Diagnosing the performance of human mobility models at small spatial scales using volunteered geographical information
Accurate modelling of local population movement patterns is a core, contemporary concern for urban policymakers, affecting both the short-term deployment of public transport resources and the longer-term planning of transport infrastructure. Yet, while macro-level population movement models (such as...
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Format: | Article |
Language: | English |
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The Royal Society
2019-11-01
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Series: | Royal Society Open Science |
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Online Access: | https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.191034 |
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author | Chico Q. Camargo Jonathan Bright Scott A. Hale |
author_facet | Chico Q. Camargo Jonathan Bright Scott A. Hale |
author_sort | Chico Q. Camargo |
collection | DOAJ |
description | Accurate modelling of local population movement patterns is a core, contemporary concern for urban policymakers, affecting both the short-term deployment of public transport resources and the longer-term planning of transport infrastructure. Yet, while macro-level population movement models (such as the gravity and radiation models) are well developed, micro-level alternatives are in much shorter supply, with most macro-models known to perform poorly at smaller geographical scales. In this paper, we take a first step to remedy this deficit, by leveraging two novel datasets to analyse where and why macro-level models of human mobility break down. We show how freely available data from OpenStreetMap concerning land use composition of different areas around the county of Oxfordshire in the UK can be used to diagnose mobility models and understand the types of trips they over- and underestimate when compared with empirical volumes derived from aggregated, anonymous smartphone location data. We argue for new modelling strategies that move beyond rough heuristics such as distance and population towards a detailed, granular understanding of the opportunities presented in different regions. |
first_indexed | 2024-12-13T15:53:22Z |
format | Article |
id | doaj.art-8aaf548419734601934b0f945880c345 |
institution | Directory Open Access Journal |
issn | 2054-5703 |
language | English |
last_indexed | 2024-12-13T15:53:22Z |
publishDate | 2019-11-01 |
publisher | The Royal Society |
record_format | Article |
series | Royal Society Open Science |
spelling | doaj.art-8aaf548419734601934b0f945880c3452022-12-21T23:39:23ZengThe Royal SocietyRoyal Society Open Science2054-57032019-11-0161110.1098/rsos.191034191034Diagnosing the performance of human mobility models at small spatial scales using volunteered geographical informationChico Q. CamargoJonathan BrightScott A. HaleAccurate modelling of local population movement patterns is a core, contemporary concern for urban policymakers, affecting both the short-term deployment of public transport resources and the longer-term planning of transport infrastructure. Yet, while macro-level population movement models (such as the gravity and radiation models) are well developed, micro-level alternatives are in much shorter supply, with most macro-models known to perform poorly at smaller geographical scales. In this paper, we take a first step to remedy this deficit, by leveraging two novel datasets to analyse where and why macro-level models of human mobility break down. We show how freely available data from OpenStreetMap concerning land use composition of different areas around the county of Oxfordshire in the UK can be used to diagnose mobility models and understand the types of trips they over- and underestimate when compared with empirical volumes derived from aggregated, anonymous smartphone location data. We argue for new modelling strategies that move beyond rough heuristics such as distance and population towards a detailed, granular understanding of the opportunities presented in different regions.https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.191034human mobilitytraffic modelsland useopen dataopenstreetmap |
spellingShingle | Chico Q. Camargo Jonathan Bright Scott A. Hale Diagnosing the performance of human mobility models at small spatial scales using volunteered geographical information Royal Society Open Science human mobility traffic models land use open data openstreetmap |
title | Diagnosing the performance of human mobility models at small spatial scales using volunteered geographical information |
title_full | Diagnosing the performance of human mobility models at small spatial scales using volunteered geographical information |
title_fullStr | Diagnosing the performance of human mobility models at small spatial scales using volunteered geographical information |
title_full_unstemmed | Diagnosing the performance of human mobility models at small spatial scales using volunteered geographical information |
title_short | Diagnosing the performance of human mobility models at small spatial scales using volunteered geographical information |
title_sort | diagnosing the performance of human mobility models at small spatial scales using volunteered geographical information |
topic | human mobility traffic models land use open data openstreetmap |
url | https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.191034 |
work_keys_str_mv | AT chicoqcamargo diagnosingtheperformanceofhumanmobilitymodelsatsmallspatialscalesusingvolunteeredgeographicalinformation AT jonathanbright diagnosingtheperformanceofhumanmobilitymodelsatsmallspatialscalesusingvolunteeredgeographicalinformation AT scottahale diagnosingtheperformanceofhumanmobilitymodelsatsmallspatialscalesusingvolunteeredgeographicalinformation |