Impact of the Geographic Resolution on Population Synthesis Quality

Microsimulation-based models, increasingly used in the transportation domain, require richer datasets than traditional models. Precisely enumerated population data being usually unavailable, transportation researchers generate their statistical equivalent through population synthesis. While various...

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Autores principales:	Mohamed Khachman, Catherine Morency, Francesco Ciari
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	population synthesis travel demand modelling iterative proportional fitting iterative proportional updating enhanced iterative proportional updating geographic resolution Geography (General) G1-922
Acceso en línea:	https://doaj.org/article/e39daa669de14a29b8921050e080d766
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spelling	oai:doaj.org-article:e39daa669de14a29b8921050e080d7662021-11-25T17:53:17ZImpact of the Geographic Resolution on Population Synthesis Quality10.3390/ijgi101107902220-9964https://doaj.org/article/e39daa669de14a29b8921050e080d7662021-11-01T00:00:00Zhttps://www.mdpi.com/2220-9964/10/11/790https://doaj.org/toc/2220-9964Microsimulation-based models, increasingly used in the transportation domain, require richer datasets than traditional models. Precisely enumerated population data being usually unavailable, transportation researchers generate their statistical equivalent through population synthesis. While various synthesizers are proposed to optimize the accuracy of synthetic populations, no insight is given regarding the impact of the geographic resolution on population synthesis quality. In this paper, we synthesize populations for the Census Metropolitan Areas of Montreal, Toronto, and Vancouver at various geographic resolutions using the enhanced iterative proportional updating algorithm. We define accuracy (representativeness of the sociodemographic characteristics of the entire population) and precision (representativeness of the real population’s spatial heterogeneity) as metrics of synthetic populations’ quality and measure the impact of the reference resolution on them. Moreover, we assess census targets’ harmonization and double geographic resolution control as means of quality improvement. We find that with a less aggregate reference resolution, the gain in precision is higher than the loss in accuracy. The most disaggregate resolution is thus found to be the best choice. Harmonization proves to further optimize synthetic populations while double control harms their quality. Hence, synthesizing at the Dissemination Area resolution using harmonized census targets is found to yield optimal synthetic populations.Mohamed KhachmanCatherine MorencyFrancesco CiariMDPI AGarticlepopulation synthesistravel demand modellingiterative proportional fittingiterative proportional updatingenhanced iterative proportional updatinggeographic resolutionGeography (General)G1-922ENISPRS International Journal of Geo-Information, Vol 10, Iss 790, p 790 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	population synthesis travel demand modelling iterative proportional fitting iterative proportional updating enhanced iterative proportional updating geographic resolution Geography (General) G1-922
spellingShingle	population synthesis travel demand modelling iterative proportional fitting iterative proportional updating enhanced iterative proportional updating geographic resolution Geography (General) G1-922 Mohamed Khachman Catherine Morency Francesco Ciari Impact of the Geographic Resolution on Population Synthesis Quality
description	Microsimulation-based models, increasingly used in the transportation domain, require richer datasets than traditional models. Precisely enumerated population data being usually unavailable, transportation researchers generate their statistical equivalent through population synthesis. While various synthesizers are proposed to optimize the accuracy of synthetic populations, no insight is given regarding the impact of the geographic resolution on population synthesis quality. In this paper, we synthesize populations for the Census Metropolitan Areas of Montreal, Toronto, and Vancouver at various geographic resolutions using the enhanced iterative proportional updating algorithm. We define accuracy (representativeness of the sociodemographic characteristics of the entire population) and precision (representativeness of the real population’s spatial heterogeneity) as metrics of synthetic populations’ quality and measure the impact of the reference resolution on them. Moreover, we assess census targets’ harmonization and double geographic resolution control as means of quality improvement. We find that with a less aggregate reference resolution, the gain in precision is higher than the loss in accuracy. The most disaggregate resolution is thus found to be the best choice. Harmonization proves to further optimize synthetic populations while double control harms their quality. Hence, synthesizing at the Dissemination Area resolution using harmonized census targets is found to yield optimal synthetic populations.
format	article
author	Mohamed Khachman Catherine Morency Francesco Ciari
author_facet	Mohamed Khachman Catherine Morency Francesco Ciari
author_sort	Mohamed Khachman
title	Impact of the Geographic Resolution on Population Synthesis Quality
title_short	Impact of the Geographic Resolution on Population Synthesis Quality
title_full	Impact of the Geographic Resolution on Population Synthesis Quality
title_fullStr	Impact of the Geographic Resolution on Population Synthesis Quality
title_full_unstemmed	Impact of the Geographic Resolution on Population Synthesis Quality
title_sort	impact of the geographic resolution on population synthesis quality
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/e39daa669de14a29b8921050e080d766
work_keys_str_mv	AT mohamedkhachman impactofthegeographicresolutiononpopulationsynthesisquality AT catherinemorency impactofthegeographicresolutiononpopulationsynthesisquality AT francescociari impactofthegeographicresolutiononpopulationsynthesisquality
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Impact of the Geographic Resolution on Population Synthesis Quality

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