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- Publisher Website: 10.1016/j.landurbplan.2023.104879
- Scopus: eid_2-s2.0-85169928602
- WOS: WOS:001091432600001
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Article: Understanding the effects of environmental perceptions on walking behavior by integrating big data with small data
Title | Understanding the effects of environmental perceptions on walking behavior by integrating big data with small data |
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Authors | |
Keywords | Big and small data Mobile phone data Objective and perceived built environment Urban planning and design Walking behavior |
Issue Date | 1-Dec-2023 |
Publisher | Elsevier |
Citation | Landscape and Urban Planning, 2023, v. 240 How to Cite? |
Abstract | Human-perceived landscape and amenities are not equivalent to the objective physical world. Traditional big data research that only uses objectively measured environments based on point-of-interest data has difficulty capturing the effect of human environmental perceptions on walking behavior. We proposed a conceptual framework to examine the effect of human perception on walking behavior by integrating travel trajectories from the “big data” derived from mobile phones and “small data” obtained from a questionnaire survey of residents living in Chengdu, China. Results show that the human subjective perceived environment is inconsistent with the objectively measured built environment. The walking behavior of individuals is completely regulated by their personal perception of the surrounding environment. Moreover, enhancing the environmental design of pathways leading to retail shops, recreational areas, and shopping centers could significantly enhance perceived accessibility and foster a more pedestrian-friendly neighborhood. |
Persistent Identifier | http://hdl.handle.net/10722/337968 |
ISSN | 2023 Impact Factor: 7.9 2023 SCImago Journal Rankings: 2.358 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Qiao, Si | - |
dc.contributor.author | Yeh, Gar-On Anthony | - |
dc.date.accessioned | 2024-03-11T10:25:16Z | - |
dc.date.available | 2024-03-11T10:25:16Z | - |
dc.date.issued | 2023-12-01 | - |
dc.identifier.citation | Landscape and Urban Planning, 2023, v. 240 | - |
dc.identifier.issn | 0169-2046 | - |
dc.identifier.uri | http://hdl.handle.net/10722/337968 | - |
dc.description.abstract | <p>Human-perceived landscape and amenities are not equivalent to the objective physical world. Traditional big data research that only uses objectively measured environments based on point-of-interest data has difficulty capturing the effect of human environmental perceptions on walking behavior. We proposed a conceptual framework to examine the effect of human perception on walking behavior by integrating travel trajectories from the “big data” derived from mobile phones and “small data” obtained from a questionnaire survey of residents living in Chengdu, China. Results show that the human subjective perceived environment is inconsistent with the objectively measured built environment. The walking behavior of individuals is completely regulated by their personal perception of the surrounding environment. Moreover, enhancing the environmental design of pathways leading to retail shops, recreational areas, and shopping centers could significantly enhance perceived accessibility and foster a more pedestrian-friendly neighborhood.</p> | - |
dc.language | eng | - |
dc.publisher | Elsevier | - |
dc.relation.ispartof | Landscape and Urban Planning | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Big and small data | - |
dc.subject | Mobile phone data | - |
dc.subject | Objective and perceived built environment | - |
dc.subject | Urban planning and design | - |
dc.subject | Walking behavior | - |
dc.title | Understanding the effects of environmental perceptions on walking behavior by integrating big data with small data | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.landurbplan.2023.104879 | - |
dc.identifier.scopus | eid_2-s2.0-85169928602 | - |
dc.identifier.volume | 240 | - |
dc.identifier.eissn | 1872-6062 | - |
dc.identifier.isi | WOS:001091432600001 | - |
dc.identifier.issnl | 0169-2046 | - |