We shape our buildings, but do they then shape us? A longitudinal analysis of pedestrian flows and development activity in Melbourne
Cities are increasingly promoting walkability to tackle climate change, improve urban quality of life, and address socioeconomic inequities that auto-oriented development tends to exacerbate, prompting a need for predictive pedestrian flow models. This paper implements a novel network-based pedestri...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2021
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| Online Access: | https://hdl.handle.net/1721.1/132932 |
| _version_ | 1811081676792528896 |
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| author | Sevtsuk, Andres Basu, Rounaq Chancey, Bahij |
| author2 | Massachusetts Institute of Technology. Department of Urban Studies and Planning |
| author_facet | Massachusetts Institute of Technology. Department of Urban Studies and Planning Sevtsuk, Andres Basu, Rounaq Chancey, Bahij |
| author_sort | Sevtsuk, Andres |
| collection | MIT |
| description | Cities are increasingly promoting walkability to tackle climate change, improve urban quality of life, and address socioeconomic inequities that auto-oriented development tends to exacerbate, prompting a need for predictive pedestrian flow models. This paper implements a novel network-based pedestrian flow model at a property-level resolution in the City of Melbourne. Data on Melbourne’s urban form, land-uses, amenities, and pedestrian walkways as well as weather conditions are used to predict pedestrian flows between different land-use pairs, which are subsequently calibrated against hourly observed pedestrian counts from automated sensors. Calibration allows the model extrapolate pedestrian flows on all streets throughout the city center based on reliable baseline observations, and to forecast how new development projects will change existing pedestrian flows. Longitudinal data availability also allows us to validate how accurate such predictions are by comparing model results to actual pedestrian counts observed in following years. Updating the built-environment data annually, we (1) test the accuracy of different calibration techniques for predicting foot-traffic on the city’s streets in subsequent years; (2) assess how changes in the built environment affect changes in foot-traffic; (3) analyze which pedestrian origin-destination flows explain observed foot-traffic during three peak weekday periods; and (4) assess the stability of model predictions over time. We find that annual changes in the built environment have a significant and measurable impact on the spatial distribution of Melbourne’s pedestrian flows. We hope this novel framework can be used by planners to implement “pedestrian impact assessments” for newly planned developments, which can complement traditional vehicular “traffic impact assessments”. |
| first_indexed | 2024-09-23T11:50:39Z |
| format | Article |
| id | mit-1721.1/132932 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T11:50:39Z |
| publishDate | 2021 |
| publisher | Public Library of Science (PLoS) |
| record_format | dspace |
| spelling | mit-1721.1/1329322024-06-05T20:31:18Z We shape our buildings, but do they then shape us? A longitudinal analysis of pedestrian flows and development activity in Melbourne Sevtsuk, Andres Basu, Rounaq Chancey, Bahij Massachusetts Institute of Technology. Department of Urban Studies and Planning Cities are increasingly promoting walkability to tackle climate change, improve urban quality of life, and address socioeconomic inequities that auto-oriented development tends to exacerbate, prompting a need for predictive pedestrian flow models. This paper implements a novel network-based pedestrian flow model at a property-level resolution in the City of Melbourne. Data on Melbourne’s urban form, land-uses, amenities, and pedestrian walkways as well as weather conditions are used to predict pedestrian flows between different land-use pairs, which are subsequently calibrated against hourly observed pedestrian counts from automated sensors. Calibration allows the model extrapolate pedestrian flows on all streets throughout the city center based on reliable baseline observations, and to forecast how new development projects will change existing pedestrian flows. Longitudinal data availability also allows us to validate how accurate such predictions are by comparing model results to actual pedestrian counts observed in following years. Updating the built-environment data annually, we (1) test the accuracy of different calibration techniques for predicting foot-traffic on the city’s streets in subsequent years; (2) assess how changes in the built environment affect changes in foot-traffic; (3) analyze which pedestrian origin-destination flows explain observed foot-traffic during three peak weekday periods; and (4) assess the stability of model predictions over time. We find that annual changes in the built environment have a significant and measurable impact on the spatial distribution of Melbourne’s pedestrian flows. We hope this novel framework can be used by planners to implement “pedestrian impact assessments” for newly planned developments, which can complement traditional vehicular “traffic impact assessments”. 2021-10-12T18:18:04Z 2021-10-12T18:18:04Z 2021-08 2020-11 2021-10-12T12:29:39Z Article http://purl.org/eprint/type/JournalArticle 1932-6203 https://hdl.handle.net/1721.1/132932 Sevtsuk A, Basu R, Chancey B (2021) We shape our buildings, but do they then shape us? A longitudinal analysis of pedestrian flows and development activity in Melbourne. PLoS ONE 16(9): e0257534 en 10.1371/journal.pone.0257534 PLOS ONE Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Public Library of Science (PLoS) PLoS |
| spellingShingle | Sevtsuk, Andres Basu, Rounaq Chancey, Bahij We shape our buildings, but do they then shape us? A longitudinal analysis of pedestrian flows and development activity in Melbourne |
| title | We shape our buildings, but do they then shape us? A longitudinal analysis of pedestrian flows and development activity in Melbourne |
| title_full | We shape our buildings, but do they then shape us? A longitudinal analysis of pedestrian flows and development activity in Melbourne |
| title_fullStr | We shape our buildings, but do they then shape us? A longitudinal analysis of pedestrian flows and development activity in Melbourne |
| title_full_unstemmed | We shape our buildings, but do they then shape us? A longitudinal analysis of pedestrian flows and development activity in Melbourne |
| title_short | We shape our buildings, but do they then shape us? A longitudinal analysis of pedestrian flows and development activity in Melbourne |
| title_sort | we shape our buildings but do they then shape us a longitudinal analysis of pedestrian flows and development activity in melbourne |
| url | https://hdl.handle.net/1721.1/132932 |
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