Acta Geographica Sinica ›› 2023, Vol. 78 ›› Issue (4): 1044-1056.doi: 10.11821/dlxb202304017
• Behavioral Geography • Previous Articles Next Articles
WU Jiayu1(), WANG Shiyi1, LI Hong2,3,4, TA Na2,3,4(
)
Received:
2022-05-09
Revised:
2022-12-28
Online:
2023-04-25
Published:
2023-04-13
Contact:
TA Na
E-mail:wujiayula@zju.edu.cn;nta@geo.ecnu.edu.cn
Supported by:
WU Jiayu, WANG Shiyi, LI Hong, TA Na. The correlation between plant color perception and anxiety based on artificial intelligence technology[J].Acta Geographica Sinica, 2023, 78(4): 1044-1056.
Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks
Tab. 1
Results of descriptive analysis of samples
焦虑调查结果 | P值 | |||||
---|---|---|---|---|---|---|
正常 | 轻度焦虑 | 中度至严重焦虑 | ||||
连续变量平均值(标准差) | 年龄(岁) | 36.54(±11.4) | 37.57(±10.6) | 38.85(±11.3) | 0.184 | |
家庭平均月收入(元) | 14856.2(±11237.5) | 17504.9(±27664.8) | 14411.3(±13931.4) | 0.246 | ||
分类变量人数(人)(构成比(%)) | 性别 | 男性 | 103(58.5) | 196(52.8) | 65(48.9) | 0.224 |
女性 | 73(41.5) | 175(47.2) | 68(51.1) | |||
受教育程度 | 小学及以下 | 4(2.3) | 8(2.2) | 3(2.3) | 0.375 | |
初中 | 35(19.9) | 58(15.6) | 23(17.3) | |||
高中(含中专、职高) | 44(25.0) | 83(22.4) | 26(19.6) | |||
大专 | 30(17.1) | 90(24.3) | 26(19.6) | |||
大学本科 | 54(30.7) | 118(31.8) | 43(32.3) | |||
本科以上 | 9(5.1) | 14(3.8) | 12(9.0) | |||
合计(人) | 176 | 371 | 133 |
Tab. 2
Mean value of plant color evaluation and comparison between groups
平均值(95%CI) | ||||||
---|---|---|---|---|---|---|
以居住地为中心 | 以工作地为中心 | |||||
500 m缓冲区 | 1000 m缓冲区 | 500 m缓冲区 | 1000 m缓冲区 | |||
GVI | 第1组 | 0.218(0.155, 0.257) | 0.230(0.206, 0.269) | 0.232(0.171, 0.289) | 0.248(0.196, 0.281) | |
第2组 | 0.220(0.162, 0.276) | 0.232(0.198, 0.276) | 0.234(0.170, 0.294) | 0.248(0.198, 0.289) | ||
第3组 | 0.226(0.177, 0.281) | 0.237(0.203, 0.276) | 0.242(0.148, 0.303) | 0.249(0.206, 0.286) | ||
P值 | 0.401 | 0.921 | 0.960 | 0.935 | ||
叶色丰富度 | 第1组 | 1.163(0.990, 1.331) | 1.244(1.141, 1.340) | 0.466(0.279, 0.576) | 0.474(0.336, 0.580) | |
第2组 | 1.200(1.016, 1.348) | 1.287(1.186, 1.362) | 0.374(0.234, 0.522) | 0.386(0.258, 0.542) | ||
第3组 | 1.200(0.990, 1.354) | 1.287(1.142, 1.362) | 0.364(0.222, 0.545) | 0.390(0.262, 0.569) | ||
P值 | 0.53 | 0.117 | 0.005** | 0.001** | ||
花色丰富度 | 第1组 | 3.854(3.785, 3.903) | 3.843(3.836, 3.888) | 2.424(1.574, 2.955) | 2.502(1.581, 2.956) | |
第2组 | 3.858(3.789, 3.903) | 3.868(3.836, 3.908) | 1.809(1.196, 2.818) | 1.812(1.224, 2.885) | ||
第3组 | 3.859(3.789, 3.903) | 3.856(3.818, 3.896) | 1.966(1.220, 2.866) | 1.956(1.253, 2.930) | ||
