersection data, along with attribute data about road types, names, and (when available) speeds, widths, and numbers of lanes. It offers good global coverage and high geometric and topological data quality (Girres and Touya 2010; Haklay 2010; Corcoran, Mooney, and Bertolotto 2013; Zielstra, Hochmair, and Neis 2013; Barron, Neis, and Zipf 2014; Maier 2014; Basiri et al 2016; Sehra et al 2020). Barrington‐Leigh and Millard‐Ball (2017) found that, as of 2016, OpenStreetMap was 83% complete worldwide, over 40% of countries’ (including many developing countries) street networks were effectively 100% complete, and completeness was highest in both dense cities and sparsely populated areas.…”

Section: Introductionmentioning

confidence: 99%

Street Network Models and Indicators for Every Urban Area in the World

Boeing

2021

Geographical Analysis

View full text Add to dashboard Cite

Cities worldwide exhibit a variety of street network patterns and configurations that shape human mobility, equity, health, and livelihoods. This study models and analyzes the street networks of every urban area in the world, using boundaries derived from the Global Human Settlement Layer. Street network data are acquired and modeled from OpenStreetMap with the open‐source OSMnx software. In total, this study models over 160 million OpenStreetMap street network nodes and over 320 million edges across 8,914 urban areas in 178 countries, and attaches elevation and grade data. This article presents the study’s reproducible computational workflow, introduces two new open data repositories of ready‐to‐use global street network models and calculated indicators, and discusses summary findings on street network form worldwide. It makes four contributions. First, it reports the methodological advances of this open‐source workflow. Second, it produces an open data repository containing street network models for each urban area. Third, it analyzes these models to produce an open data repository containing street network form indicators for each urban area. No such global urban street network indicator data set has previously existed. Fourth, it presents a summary analysis of urban street network form, reporting the first such worldwide results in the literature.

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Extending Processing Toolbox for assessing the logical consistency of OpenStreetMap data

Cited by 23 publications

References 64 publications

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

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

Street Network Models and Indicators for Every Urban Area in the World

Street Network Models and Indicators for Every Urban Area in the World

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