Gender Disparities in green exposure: An empirical study in suburban Beijing. Wu, J., Newell, J., Xu, Z., Jin, Y., Chai, Y., & Ta, N. Landscape and Urban Planning, 2022. ![Gender Disparities in green exposure: An empirical study in suburban Beijing [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Good urban green space is conducive to the physical and mental health of residents. However, the exposure of different social groups to urban greenness is not always equal. The majority of literature used residential areas as the analysis unit to evaluate green space, which may lead to biased estimates because it ignores daily mobility. In addition, many studies discussed gender as a variable rather than the main focus. In this context, the present research attempted to develop and explore a broad analytical theme, namely, examine whether green exposure between genders is equal. We used 7,880 GPS trip tracking data from 662 respondents in Haidian District, Beijing, and combined these with street view big data and machine learning to calculate the green view index for constructing a novel method of measuring green exposure. The results provided three main insights: (1) Men enjoyed greater overall green exposure than women because they are generally less restricted when traveling. (2) Women are more likely to choose green, pleasant, and safe travel routes than men. Thus, they experience higher levels of green exposure of unit travel distance. (3) Individual and travel characteristics result in different green exposure, and different travel modes may enhance or weaken men and women's exposure to green spaces in different ways. This study tested and reported the disparities in green exposure of residents with different genders. Also, it contributes empirical evidence to the connection between individual or travel characteristics and access to green street landscape of men and women. © 2022 Elsevier B.V.
@article{wu_gender_2022,
title = {Gender {Disparities} in green exposure: {An} empirical study in suburban {Beijing}},
volume = {222},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125253584&doi=10.1016%2fj.landurbplan.2022.104381&partnerID=40&md5=656de32abec24eb95a4f23442843c525},
doi = {10.1016/j.landurbplan.2022.104381},
abstract = {Good urban green space is conducive to the physical and mental health of residents. However, the exposure of different social groups to urban greenness is not always equal. The majority of literature used residential areas as the analysis unit to evaluate green space, which may lead to biased estimates because it ignores daily mobility. In addition, many studies discussed gender as a variable rather than the main focus. In this context, the present research attempted to develop and explore a broad analytical theme, namely, examine whether green exposure between genders is equal. We used 7,880 GPS trip tracking data from 662 respondents in Haidian District, Beijing, and combined these with street view big data and machine learning to calculate the green view index for constructing a novel method of measuring green exposure. The results provided three main insights: (1) Men enjoyed greater overall green exposure than women because they are generally less restricted when traveling. (2) Women are more likely to choose green, pleasant, and safe travel routes than men. Thus, they experience higher levels of green exposure of unit travel distance. (3) Individual and travel characteristics result in different green exposure, and different travel modes may enhance or weaken men and women's exposure to green spaces in different ways. This study tested and reported the disparities in green exposure of residents with different genders. Also, it contributes empirical evidence to the connection between individual or travel characteristics and access to green street landscape of men and women. © 2022 Elsevier B.V.},
journal = {Landscape and Urban Planning},
author = {Wu, J. and Newell, J. and Xu, Z. and Jin, Y. and Chai, Y. and Ta, N.},
year = {2022},
keywords = {Gender, Green exposure, Green travel experience, Urban planning},
}
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In addition, many studies discussed gender as a variable rather than the main focus. In this context, the present research attempted to develop and explore a broad analytical theme, namely, examine whether green exposure between genders is equal. We used 7,880 GPS trip tracking data from 662 respondents in Haidian District, Beijing, and combined these with street view big data and machine learning to calculate the green view index for constructing a novel method of measuring green exposure. The results provided three main insights: (1) Men enjoyed greater overall green exposure than women because they are generally less restricted when traveling. (2) Women are more likely to choose green, pleasant, and safe travel routes than men. Thus, they experience higher levels of green exposure of unit travel distance. (3) Individual and travel characteristics result in different green exposure, and different travel modes may enhance or weaken men and women's exposure to green spaces in different ways. This study tested and reported the disparities in green exposure of residents with different genders. 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