【摘要】
参考文献

基于多源数据的街道环境对个体安全感的影响研究

Research on the Influence of Street Space on Individual Security Based on Multisource Data

方智果
上海理工大学艺术设计学院副教授，硕士生导师

王振
上海理工大学艺术设计学院讲师

刘聪
上海理工大学艺术学院硕士研究生

王冉冉
上海理工大学艺术设计学院硕士研究生

摘要: 以开放街道地图、兴趣点、地理位置，以及图像识别、深度学习等为代表的各种新数据、新技术为定量的街道空间评估带来新的数据源和全新的研究方法与途经。结合上海市打造高品质街道空间的议题背景，以上海街道空间为研究对象，以地图兴趣点、街景图像、三维建筑地图等多源数据为载体，利用深度学习技术与GIS，大规模测度个体安全感感知与城市功能、建筑界面、街道物理3类客体指标。在此基础上，通过数理推导以揭示客体指标与街道安全感知的关系。研究发现：城市功能是影响街道安全感的关键因子，其中街道功能密度比功能混合度对安全感的感知影响更大；店招个数、绿视率对安全感知也具有积极影响。

Abstract: Various new data and new technologies represented by open street maps, points of interest, Location Based Services, image recognition, and deep learning bring new data sources and brand-new research methods and approaches to quantitative street space assessment. Under the background of creating high-quality street space, this article takes Shanghai's streets as the research object, uses map points of interest, street scene images, three-dimensional architectural maps and other multi-source data as the carrier, and uses deep learning technology and GIS to measure personal security perception and urban function, architectural interface, and street physics on a large scale. On this basis, the mathematical derivation is used to reveal the relationship between object indicators and street safety perception. The study finds that urban function is a key factor that affects the sense of security in the street, and the density of street functions has a greater impact on the perception of security than the degree of functional mixture. The number of store recruitments and the green viewing rate also have a positive effect on the perception of security.