P值 | 0.904 | 0.025* | 0.001** | 0.002** |
Tab. 3
Results of ordinal Logistic regression models on plant color and anxiety
OR(95%CI) | ||||||
---|---|---|---|---|---|---|
以居住地为中心 | 以工作地为中心 | |||||
500 m缓冲区 | 1000 m缓冲区 | 500 m缓冲区 | 1000 m缓冲区 | |||
GVI | 低(Q1) | 1.00 | 1.00 | 1.00 | 1.00 | |
中(Q2) | 0.62(0.39~0.99)* | 1.06(0.67~1.68) | 0.77(0.51~1.16) | 1.25(0.84~1.90) | ||
较高(Q3) | 0.97(0.62~1.52) | 0.79(0.49~1.26) | 0.98(0.64~1.48) | 1.10(0.73~1.65) | ||
高(Q4) | 0.95(0.59~1.52) | 1.06(0.67~1.68) | 1.01(0.67~1.52) | 1.13(0.74~1.70) | ||
叶色丰富度 | 低(Q1) | 1.00 | 1.00 | 1.00 | 1.00 | |
中(Q2) | 0.90(0.59~1.36) | 1.02(0.67~1.54) | 0.88(0.58~1.34) | 1.24(0.82~1.88) | ||
较高(Q3) | 1.28(0.54~1.92) | 1.18(0.79~1.79) | 0.68(0.45~1.02) | 1.17(0.77~1.77) | ||
高(Q4) | 1.13(0.75~1.70) | 1.30(0.86~1.97) | 0.64(0.42~0.97)* | 0.96(0.64~1.45) | ||
花色丰富度 | 低(Q1) | 1.00 | 1.00 | 1.00 | 1.00 | |
中(Q2) | 1.09(0.73~1.63) | 1.22(0.81~1.86) | 0.65(0.43~0.99)* | 0.84(0.56~1.27) | ||
较高(Q3) | 1.19(0.79~1.80) | 1.23(0.82~1.84) | 0.73(0.48~1.10) | 1.15(0.76~1.73) | ||
高(Q4) | 1.14(0.76~1.73) | 1.16(0.77~1.73) | 0.63(0.41~0.95)* | 0.85(0.57~1.28) |
[1] |
Trautmann S, Rehm J, Wittchen H U. The economic costs of mental disorders: Do our societies react appropriately to the burden of mental disorders? EMBO Reports, 2016, 17(9): 1245-1249.
doi: 10.15252/embr.201642951 pmid: 27491723 |
[2] |
Helbich M. Toward dynamic urban environmental exposure assessments in mental health research. Environmental Research, 2018, 161: 129-135.
doi: S0013-9351(17)31255-0 pmid: 29136521 |
[3] |
Banay R F, James P, Hart J E, et al. Greenness and depression incidence among older women. Environmental Health Perspectives, 2019, 127(2): 027001. DOI: 10.1289/EHP1229.
doi: 10.1289/EHP1229 |
[4] |
Liu Y, Wang R Y, Xiao Y, et al. Exploring the linkage between greenness exposure and depression among Chinese people: Mediating roles of physical activity, stress and social cohesion and moderating role of urbanicity. Health & Place, 2019, 58: 102168. DOI: 10.1016/j.healthplace.2019.102168.
doi: 10.1016/j.healthplace.2019.102168 |
[5] |
Villeneuve P J, Ysseldyk R L, Root A, et al. Comparing the normalized difference vegetation index with the Google street view measure of vegetation to assess associations between greenness, walkability, recreational physical activity, and health in Ottawa, Canada. International Journal of Environmental Research and Public Health, 2018, 15(8): 1719. DOI: 10.3390/ijerph15081719.
