AccScience Publishing / JCAU / Volume 6 / Issue 1 / DOI: 10.36922/jcau.1736
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ORIGINAL RESEARCH ARTICLE

Exploring the spatial attributes of streets in Lu Xun’s hometown of Shaoxing, China, through image semantic segmentation

Qingyuan Hong1*
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1 Department of Architecture, School of Architecture, Southeast University, Nanjing, China
Journal of Chinese Architecture and Urbanism 2024, 6(1), 1736 https://doi.org/10.36922/jcau.1736
Submitted: 31 August 2023 | Accepted: 25 October 2023 | Published: 5 January 2024
© 2024 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

Image semantic segmentation, a deep learning algorithm, enables the recognition of pixel collections that form distinct categories, allowing for the identification of vehicles, pedestrians, traffic signs, pavement, and other road features. In urban and architectural design domains, image semantic segmentation and related techniques empower practitioners and researchers to efficiently analyze the distribution of public spaces. This application facilitates a better understanding of how people interact with urban environments, ultimately improving the design of functional and inviting spaces. This paper presents an analysis of images of different streets within the Lu Xun Heritage Area in Shaoxing, Zhejiang Province, China, which were obtained through onsite photography. The images were sampled, segmented, and compared to assess the spatial characteristics of distinct street types. A self-trained semantic segmentation model based on the Cityscapes dataset and the PaddlePaddle framework was employed to statistically analyze space variations across various dimensions. This analysis contributes to a better understanding of historical street structure and provides insights into the integration of artificial intelligence in urban planning and design.

Keywords
Lu Xun’s hometown
Semantic segmentation
Street space
Historic streets
Vibrant streets
Shaoxing China
Funding
This research received no financial support from public or private sectors.
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Conflict of interest
The author declares no competing interests in this paper.
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Journal of Chinese Architecture and Urbanism, Electronic ISSN: 2717-5626 Published by AccScience Publishing