Quantifying the Urban Visual Perception of Chinese Traditional-Style Building with Street View Images

Li-ying, Zhang; Pei, Tao; Xi, Wei; Wu, Mingbo; Ci, Song; Guo, Sihui; Chen, Yijin

doi:10.3390/app10175963

Cited by 18 publications

(14 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In recent years, street view image has became an important data source in urban studies,which provided the advantage of high accessibility, high resolution and wide coverage. (Dubey et al 2016, Zhang et al 2020. Corresponding, street view image is extensively implemented in urban studies (Long and Tang 2019, Ma et al 2021.…”

Section: Introductionmentioning

confidence: 99%

Measuring the perceptual features of coastal streets: a case study in Qingdao, China

Lyu

Meng

Gao

et al. 2022

Environ. Res. Commun.

View full text Add to dashboard Cite

The coastal streets are the most attractive urban space, improving spatial quality and public perception of coastal streets is an important work of urban regeneration. The study used machine learning semantic segmentation, GIS and Semantic difference (SD) etc methods to obtain the spatial data and perceptual evaluation of coastal streets in Qingdao. Each of the six perceptual features, imageability, enclosure, human scale, transparency, complexity and nature, was taken as dependent variables and the corresponding physical features was taken as independent variables. The six regression models were established and the influence rules of spatial parameters on public perception were obtained. Meanwhile, based on the results of perceptual features evaluation, the overall coastal streets are divided into three types, open streets, mixed streets and biophilic streets. In all the three types coastal streets, the nature was the most significant perceptual feature due to the high greenness; the complexity was the lowest perceptual feature because of the low landscape diversity. The research results provided theoretical and technical support for the urban regeneration and spatial quality improvement of coastal streets in Qingdao.

show abstract

Section: Introductionmentioning

confidence: 99%

Measuring the perceptual features of coastal streets: a case study in Qingdao, China

Lyu

Meng

Gao

et al. 2022

Environ. Res. Commun.

View full text Add to dashboard Cite

show abstract

“…The most popular mainstream mapping services used in research are Google Maps, Tencent Maps, and Baidu Maps ( 26 – 28 ). As interactive electronic maps, street views provide users with a panoramic view of the urban built environment at a low cost with high accessibility, high resolution, and wide coverage; thus, street-view images have become a very important new data source for urban built environment research ( 29 – 31 ). Salesses et al ( 32 ) used thousands of geotagged urban street-view images to explore the perceived safety, class, and uniqueness of the built environment in the streets of Boston and New York in the United States and Linz and Salzburg in Austria.…”

Section: Related Workmentioning

confidence: 99%

“…In recent years, many researchers have begun to use street-view images combined with deep learning algorithms to investigate the elements that most strongly affect urban street perception ( 30 , 31 ). Deep learning algorithms, such as FCN, Resnet, and SegNet, use a deep convolutional neural network to process visual information within images, leading to an accurate identification of various visual features that include lanes, buildings, the sky, sidewalks, trees, and greenery and laying a solid foundation for better research on the quality of urban streets and human perception ( 34 – 36 ).…”

Section: Related Workmentioning

confidence: 99%

Measuring Perceived Psychological Stress in Urban Built Environments Using Google Street View and Deep Learning

Han

Wang

Seo

et al. 2022

Front. Public Health

View full text Add to dashboard Cite

An urban built environment is an important part of the daily lives of urban residents. Correspondingly, a poor design can lead to psychological stress, which can be harmful to their psychological and physical well-being. The relationship between the urban built environment and the perceived psychological stress of residents is a significant in many disciplines. Further research is needed to determine the stress level experienced by residents in the built environment on a large scale and identify the relationship between the visual components of the built environment and perceived psychological stress. Recent developments in big data and deep learning technology mean that the technical support required to measure the perceived psychological stress of residents has now become available. In this context, this study explored a method for a rapid and large-scale determination of the perceived psychological stress among urban residents through a deep learning approach. An empirical study was conducted in Gangnam District, Seoul, South Korea, and the SegNet deep learning algorithm was used to segment and classify the visual elements of street views. In addition, a human–machine adversarial model using random forest as a framework was employed to score the perception of the perceived psychological stress in the built environment. Consequently, we found a strong spatial autocorrelation in the perceived psychological stress in space, with more low-low clusters in the urban traffic arteries and riverine areas in Gangnam district and more high-high clusters in the commercial and residential areas. We also analyzed the street view images for three types of stress perception (i.e., low, medium and high) and obtained the percentage of each street view element combination under different stresses. Using multiple linear regression, we found that walls and buildings cause psychological stress, whereas sky, trees and roads relieve it. Our analytical study integrates street view big data with deep learning and proposes an innovative method for measuring the perceived psychological stress of residents in the built environment. The research methodology and results can be a reference for urban planning and design from a human centered perspective.

show abstract

“…With the rapid increase in the number of enterprises on the cloud, the digital technology has played a key role in promoting the rural tourism industry and the reshaping of tourism culture. In digital society and digital tourism, digital platforms and digital marketing methods should be adopted to create a healthy social atmosphere in each village, so as to establish a stable rural tourism culture system (Zhang et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

How “cultural reshaping” affects rural tourism development in China - a case from zhejiang beautiful countryside demonstration area

2022

Tourism and Hospitality Research

View full text Add to dashboard Cite

A number of studies have been carried out on the importance and connotation of tourism culture. However, from the literature study of tourism culture, it is found that there is still a gap between the remolding of tourism culture and the development of tourism enterprises in the digital era. This study aims to identify the enterprise clustering effect and employment benefit of rural tourism culture reshaping. By empirical research, this study establishes a new conceptual research framework for rural tourism sustainability to cover the gap between the cultural reshaping and enterprise development for rural tourism in Zhejiang. We began with investigation to villagers on their acceptance of reshaped tourism culture. Through interviews with entrepreneurs, this study investigates the relationship between tourism cultural reshaping and tourism enterprise image. An enterprise network of regional tourism cultural IP image has been established to describe the density among the whole tourism cultural industry. The location entropy index is adopted to show the employment in tourism enterprises. This index reflects residents’ acceptance of the reshaped cultural image as a key influencing factor of enterprises’ sustainable development. Furthermore, it is found that tourism cultural reshaping is a significant base for rural tourism industry clustering. The research results suggest that tourism corporation can contribute to the local tourism economy by reshaping culture.

show abstract

Quantifying the Urban Visual Perception of Chinese Traditional-Style Building with Street View Images

Cited by 18 publications

References 37 publications

Measuring the perceptual features of coastal streets: a case study in Qingdao, China

Measuring the perceptual features of coastal streets: a case study in Qingdao, China

Measuring Perceived Psychological Stress in Urban Built Environments Using Google Street View and Deep Learning

How “cultural reshaping” affects rural tourism development in China - a case from zhejiang beautiful countryside demonstration area

Contact Info

Product

Resources

About