doi: 10.3390/ijerph15081719 |
[6] |
Hartig T, Mitchell R, de Vries S, et al. Nature and health. Annual Review of Public Health, 2014, 35: 207-228.
doi: 10.1146/annurev-publhealth-032013-182443 pmid: 24387090 |
[7] |
Markevych I, Schoierer J, Hartig T, et al. Exploring pathways linking greenspace to health: Theoretical and methodological guidance. Environmental Research, 2017, 158: 301-317.
doi: S0013-9351(17)30306-7 pmid: 28672128 |
[8] |
De Vries S, Van Dillen S M E, Groenewegen P P, et al. Streetscape greenery and health: Stress, social cohesion and physical activity as mediators. Social Science & Medicine, 2013, 94: 26-33.
doi: 10.1016/j.socscimed.2013.06.030 |
[9] |
Dzhambov A, Hartig T, Markevych I, et al. Urban residential greenspace and mental health in youth: Different approaches to testing multiple pathways yield different conclusions. Environmental Research, 2018, 160: 47-59.
doi: S0013-9351(17)31222-7 pmid: 28961469 |
[10] |
Liu Y, Wang R Y, Grekousis G, et al. Neighbourhood greenness and mental wellbeing in Guangzhou, China: What are the pathways? Landscape and Urban Planning, 2019, 190: 103602. DOI: 10.1016/j.landurbplan.2019.103602.
doi: 10.1016/j.landurbplan.2019.103602 |
[11] | Gerstenberg T, Hofmann M. Perception and preference of trees: A psychological contribution to tree species selection in urban areas. Urban Forestry & Urban Greening, 2016, 15: 103-111. |
[12] | Ulrich R S. Aesthetic and affective response to natural environment//Altman I, Wohlwill J F. Behavior and the Natural Environment. Boston: Springer, 1983: 85-125. |
[13] | Larson L R, Barger B, Ogletree S, et al. Gray space and green space proximity associated with higher anxiety in youth with autism. Health & Place, 2018, 53: 94-102. |
[14] | Kaplan S, Talbot J F. Psychological benefits of a wilderness experience//Altman I, Wohlwill J F. Behavior and the Natural Environment. Boston: Springer, 1983: 163-203. |
[15] |
Kaplan S. The restorative benefits of nature: Toward an integrative framework. Journal of Environmental Psychology, 1995, 15(3): 169-182.
doi: 10.1016/0272-4944(95)90001-2 |
[16] |
Olszewska A A, Marques P F, Ryan R L, et al. What makes a landscape contemplative? Environment and Planning B: Urban Analytics and City Science, 2018, 45(1): 7-25.
doi: 10.1177/0265813516660716 |
[17] |
Olszewska-Guizzo A. Contemplative landscapes: Towards healthier built environments. Environment and Social Psychology, 2018, 3(2). DOI: 10.18063/esp.v0.i0.735.
doi: 10.18063/esp.v0.i0.735 |
[18] |
Du H Y, Zhou F Q, Cai Y L, et al. Research on public health and well-being associated to the vegetation configuration of urban green space, a case study of Shanghai, China. Urban Forestry & Urban Greening, 2021, 59: 126990. DOI: 10.1016/j.ufug.2021.126990.
doi: 10.1016/j.ufug.2021.126990 |
[19] | Lengen C. The effects of colours, shapes and boundaries of landscapes on perception, emotion and mentalising processes promoting health and well-being. Health & Place, 2015, 35: 166-177. |
[20] | Paraskevopoulou A T, Kamperi E, Demiris N, et al. The impact of seasonal colour change in planting on patients with psychotic disorders using biosensors. Urban Forestry & Urban Greening, 2018, 36: 50-56. |
[21] |
Liu K X, Elsadek M, Liu B Y, et al. Foliage colors improve relaxation and emotional status of university students from different countries. Heliyon, 2021, 7(1): e06131. DOI: 10.1016/j.heliyon.2021.e06131.
