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Visual Quality Evaluation of Urban Landscape Based on Computer Vision Technology

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Digital Analysis of Urban Structure and Its Environment Implication

Part of the book series: Advances in 21st Century Human Settlements ((ACHS))

Abstract

The visual quality of urban streetscape is an important feature that directly effects public’s perception of the city; it is also the main content of urban renewal research. The deep learning-based image semantic segmentation method is an important part of computer vision technology, which provides a new method for visual quality evaluation of urban landscape. In this chapter, the core area of Shenyang (within the first ring road) was chosen as the research object, and the street panorama was extracted using Baidu Map API. DeepLabv3+ semantic segmentation model was applied to semantic segmentation of the sample photos; the five spatial characteristic indices of public visual perception of urban streetscape were calculated: green space factor, sky view factor, building area ratio, vehicle occurrence rate, and pedestrian occurrence rate. A regression model of urban streetscape visual quality was constructed by correlation and regression analysis of SBE of urban streetscape and spatial characteristic indices through using typical sample photos. This study combines the spatial characteristic indices of all samples in the core area to calculate the visual quality of streetscape in the core area of Shenyang, establishes the dataset of the street spatial visual quality, explores the correlation between urban spatial characteristics and spatial visual perception, and provides suggestions for urban development planning.

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Author information

Authors and Affiliations

  1. School of Architecture and Urban Planning, Shenyang Jianzhu University, Shenyang, China

    Dong Sun

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  1. Dong Sun
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Correspondence to Dong Sun .

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Editors and Affiliations

  1. Department of Architecture, Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu, Japan

    Weijun Gao

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Sun, D. (2023). Visual Quality Evaluation of Urban Landscape Based on Computer Vision Technology. In: Gao, W. (eds) Digital Analysis of Urban Structure and Its Environment Implication. Advances in 21st Century Human Settlements. Springer, Singapore. https://doi.org/10.1007/978-981-19-6641-5_6

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