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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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/10/11/790 |
| _version_ | 1797510113501642752 |
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| author | Mohamed Khachman Catherine Morency Francesco Ciari |
| author_facet | Mohamed Khachman Catherine Morency Francesco Ciari |
| author_sort | Mohamed Khachman |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T05:27:03Z |
| format | Article |
| id | doaj.art-e39daa669de14a29b8921050e080d766 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T05:27:03Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-e39daa669de14a29b8921050e080d7662023-11-22T23:36:53ZengMDPI AGISPRS International Journal of Geo-Information2220-99642021-11-01101179010.3390/ijgi10110790Impact of the Geographic Resolution on Population Synthesis QualityMohamed Khachman0Catherine Morency1Francesco Ciari2Department of Civil, Geological and Mining Engineering, Polytechnique Montréal, C.P. 6079, Station Centre-Ville, Montreal, QC H3C 3A7, CanadaDepartment of Civil, Geological and Mining Engineering, Polytechnique Montréal, C.P. 6079, Station Centre-Ville, Montreal, QC H3C 3A7, CanadaDepartment of Civil, Geological and Mining Engineering, Polytechnique Montréal, C.P. 6079, Station Centre-Ville, Montreal, QC H3C 3A7, CanadaMicrosimulation-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.https://www.mdpi.com/2220-9964/10/11/790population synthesistravel demand modellingiterative proportional fittingiterative proportional updatingenhanced iterative proportional updatinggeographic resolution |
| spellingShingle | Mohamed Khachman Catherine Morency Francesco Ciari Impact of the Geographic Resolution on Population Synthesis Quality ISPRS International Journal of Geo-Information population synthesis travel demand modelling iterative proportional fitting iterative proportional updating enhanced iterative proportional updating geographic resolution |
| title | 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_short | Impact of the Geographic Resolution on Population Synthesis Quality |
| title_sort | impact of the geographic resolution on population synthesis quality |
| topic | population synthesis travel demand modelling iterative proportional fitting iterative proportional updating enhanced iterative proportional updating geographic resolution |
| url | https://www.mdpi.com/2220-9964/10/11/790 |
| work_keys_str_mv | AT mohamedkhachman impactofthegeographicresolutiononpopulationsynthesisquality AT catherinemorency impactofthegeographicresolutiononpopulationsynthesisquality AT francescociari impactofthegeographicresolutiononpopulationsynthesisquality |