doi: 10.1016/j.heliyon.2021.e06131 |
[22] |
Wang Y Q, Qu H H, Bai T, et al. Effects of variations in color and organ of color expression in urban ornamental bamboo landscapes on the physiological and psychological responses of college students. International Journal of Environmental Research and Public Health, 2021, 18(3): 1151. DOI: 10.3390/ijerph18031151.
doi: 10.3390/ijerph18031151 |
[23] |
Du H Y, Jiang H, Song X J, et al. Assessing the visual aesthetic quality of vegetation landscape in urban green space from a visitor's perspective. Journal of Urban Planning and Development, 2016, 142(3): 04016007. DOI: 10.1061/(ASCE)UP.1943-5444.0000329.
doi: 10.1061/(ASCE)UP.1943-5444.0000329 |
[24] | Li X J, Zhang C R, Li W D, et al. Assessing street-level urban greenery using Google Street View and a modified green view index. Urban Forestry & Urban Greening, 2015, 14(3): 675-685. |
[25] |
Bonney R, Cooper C B, Dickinson J, et al. Citizen science: A developing tool for expanding science knowledge and scientific literacy. BioScience, 2009, 59(11): 977-984.
doi: 10.1525/bio.2009.59.11.9 |
[26] |
Soroye P, Ahmed N, Kerr J T. Opportunistic citizen science data transform understanding of species distributions, phenology, and diversity gradients for global change research. Global Change Biology, 2018, 24(11): 5281-5291.
doi: 10.1111/gcb.14358 pmid: 29920854 |
[27] | Jin Shichao, Hu Tianyu, Su Yanjun, et al. LiVegetation: An investigative tool for vegetation mapping in the era of citizen science. Scientia Sinica (Vitae), 2021, 51(3): 362-374. |
[金时超, 胡天宇, 苏艳军, 等. “绿途”系统: 公民科学时代的植被调查制图新工具. 中国科学: 生命科学, 2021, 51(3): 362-374.] | |
[28] |
Li X J, Ghosh D. Associations between body mass index and urban "green" streetscape in Cleveland, Ohio, USA. International Journal of Environmental Research and Public Health, 2018, 15(10): 2186. DOI: 10.3390/ijerph15102186.
doi: 10.3390/ijerph15102186 |
[29] |
Ki D, Lee S. Analyzing the effects of Green View Index of neighborhood streets on walking time using Google Street View and deep learning. Landscape and Urban Planning, 2021, 205: 103920. DOI: 10.1016/j.landurbplan.2020.103920.
doi: 10.1016/j.landurbplan.2020.103920 |
[30] |
Paddle E, Gilliland J. Orange is the new green: Exploring the restorative capacity of seasonal foliage in schoolyard trees. International Journal of Environmental Research and Public Health, 2016, 13(5): 497. DOI: 10.3390/ijerph13050497.
doi: 10.3390/ijerph13050497 |
[31] |
Ta Na, Chai Yanwei. Disciplinary position and research frontiers of behavioral geography. Progress in Geography, 2022, 41(1): 1-15.
doi: 10.18306/dlkxjz.2022.01.001 |
[塔娜, 柴彦威. 行为地理学的学科定位与前沿方向. 地理科学进展, 2022, 41(1): 1-15.]
doi: 10.18306/dlkxjz.2022.01.001 |
|
[32] |
Kwan M P. The limits of the neighborhood effect: Contextual uncertainties in geographic, environmental health, and social science research. Annals of the American Association of Geographers, 2018, 108(6): 1482-1490.
doi: 10.1080/24694452.2018.1453777 |
[33] |
Kwan M P. The uncertain geographic context problem. Annals of the Association of American Geographers, 2012, 102(5): 958-968.
