Assessing the nonlinear impact of green space exposure on psychological stress perception using machine learning and street view images.

Journal: Frontiers in public health

PMID: 39360258

Abstract

INTRODUCTION: Urban green space (GS) exposure is recognized as a nature-based strategy for addressing urban challenges. However, the stress relieving effects and mechanisms of GS exposure are yet to be fully explored. The development of machine learning and street view images offers a method for large-scale measurement and precise empirical analysis.

Authors

Tianlin Zhang

School of Computer Science and Technology, University of Chinese Academy of Sciences, China.
Lei Wang

Department of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Yazhuo Zhang

School of Civil Engineering, Tianjin University, Tianjin, China.
Yike Hu

School of Architecture, Tianjin University, Tianjin, China.
Wenzheng Zhang

School of Architecture, Tianjin University, Tianjin, China.

Keywords

Adult Algorithms China Cities Environment Design Female Humans Machine Learning Male Middle Aged Perception Stress, Psychological Support Vector Machine

External Resources

View on PubMed Access via DOI PubMed (39360258)

Assessing the nonlinear impact of green space exposure on psychological stress perception using machine learning and street view images.

Abstract

Authors

Keywords

External Resources

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