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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Main Authors: Chico Q. Camargo, Jonathan Bright, Scott A. Hale
Format: Article
Language:English
Published: The Royal Society 2019-11-01
Series:Royal Society Open Science
Subjects:
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.
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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