doi: 10.1080/00045608.2012.687349 |
[34] | Shanghai Municipal Statistical Bureau. Shanghai Population Census Yearbook 2020, 2021. https://tjj.sh.gov.cn/tjnj_rkpc/20220829/29affc5f21a942cc8ab73a39e93c88f3.html, 2022-08-03. |
[上海市统计局. 上海市人口普查年鉴2020, 2021. https://tjj.sh.gov.cn/tjnj_rkpc/20220829/29affc5f21a942cc8ab73a39e93c88f3.html, 2022-08-03.] | |
[35] |
Lovibond P F, Lovibond S H. The structure of negative emotional states: Comparison of the Depression Anxiety Stress Scales (DASS) with the Beck Depression and Anxiety Inventories. Behaviour Research and Therapy, 1995, 33(3): 335-343.
doi: 10.1016/0005-7967(94)00075-u pmid: 7726811 |
[36] |
Dong G P, Ma J, Lee D C, et al. Developing a locally adaptive spatial multilevel logistic model to analyze ecological effects on health using individual census records. Annals of the American Association of Geographers, 2020, 110(3): 739-757.
doi: 10.1080/24694452.2019.1644990 |
[37] |
Dong G P, Harris R. Spatial autoregressive models for geographically hierarchical data structures. Geographical Analysis, 2015, 47(2): 173-191.
doi: 10.1111/gean.2015.47.issue-2 |
[38] |
Ma J, Dong G P, Chen Y, et al. Does satisfactory neighbourhood environment lead to a satisfying life? An investigation of the association between neighbourhood environment and life satisfaction in Beijing. Cities, 2018, 74: 229-239.
doi: 10.1016/j.cities.2017.12.008 |
[39] |
Hartley K, Perazzo J, Brokamp C, et al. Residential surrounding greenness and self-reported symptoms of anxiety and depression in adolescents. Environmental Research, 2021, 194: 110628. DOI: 10.1016/j.envres.2020.110628.
doi: 10.1016/j.envres.2020.110628 |
[40] |
Stas M, Aerts R, Hendrickx M, et al. Residential green space types, allergy symptoms and mental health in a cohort of tree pollen allergy patients. Landscape and Urban Planning, 2021, 210: 104070. DOI: 10.1016/j.landurbplan.2021.104070.
doi: 10.1016/j.landurbplan.2021.104070 |
[41] |
Torres Toda M, Anabitarte Riol A, Cirach M, et al. Residential surrounding greenspace and mental health in three Spanish areas. International Journal of Environmental Research and Public Health, 2020, 17(16): 5670. DOI: 10.3390/ijerph17165670.
doi: 10.3390/ijerph17165670 |
[42] |
Dai L Y, Zheng C L, Dong Z K, et al. Analyzing the correlation between visual space and residents' psychology in Wuhan, China using street-view images and deep-learning technique. City and Environment Interactions, 2021, 11: 100069. DOI: 10.1016/j.cacint.2021.100069.
doi: 10.1016/j.cacint.2021.100069 |
[43] |
Helbich M, Poppe R, Oberski D, et al. Can't see the wood for the trees? An assessment of street view-and satellite-derived greenness measures in relation to mental health. Landscape and Urban Planning, 2021, 214: 104181. DOI: 10.1016/j.landurbplan.2021.104181.
doi: 10.1016/j.landurbplan.2021.104181 |
[44] |
Jiang B, Larsen L, Deal B, et al. A dose-response curve describing the relationship between tree cover density and landscape preference. Landscape and Urban Planning, 2015, 139: 16-25.
