Ensemble model for estimating continental-scale patterns of human movement: a case study of Australia

Abstract Understanding human movement patterns at local, national and international scales is critical in a range of fields, including transportation, logistics and epidemiology. Data on human movement is increasingly available, and when combined with statistical models, enables predictions of movem...

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Autores principales:	Karen McCulloch, Nick Golding, Jodie McVernon, Sarah Goodwin, Martin Tomko
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/27de64c9a8ca49e492ee3935a5ef1df6
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spelling	oai:doaj.org-article:27de64c9a8ca49e492ee3935a5ef1df62021-12-02T13:34:58ZEnsemble model for estimating continental-scale patterns of human movement: a case study of Australia10.1038/s41598-021-84198-62045-2322https://doaj.org/article/27de64c9a8ca49e492ee3935a5ef1df62021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-84198-6https://doaj.org/toc/2045-2322Abstract Understanding human movement patterns at local, national and international scales is critical in a range of fields, including transportation, logistics and epidemiology. Data on human movement is increasingly available, and when combined with statistical models, enables predictions of movement patterns across broad regions. Movement characteristics, however, strongly depend on the scale and type of movement captured for a given study. The models that have so far been proposed for human movement are best suited to specific spatial scales and types of movement. Selecting both the scale of data collection, and the appropriate model for the data remains a key challenge in predicting human movements. We used two different data sources on human movement in Australia, at different spatial scales, to train a range of statistical movement models and evaluate their ability to predict movement patterns for each data type and scale. Whilst the five commonly-used movement models we evaluated varied markedly between datasets in their predictive ability, we show that an ensemble modelling approach that combines the predictions of these models consistently outperformed all individual models against hold-out data.Karen McCullochNick GoldingJodie McVernonSarah GoodwinMartin TomkoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Karen McCulloch Nick Golding Jodie McVernon Sarah Goodwin Martin Tomko Ensemble model for estimating continental-scale patterns of human movement: a case study of Australia
description	Abstract Understanding human movement patterns at local, national and international scales is critical in a range of fields, including transportation, logistics and epidemiology. Data on human movement is increasingly available, and when combined with statistical models, enables predictions of movement patterns across broad regions. Movement characteristics, however, strongly depend on the scale and type of movement captured for a given study. The models that have so far been proposed for human movement are best suited to specific spatial scales and types of movement. Selecting both the scale of data collection, and the appropriate model for the data remains a key challenge in predicting human movements. We used two different data sources on human movement in Australia, at different spatial scales, to train a range of statistical movement models and evaluate their ability to predict movement patterns for each data type and scale. Whilst the five commonly-used movement models we evaluated varied markedly between datasets in their predictive ability, we show that an ensemble modelling approach that combines the predictions of these models consistently outperformed all individual models against hold-out data.
format	article
author	Karen McCulloch Nick Golding Jodie McVernon Sarah Goodwin Martin Tomko
author_facet	Karen McCulloch Nick Golding Jodie McVernon Sarah Goodwin Martin Tomko
author_sort	Karen McCulloch
title	Ensemble model for estimating continental-scale patterns of human movement: a case study of Australia
title_short	Ensemble model for estimating continental-scale patterns of human movement: a case study of Australia
title_full	Ensemble model for estimating continental-scale patterns of human movement: a case study of Australia
title_fullStr	Ensemble model for estimating continental-scale patterns of human movement: a case study of Australia
title_full_unstemmed	Ensemble model for estimating continental-scale patterns of human movement: a case study of Australia
title_sort	ensemble model for estimating continental-scale patterns of human movement: a case study of australia
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/27de64c9a8ca49e492ee3935a5ef1df6
work_keys_str_mv	AT karenmcculloch ensemblemodelforestimatingcontinentalscalepatternsofhumanmovementacasestudyofaustralia AT nickgolding ensemblemodelforestimatingcontinentalscalepatternsofhumanmovementacasestudyofaustralia AT jodiemcvernon ensemblemodelforestimatingcontinentalscalepatternsofhumanmovementacasestudyofaustralia AT sarahgoodwin ensemblemodelforestimatingcontinentalscalepatternsofhumanmovementacasestudyofaustralia AT martintomko ensemblemodelforestimatingcontinentalscalepatternsofhumanmovementacasestudyofaustralia
_version_	1718392723548930048

Ensemble model for estimating continental-scale patterns of human movement: a case study of Australia

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