关键词：安全感；街景图像；深度学习；上海街道

Keyword: sense of security; street view image; deep learning; Shanghai street

中图分类号：TU984

文献标识码: A

资金资助

国家重点研发计划文化产品产权价值评估与确权标识应用技术研究 2021YFF0900400

FRUIN J. Pedestrian: planning and design[M]. New York: Metropolitan Association of Urban Designers and Environmental Planners, 1971.
黄建中，胡刚钰. 城市建成环境的步行性测度方法比较与思考[J]. 西部人居环境学刊，2016，31（1）：
67-74.
HUANG Jianzhong, HU Gangyu. Comparison and consideration of walkability measurement methods
in urban built environment[J]. Journal of Human Settlements in West China, 2016, 31(1): 67-74.
龙瀛，唐婧娴. 街道空间品质大规模量化测度研究进展[J]. 城市规划，2020（6）：107-114.
LONG Ying, TANG Jingxian. Research progress on large-scale quantitative measurement of street space quality[J]. City Planning Review, 2020(6): 107-114.
PANTER J, GUELL C, PRINS R, et al. Physical activity and the environment: conceptual review and
framework for intervention research[J]. International Journal of Behavioral Nutrition and Physical Activity, 2017, 14(1): 156.
DALGARD O S, TAMBS K. Urban environment and mental health: a longitudinal study[J]. The British
Journal of Psychiatry, 1997, 171(6): 530-536.
ANESHENSEL C S , SUCOFF C A . T h e neighborhood context of adolescent mental health[J].
Journal of Health and Social Behavior, 1996, 37(4): 293-310.
扬•盖尔. 交往与空间[M]. 何人可，译. 北京：中国建筑工业出版社，2002.
GEHL J. Communication and space[M]. HE Renke, et al. Beijing: China Architecture & Building Press,
2002.
徐磊青，江文津，陈筝. 公共空间安全感研究：以上海城市街景感知为例[J]. 风景园林，2018（7）：23-
29.
XU Leiqing, JIANG Wenjin, CHEN Zheng. Research on the sense of security in public space:
taking Shanghai City street view perception as an example[J]. Landscape Architecture, 2018(7): 23-29.
KAMADA M, TSUMITA H, et al. Study on spatial evaluation on the discontinuous streetscape[C]//
The Proceedings of 9th International Symposium on Environment Behavior Studies, 2010.
JIANG B, MAK S, ZHONG H, et al. From broken windows to perceived routine activities: examining
impacts of environmental interventions on perceived safety of urban alleys[J]. Frontiers in Psychology, 2018, 9: 2450.
NAIK N, PHILIPOOM J, RASKAR R, et al. Streetscore—predicting the perceived safety of one
million streetscapes[C]//2014 IEEE Conference on Computer Vision & Pattern Recognition Workshops, 2014: 793-799.
ZHANG F, ZHOU B. LIU L, et al. Measuring human perceptions of a large-scale urban region using machine learning[J]. Landscape and Urban Planning, 2018, 180: 148-160.
HARVEY C, AULTMAN L, HURLEY S E, et al. Effects of skeletal streetscape design on perceived
safety[J]. Landscape and Urban Planning, 2015, 142: 18-28.
KELLY C M, WILSON J S, BAKER E A, et al. Using Google Street View to audit the built environment:
inter-rater reliability results[J]. Annals of Behavioral Medicine, 2013, 45(1): 108-112.
HU C, ZHANG F, GONG F, et al. Classification and mapping of urban canyon geometry using Google
Street View images and deep multitask learning[J]. Urban Forestry & Urban Greening, 2020(4): 100-106.
LI X, ZHANG C, LI W, et al. Who lives in greener neighborhoods? The distribution of street greenery and its association with residents' socioeconomic conditions in Hartford, Connecticut, USA[J]. Urban Forestry & Urban Greening, 2015, 14(4): 100-106.
COHEN L, FELSON M. Social change and crime rate trends: a routine activities approach[J]. American
Sociological Review, 1979, 44(4): 588-608.
WILSON J. Broken windows[J]. Atlantic Monthly, 1982, 249(3): 29-38.
EWING R, HANDY S. Measuring the unmeasurable: urban design qualities related to walkability[J]. Journal of Urban Design, 2009, 14(1): 65-84.
JIANG B, CHANG C, SULLIVAN W C. A dose of nature: tree cover, stress reduction, and gender
differences[J]. Landscape and Urban Planning, 2014, 132: 26-36.
JIANG B, LARSEN L, DEAL B, et al. A dose-response curve describing the relationship between tree cover density and landscape preference[J]. Landscape and Urban Planning, 2015, 139: 16-25.
GEHL J. Cities for people[M]. Washington, DC: Island Press, 2010.
JACOBS J. The death and life of great American cities[M]. Visalia: Vintage Press, 2016.
GEHL J, KAEFER L J, REIGSTAD S. Close encounters with buildings[J]. Urban Design International, 2006, 11: 29-47.
MONTGOMERY C. Happy city: transforming our lives through urban design[M]. Stuttgart: Macmillan,
2013. ZHAO H, SHI J, QI X, et al. Pyramid scene parsing network[C]//2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017: 2881-2890.
CAMPBELL A, BOTH A, SUN Q C. Detecting and mapping traffic signs from Google Street View images using deep learning and GIS[J]. Computers, Environment and Urban Systems, 2019, 77: 101350.
SALESSES P, SCHECHTNER K, HIDALGO C. The collaborative image of the city: mapping the inequality
of urban perception[J]. PLoS One, 2013(7): e68400.
雅各布斯. 伟大的街道[M]. 王又佳，金秋野，译. 北京：中国工业建筑出版社，2009.
JACOBS A. The great street[M]. WANG Youjia,JIN Qiuye, translate. Beijing: China Architecture &
Building Press, 2009.
ASHIHARA Y. The aesthetic townscape[M]. Cambridge: The MIT Press, 1983.
徐磊青，孟若希. 疗愈导向的街道设计：基于VR实验的探索[J]. 国际城市规划，2019（1）：65-84.
XU Leiqing, MENG Ruoxi. Healing oriented street design: exploration based on VR experiment[J]. Urban Planning International, 2019(1): 65-84.
扬•盖尔. 人性化的城市[M]. 欧阳文，徐哲文，译. 北京：中国建筑工业出版社，2010.
GEHL J. A humane city[M]. OUYANG Wen, XU Zhewen, translate. Beijing: China Architecture &
Building Press, 2010.
DAVEIS L .Urban design compendium[M]. London: English Partnerships and the Housing Corporation, 2000.
JANSSON M, FORS H, LINDGREN T, et al. Perceived personal safety in relation to urban woodland
vegetation–a review[J]. Urban Forestry Urban Greening, 2013(1): 127-133.

返回列表>>