doi: 10.1016/j.landurbplan.2015.02.018 |
[45] | De Jong K, Albin M, Skärbäck E, et al. Perceived green qualities were associated with neighborhood satisfaction, physical activity, and general health: Results from a cross-sectional study in suburban and rural Scania, southern Sweden. Health & Place, 2012, 18(6): 1374-1380. |
[46] |
Yu H Y, Hu L W, Zhou Y, et al. Association between eye-level greenness and lung function in urban Chinese children. Environmental Research, 2021, 202: 111641. DOI: 10.1016/j.envres.2021.111641.
doi: 10.1016/j.envres.2021.111641 |
[47] | Wong D W S. The modifiable areal unit problem (MAUP)//Janelle D G, Warf B, Hansen K. World Minds: Geographical Perspectives on 100 Problems. Dordrecht: Springer, 2004: 571-575. |
[48] |
Gascon M, Sánchez-Benavides G, Dadvand P, et al. Long-term exposure to residential green and blue spaces and anxiety and depression in adults: A cross-sectional study. Environmental Research, 2018, 162: 231-239.
doi: S0013-9351(18)30012-4 pmid: 29358115 |
[49] |
Mackay G J, Neill J T. The effect of "green exercise" on state anxiety and the role of exercise duration, intensity, and greenness: A quasi-experimental study. Psychology of Sport and Exercise, 2010, 11(3): 238-245.
doi: 10.1016/j.psychsport.2010.01.002 |
[50] | Giles-Corti B, Broomhall M H, Knuiman M, et al. Increasing walking: How important is distance to, attractiveness, and size of public open space? American Journal of Preventive Medicine, 2005, 28(2): 169-176. |
[51] |
Yang Y Y, Lu Y, Yang H R, et al. Impact of the quality and quantity of eye-level greenery on park usage. Urban Forestry & Urban Greening, 2021, 60: 127061. DOI: 10.1016/j.ufug.2021.127061.
doi: 10.1016/j.ufug.2021.127061 |
[52] |
Pilarczyk J, Kuniecki M, Wołoszyn K, et al. Blue blood, red blood. How does the color of an emotional scene affect visual attention and pupil size? Vision Research, 2020, 171: 36-45.
doi: S0042-6989(20)30068-7 pmid: 32371225 |
[53] |
Wu W J, Yao Y, Song Y M, et al. Perceived influence of street-level visible greenness exposure in the work and residential environment on life satisfaction: Evidence from Beijing, China. Urban Forestry & Urban Greening, 2021, 62: 127161. DOI: 10.1016/j.ufug.2021.127161.
doi: 10.1016/j.ufug.2021.127161 |
[54] |
Kaplan R. The role of nature in the context of the workplace. Landscape and Urban Planning, 1993, 26(1-4): 193-201.
doi: 10.1016/0169-2046(93)90016-7 |
[55] |
Kwan M P. The neighborhood effect averaging problem (NEAP): An elusive confounder of the neighborhood effect. International Journal of Environmental Research and Public Health, 2018, 15(9): 1841. DOI: 10.3390/ijerph15091841.
doi: 10.3390/ijerph15091841 |
[1] | LIU Yu, WANG Keli, XING Xiaoyue, GUO Hao, ZHANG Weiyu, LUO Qinyao, GAO Song, HUANG Zhou, LI Haifeng, LI Xin, WANG Jiaoe, WANG Jinfeng, ZHU Di. On spatial effects in geographical analysis [J]. Acta Geographica Sinica, 2023, 78(3): 517-531. |
[2] | DU Yun-Yan-1, Wang-Li-Jing-2, Ji-Min-2, Cao-Feng-1. A CBR Approach for Land Use Change Prediction [J]. Acta Geographica Sinica, 2009, 64(12): 1421-1429. |
[3] | Yang Leang. ARTIFICIAL INTELLIGENCE,SPATIAL ANALYSIS, AND SPATIAL DECISION MAKING [J]. Acta Geographica Sinica, 1997, 52(s1): 104-113. |
[4] | Liang Qizhang. THE STATE AND TRENDS IN CIS [J]. Acta Geographica Sinica, 1989, 44(1): 117-121. |