TY - JOUR
T1 - Effects of seasonal environment changes on greenway use intensity
T2 - Evidence from the Huangpu River waterfront greenway in Shanghai, China
AU - Hu, Xinyu
AU - Cao, Kai
AU - Kwan, Mei Po
N1 - Publisher Copyright:
© 2025 Elsevier GmbH.
PY - 2026/3
Y1 - 2026/3
N2 - The use intensity of urban greenways is significantly influenced by seasonal environmental fluctuations, which have been frequently overlooked in previous studies yet hold great importance for urban planning. This study bridges this critical gap by proposing a comprehensive analytical framework that combines both built environment and micro environment factors to evaluate seasonal variations in greenway use intensity. Specifically, the framework incorporates street view images captured via wearable GoPro cameras across all four seasons. Through the random forest regression models, the study analyzed how seasonal shifts influence greenway use intensity. The results indicate that while the impact of built environment factors accounts for more than half of the weight on greenway use intensity, seasonal factors still make a significant contribution, emphasizing their secondary but substantial impact. Moreover, the results also reveal a distinct seasonal pattern in the determinants of greenway use intensity. In summer, the sky view factor is the dominant influential factor, whereas in winter, the focus shifts to POIs. The patterns of the sky view factor and the green view index on greenway usage varied significantly across seasons, while the effects of most other variables remained consistent across seasons. By considering the dynamic interplay between built and seasonal environmental variables, this study advocates for a more adaptive and responsive approach to urban greenway planning and design.
AB - The use intensity of urban greenways is significantly influenced by seasonal environmental fluctuations, which have been frequently overlooked in previous studies yet hold great importance for urban planning. This study bridges this critical gap by proposing a comprehensive analytical framework that combines both built environment and micro environment factors to evaluate seasonal variations in greenway use intensity. Specifically, the framework incorporates street view images captured via wearable GoPro cameras across all four seasons. Through the random forest regression models, the study analyzed how seasonal shifts influence greenway use intensity. The results indicate that while the impact of built environment factors accounts for more than half of the weight on greenway use intensity, seasonal factors still make a significant contribution, emphasizing their secondary but substantial impact. Moreover, the results also reveal a distinct seasonal pattern in the determinants of greenway use intensity. In summer, the sky view factor is the dominant influential factor, whereas in winter, the focus shifts to POIs. The patterns of the sky view factor and the green view index on greenway usage varied significantly across seasons, while the effects of most other variables remained consistent across seasons. By considering the dynamic interplay between built and seasonal environmental variables, this study advocates for a more adaptive and responsive approach to urban greenway planning and design.
KW - Greenway
KW - Seasonal change
KW - Street view images
KW - Use intensity
UR - https://www.scopus.com/pages/publications/105026196131
U2 - 10.1016/j.ufug.2025.129245
DO - 10.1016/j.ufug.2025.129245
M3 - 文章
AN - SCOPUS:105026196131
SN - 1618-8667
VL - 117
JO - Urban Forestry and Urban Greening
JF - Urban Forestry and Urban Greening
M1 - 129245
ER -