id |
caadria2024_272 |
authors |
Liu, Jiaxin, Huang, Xiaoran and Yan, Hongming |
year |
2024 |
title |
Exploring Visual Factors Influencing Women’s Perceived Insecurity in Metro Stations and Adjacent Built Environments: A Case Study of Milan, Italy |
doi |
https://doi.org/10.52842/conf.caadria.2024.2.385
|
source |
Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 2, pp. 385–394 |
summary |
Prior research has established a direct correlation between women's perceived insecurity in public spaces and the design of the surrounding built environment. However, limited attention has been given to investigating how the built environment influences women's security perceptions within metro systems. This study introduces a novel methodology to analyze the impact of visual factors on the entire walking experience within commuter cores, covering both the station and surrounding areas in Milan Metro Line 1. Both Street View Imagery (SVI) and manual photography are employed for semantic segmentation analysis, followed by expert auditing and machine learning for evaluation. Finally, the study constructs regression models to analyze the relationship between the area ratio of visual factors and women’s perceptions. The results demonstrate that certain factors, such as wider platforms and sidewalks, can positively influence women's safety perceptions in the surrounding and interior spaces, respectively. The models could be used to dissect Milan's other metro stations and their surroundings, offering insights applicable to other metro lines. Moreover, the methodology presents serves as a framework for investigating analogous concerns in diverse cities and delving into the experiences of other marginal groups. |
keywords |
metro station, perceived insecurity, women perception, Google Street View, built environment, deep learning, inclusive city |
series |
CAADRIA |
email |
xiaoran.huang@ncut.edu.cn |
full text |
file.pdf (2,094,909 bytes) |
references |
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Barabas, A.T. (Ed.) (2018)
The dimensions of insecurity in urban areas: research on the roots of unsafety and fear of crime in European cities
, National Institute of Criminology, Budapest
|
|
|
|
Ceccato, V., Uittenbogaard, A., Bamzar, R. (2013)
Security in Stockholms underground stations: The importance of environmental attributes and context
, Security Journal, 26, 33-59
|
|
|
|
Cozens, P., Neale, R., Whitaker, J., Hillier, D. (2003)
Managing crime and the fear of crime at railway stations--a case study in South Wales (UK)
, International Journal of Transport Management, 1, 121-132
|
|
|
|
Gong, W., Huang, X., White, M., Langenheim, N. (2023)
Walkability Perceptions and Gender Differences in Urban Fringe New Towns: A Case Study of Shanghai
, Land, 12, 1339
|
|
|
|
Jansson, C. (2019)
Factors important to street users perceived safety on a main street
, Skolan För Arkitektur Och Samhällsbyggnad: Stockholm
|
|
|
|
Paydar, M., Kamani-Fard, A., Etminani-Ghasrodashti, R. (2017)
Perceived security of women in relation to their path choice toward sustainable neighborhood in Santiago, Chile
, Cities, 60, 289-300
|
|
|
|
Pozzi, G. (2023)
Very sneaky crimes: Squatting, urban security, and class anthropopoiesis in Milan (Italy)
, Focaal, 1, 1-15
|
|
|
|
Yao, Y., Liang, Z., Yuan, Z., Liu, P., Bie, Y., Zhang, J., Wang, R., Wang, J., Guan, Q. (2019)
A human-machine adversarial scoring framework for urban perception assessment using street-view images
, International Journal of Geographical Information Science, 33, 2363-2384
|
|
|
|
Zhou, B., Liu, L., Oliva, A., Torralba, A. (2014)
Recognizing City Identity via Attribute Analysis of Geo-tagged Images
, Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (Eds.), Computer Vision - ECCV 2014. Lecture Notes in Computer Science. Springer Interna-tional Publishing, Cham, pp. 519-534
|
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last changed |
2024/11/17 22:05 |
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