Research on the Correlation Mechanism between Street Space Quality and Walking Behavior in Data Environment
Abstract
It is of great significance to explore the correlation mechanism between urban street space quality and residents’walking behavior for rational and effective allocation of street facilities resources and promotion of healthy and green travel. Taking Qiguitang block in Hefei as an example, the streetscape image is crawled through Python, and the elements of street spatial quality are quantified by a machine learning algorithm, spatial syntax, and ArcGIS. Get travel data through behavior observation, and then build a multiple linear regression model for the correlation study of spatial quality and behavior characteristics to summarize the interaction degree and mode of various influencing factors. The research shows that there is a specific mathematical relationship between walking behavior and street space elements, among which functional formats, walking width, and interface openness have a more significant impact on walking behavior. Accordingly, the optimization strategy of street space in the old city area is proposed to provide a reference for the formulation of Hefei street design guidelines.
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WHYTE W H. The Social life of Small Urban Spaces[M]. The US: The Conservation Foundation, 1980.
HUANG Jianzhong,HU Gangyu.Comparison and Thinking of Pedestrian Measurement Methods of Urban Built Environment [J]. Western Journal of Human Settlements, 2016,31( 1):67-74.
MA Qiang,WEI Xiao,REN Guannan. Street Design Guidelines and Optimization and Improvement of Urban Road System Transfomation From Traffic Capacity to Space Quality [J]. Urban traffic, 2021, 19(5):1-16.
LONG Ying, SHEN Yao. Data Enhanced Design—Planning and Design Response and Change in the New Data Environment[J]. Shanghai Urban Planning,2015(2):81-87.
HAO Xinhua,LONG Ying, SHI Miao, et al.The Vitality of Beijing Streets: Measurement, Influencing Factors and Inspiration From Planning and Design[J]. Shanghai Urban Planning,2016(3):37-45.
HAO Xinhua,LONG Ying.Street Greening:a New Pedestrian Evaluation Index[J]. Shanghai Urban Planning, 2017( 1):32-36,49.
TANG Jingxian,LONG Ying.Measurement of street space quality in the central area of mega cities—taking the second and third ring roads of Beijing and the inner ring roads of Shanghai as examples[J]. Planners,2017,33(2):68-73.
YE Yu, ZHANG Zhaoxi, ZHANG Xiaohu, et al. Humanistic Street Space Quality Measurement—a Large-Scale and High-Precision Evaluation Framework Combining Street Scene Data and New Analysis Technology[J]. International Urban Planning, 2019, 34( 1): 18-27.
XU Leiqing,MENG Ruoxi,CHEN Zheng.The Charming Street:The Influence of Architectural Interface and Green Vision[J]. Landscape architecture,2017( 10):27-33.
YANG Junyan, WU Hao, ZHENG Yi. Research on the Spatial Characteristics and Optimization Strategies of Urban Street Walkability Based on Multi-Source Big Data—Taking the Central Urban Area of Nanjing as an example[J]. International Uban Planning,2019,34(5):33-42.
CHEN Jingjia, ZHANG Zhaoxi, LONG Ying. Strategies for Improving the Quality of Public Health Oriented Street Space —From the Perspective of Spatial Disorder [J]. Urban Planning, 2020,44(9):35-47.
MIAO Cencen.Research on the Measurement and Impact Mechanism of Urban Street Space Quality Based on Street View Image Data[D]. Southeast University, 2018.
ZHANG Zhang,XU Gaofeng, LI Wenyue, et al.The Impact of the Micro-Scale Built Environment of Historic Street on Visitor ’s Walking Behaviors:A Case Study on Wudaoying Hutong in Beijing[J]. Architecture Journal,2019(3):96-102.
JACOBS J. The Death and Life of Great American Cities[M]. New York:Random house, 1961.
Gehl, J.Life Between Buildings[M]. New York:Van Nostrand Reinhold, 1987.
LI Chi,HUANG Zhejiao,ZHU Sisi.An Investigation on Pedestrian Pleasure inShichahai,Beijing[J]. Planner,2014,30(4):112-118.
GOU Aiping,WANG Jiangbo.SD Method Based Street Space Vitality Evaluation[J]. Planner,2011,27( 10):102-106.
