Evaluation and Optimization of Urban Street Spatial Quality Based on Street View Images and Machine Learning: A Case Study of the Jinan Old City
As one of the most important urban public spaces, the design and management of streets have shifted from “two-dimensional plan” to “three-dimensional space”, and higher requirements have been put forward for the scale and precision of urban design. The core research question of this research is how...
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MDPI AG
2025-04-01
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| author | Peipei Li Yabing Xu Zichuan Liu Haitao Jiang Anzhen Liu |
| author_facet | Peipei Li Yabing Xu Zichuan Liu Haitao Jiang Anzhen Liu |
| author_sort | Peipei Li |
| collection | DOAJ |
| description | As one of the most important urban public spaces, the design and management of streets have shifted from “two-dimensional plan” to “three-dimensional space”, and higher requirements have been put forward for the scale and precision of urban design. The core research question of this research is how to refine street spatial quality measurement and evaluation based on multitemporal street view images, while providing basic data and corresponding decision support for updates and renovations. “One Garden and Twelve Fangs” in Jinan old city is the core area of the Jinan Commercial Port District. It integrates diverse cultural elements of tradition and modernity, local and foreign, and is of great significance to the cultural inheritance and urban development of Jinan. Nowadays, there is a lack of vitality, lagging development, and shorting of high-quality living service facilities here. How to enhance the overall vitality of the region and drive regional social value is an urgent problem that needs to be solved at present. This research takes the old city area of Jinan as the research scope, constructs a street space quality evaluation model through street view images and machine learning, and establishes the connection between quantitative research on street space quality and urban renewal practice. In this research, the standard system will be supplemented and improved, and the practicality of the application will be enhanced through more refined evaluation models. The evaluation indicators include walkability, green visibility, enclosure, openness, imaginability, coordination, extreme boundary area, and interface transparency. This article provides a feasible framework and paradigm for measuring the quality of large-scale and high-precision street spaces through the combination of big data and artificial intelligence, effectively bridging the gap between spatial quantification research and urban renewal practices. |
| format | Article |
| id | doaj-art-1ad47ad99bbc4d18aea8ddca0a1a49a8 |
| institution | Kabale University |
| issn | 2075-5309 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
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| series | Buildings |
| spelling | doaj-art-1ad47ad99bbc4d18aea8ddca0a1a49a82025-08-20T03:52:56ZengMDPI AGBuildings2075-53092025-04-01159140810.3390/buildings15091408Evaluation and Optimization of Urban Street Spatial Quality Based on Street View Images and Machine Learning: A Case Study of the Jinan Old CityPeipei Li0Yabing Xu1Zichuan Liu2Haitao Jiang3Anzhen Liu4School of Civil Engineering, Tsinghua University, Beijing 100084, ChinaSchool of Architecture and Urban Planning, Shandong Jianzhu University, Jinan 250101, ChinaSchool of Architecture and Urban Planning, Shandong Jianzhu University, Jinan 250101, ChinaSchool of Architecture and Urban Planning, Shandong Jianzhu University, Jinan 250101, ChinaSchool of Architecture and Urban Planning, Shandong Jianzhu University, Jinan 250101, ChinaAs one of the most important urban public spaces, the design and management of streets have shifted from “two-dimensional plan” to “three-dimensional space”, and higher requirements have been put forward for the scale and precision of urban design. The core research question of this research is how to refine street spatial quality measurement and evaluation based on multitemporal street view images, while providing basic data and corresponding decision support for updates and renovations. “One Garden and Twelve Fangs” in Jinan old city is the core area of the Jinan Commercial Port District. It integrates diverse cultural elements of tradition and modernity, local and foreign, and is of great significance to the cultural inheritance and urban development of Jinan. Nowadays, there is a lack of vitality, lagging development, and shorting of high-quality living service facilities here. How to enhance the overall vitality of the region and drive regional social value is an urgent problem that needs to be solved at present. This research takes the old city area of Jinan as the research scope, constructs a street space quality evaluation model through street view images and machine learning, and establishes the connection between quantitative research on street space quality and urban renewal practice. In this research, the standard system will be supplemented and improved, and the practicality of the application will be enhanced through more refined evaluation models. The evaluation indicators include walkability, green visibility, enclosure, openness, imaginability, coordination, extreme boundary area, and interface transparency. This article provides a feasible framework and paradigm for measuring the quality of large-scale and high-precision street spaces through the combination of big data and artificial intelligence, effectively bridging the gap between spatial quantification research and urban renewal practices.https://www.mdpi.com/2075-5309/15/9/1408spatial qualitystreet view imagesmachine learningtraditional architecture and culturerenewal strategy |
| spellingShingle | Peipei Li Yabing Xu Zichuan Liu Haitao Jiang Anzhen Liu Evaluation and Optimization of Urban Street Spatial Quality Based on Street View Images and Machine Learning: A Case Study of the Jinan Old City Buildings spatial quality street view images machine learning traditional architecture and culture renewal strategy |
| title | Evaluation and Optimization of Urban Street Spatial Quality Based on Street View Images and Machine Learning: A Case Study of the Jinan Old City |
| title_full | Evaluation and Optimization of Urban Street Spatial Quality Based on Street View Images and Machine Learning: A Case Study of the Jinan Old City |
| title_fullStr | Evaluation and Optimization of Urban Street Spatial Quality Based on Street View Images and Machine Learning: A Case Study of the Jinan Old City |
| title_full_unstemmed | Evaluation and Optimization of Urban Street Spatial Quality Based on Street View Images and Machine Learning: A Case Study of the Jinan Old City |
| title_short | Evaluation and Optimization of Urban Street Spatial Quality Based on Street View Images and Machine Learning: A Case Study of the Jinan Old City |
| title_sort | evaluation and optimization of urban street spatial quality based on street view images and machine learning a case study of the jinan old city |
| topic | spatial quality street view images machine learning traditional architecture and culture renewal strategy |
| url | https://www.mdpi.com/2075-5309/15/9/1408 |
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