Encouraging cycling through the improvement of streetscape perception
A bottom-up investigation into the relationship between street greening and bicycling volume
Dados Bibliográficos
| ID | 21450054 |
|---|---|
| Autores | Qiao Zhang (0000-0002-7752-0528), 喬森 張 (0009-0006-8884-1411, Beijing Forestry University, autor correspondente), Jin Rui (0000-0002-0926-0947, TU Dortmund University), Yufei Wu (0009-0009-6733-3196, Beijing Forestry University) |
| Ano | 2024 |
| Volume | 171 |
| Páginas | 103388 |
| Data de publicação | 2024-10-01 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Applied Geography (JOURNAL) |
| Identificadores do periódico | ISSN: 0143-6228 • E-ISSN: 1873-7730 |
| Editora | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.apgeog.2024.103388 |
| OpenAlex | W4401894927 |
| Idioma | EN |
| Citações recebidas | 4 |
| Referências citadas | 43 |
Archaeology · Biology · Cycling · Environmental planning · Geography · Greening · Perception · Transport engineering · Ecology · Engineering · Impact of Light on Environment and Health · Psychology · Urban Green Space and Health · Urban Transport and Accessibility
Embodied Intelligent Perception for Human-Centered Design in the Built Environment
Understanding environmental factors affecting cyclists' perceptions in high-density neighborhoods using street view imagery
Exploring the impact of objective features and subjective perceptions of street environment on cycling preferences
Marginalized but equal? An investigation of visible green equity disparities in marginalized residents' daily commutes and its potential green solutions
Developing and testing a street audit tool using Google Street View to measure environmental supportiveness for physical activity
Mapping sky, tree, and building view factors of street canyons in a high-density urban environment
Notes on Continuous Stochastic Phenomena
Google Street View
Using Google Street View to investigate the association between street greenery and physical activity
Perceived Neighborhood Environmental Attributes Associated with Walking and Cycling for Transport among Adult Residents of 17 Cities in 12 Countries
Measuring the Unmeasurable
Measuring daily accessed street greenery
Random Forests
Geographically Weighted Regression
Assessing Street Space Quality Using Street View Imagery and Function-Driven Method
Assessing impacts of objective features and subjective perceptions of street environment on running amount
Analyzing the effects of Green View Index of neighborhood streets on walking time using Google Street View and deep learning
Relationship between eye-level greenness and cycling frequency around metro stations in Shenzhen, China
The distribution of greenspace quantity and quality and their association with neighbourhood socioeconomic conditions in Guangzhou, China
Using street view images to examine the association between human perceptions of locale and urban vitality in Shenzhen, China
Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice
A Systematic Measurement of Street Quality through Multi-Sourced Urban Data
How Green Are the Streets Within the Sixth Ring Road of Beijing? An Analysis Based on Tencent Street View Pictures and the Green View Index
Longitudinal effects of urban green space on walking and cycling
Objective scoring of streetscape walkability related to leisure walking
The inequalities of different dimensions of visible street urban green space provision
Measuring human perceptions of streetscapes to better inform urban renewal
Associations between overhead-view and eye-level urban greenness and cycling behaviors
Automatic assessment of public open spaces using street view imagery
Measuring streetscape perceptions from driveways and sidewalks to inform pedestrian-oriented street renewal in Düsseldorf
Can Likert Scales be Treated as Interval Scales?—A Simulation Study
Evaluation methods for landscapes with greenery
Local Indicators of Spatial Association—Lisa
| Obras citantes distintas | 4 |
|---|---|
| Citações por ano | 4 |
| Intervalo de citações | 2025 - 2026 (2) |
| Velocidade de citação | current |
| Altamente citado | Não |
| Tipos de citação | Neutras: 3 |