ZHOU Wei, HUANG Zhenfang, GUO Wen, et al. Empirical Research on The Tourists’perception After The Trip of Landscape Preference of The Historical Culture Block: A Case Study of Confucius Temple in Nanjing[J]. Human Geography,2012, 27( 6): 117-123.
WANG Kun. Research on the Street Space in the Old city of Hefei [D]. Hefei:Hefei University of Technology, 2019.
LONG Ying,ZHOU Yin.Picture Urbanism: A New Approach to the Study of Human based Urban Form[J]. Planner, 2017, 33(2): 54-60.
JAN G.Communication and Space[M]. China Architecture Press, 2002, 10.
XU Leiqing,JIANG Wenjin,CHEN Zheng.Research on the Sense of Security in Public Space: Taking the Perception of Urban Street Scenes in Shanghai as an Example [J]. Landscape architecture,2018,25(7):23-29.
YANG Junyan, CAO Jun. Dynamic · Static · Visible · Hidden: Four Application Modes of Big Data in Urban Design[J]. Jounal of Urban Planning,2017(4):39-46.
TIMMERMANS H, VAN D W, ALVES M, et al. Spatial Context and the Complexity of Daily Travel Patterns: An International Comparison[J]. Journal of Transport Geography,2003, 111:37-46.
GIULIANO G , NARAYAN D. Another Look at Travel Patterns and Urban Form: The US and Great Britain[J]. Urban Studies,2003,40( 11):2295-2312.
SHAO Yuan,YE Dan,YE Yu.Research on Large-Scale Measurement of Street Interface Permeability Based on Streetscape Data and in-Depth Learning-Taking Shanghai as an Example[J/OL]. International Urban Planning:1-13[2022-11-14].
BADRINARAYANAN V, KENDALL A, CIPOLLA R. SegNet: a Deepconvolutional Encoder-Decoder Architecture for Image Segmentation[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence,2017( 12):2481-2495.
CHEN L C, PAPANDREOU G, KOKKINOS I, et al.Deeplab: Semanticimage Segmentation With Deep Convolutional Nets, Atrous Convolution, and Fully Connected Crfs[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018, 40( 4): 834-848.
REDMON J, FARHADI A. YOLO9000: Better, Faster, Stronger [C] ∥ 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) .IEEE,2017:6517-6525.
ZHANG Ruifang. Evaluation and Analysis of Urban Street Space Quality[D]. Hebei University of Engineering,2020.
CHEN Shuai. Study on Behavior Vigor of Urban Leisure Square [D]. Central South University,2009.
PENG Huiyun. Restorative Environmental Impact Mechanism and Spatial Optimization of Community parks [D]. Chongqing:Chongqing University, 2017.
ZHAO Xiaolong,ZHAO Ruyue, HOU Yunjing, et al. Research on the Correlation Between Residential Street Spatial Characteristics and Pedestrian Flow Based on Multi-Source Open data [ J]. Journal of Architecture, 2020 ( S2): 110-114.
YIN Yuchen. Study on the Design Strategy of Living Street Sha ring in Hefei Old Town From the Perspective of “Urban repair” [D]. Hefei :Hefei University of Technology, 2020.
MAO Zhirui, CHEN Xiaokui, XIANG Zhenhai, et al.Research on Street Vitality Measurement and Influencing Factors of Historical Blocks—Taking the Historical Block of Wenming Street in Kunming as an Example[J]. Southern Architecture, 2021(4):54-61.
ZENG Wei, ZHANG Yike. Protection and Utilization of Ancient Temples and Surrounding Areas in Urban renewal: a Reflection Based on Place theory. Southern Architecture, 2021(2): 83-89.
Shanghai Municipal Planning and Land Resources Administration Bureau[M]. Shanghai Transportation Commission, Shanghai Urban Planning and Design Institute, Shanghai Street Design Guidelines, Tongji University Press,2016.10.
LUO Qi,WEN Zihan, YU Laiyan.Research on Strategies for Improving Street Space Vitality in Small Towns Under the Guidance of Environmental Behavior—Taking Zihu Town as an Example[J]. Research on Urban Development,2019,26(2):20-24,30.
DOI: https://doi.org/10.33142/jsa.v2i1.15474
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