Luo, J.; Zhai, S.; Song, G.; He, X.; Song, H.; Chen, J.; Liu, H.; Feng, Y.
Assessing Inequity in Green Space Exposure toward a “15-Minute City” in Zhengzhou, China: Using Deep Learning and Urban Big Data. Int. J. Environ. Res. Public Health 2022, 19, 5798.
https://doi.org/10.3390/ijerph19105798
AMA Style
Luo J, Zhai S, Song G, He X, Song H, Chen J, Liu H, Feng Y.
Assessing Inequity in Green Space Exposure toward a “15-Minute City” in Zhengzhou, China: Using Deep Learning and Urban Big Data. International Journal of Environmental Research and Public Health. 2022; 19(10):5798.
https://doi.org/10.3390/ijerph19105798
Chicago/Turabian Style
Luo, Jingjing, Shiyan Zhai, Genxin Song, Xinxin He, Hongquan Song, Jing Chen, Huan Liu, and Yuke Feng.
2022. "Assessing Inequity in Green Space Exposure toward a “15-Minute City” in Zhengzhou, China: Using Deep Learning and Urban Big Data" International Journal of Environmental Research and Public Health 19, no. 10: 5798.
https://doi.org/10.3390/ijerph19105798
APA Style
Luo, J., Zhai, S., Song, G., He, X., Song, H., Chen, J., Liu, H., & Feng, Y.
(2022). Assessing Inequity in Green Space Exposure toward a “15-Minute City” in Zhengzhou, China: Using Deep Learning and Urban Big Data. International Journal of Environmental Research and Public Health, 19(10), 5798.
https://doi.org/10.3390/ijerph19105798