Evaluation of Street Space Quality Using Streetscape Data: Perspective from Recreational Physical Activity of the Elderly
The quality of street space has attracted attention. It is important to understand the needs of different population groups for street space quality, especially the rapidly growing elderly group. Improving the quality of street space is conducive to promoting the physical leisure activities of the e...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/11/4/241 |
| _version_ | 1827628581355782144 |
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| author | Ying Du Wei Huang |
| author_facet | Ying Du Wei Huang |
| author_sort | Ying Du |
| collection | DOAJ |
| description | The quality of street space has attracted attention. It is important to understand the needs of different population groups for street space quality, especially the rapidly growing elderly group. Improving the quality of street space is conducive to promoting the physical leisure activities of the elderly to benefit to their health. Therefore, it is important to evaluate street space quality for the elderly. The existing studies, on the one hand, are limited by the sample size of traditional survey data, which is hard to apply on a large scale; on the other hand, there is a lack of consideration for factors that reveal the quality of street space from the perspective of the elderly. This paper takes Guangzhou as an example to evaluate the quality of street space. First, the sample street images were scored by the elderly on a small scale; then the regression analysis was used to extract the street elements that the elderly care about. Last, the street elements were put into the random forest model to assess street space quality io a large scale. It was found that the green view rate and sidewalks are positively correlated with satisfaction, and the positive effect increases in that order. Roads, buildings, sky, vehicles, walls, ceilings, glass windows, runways, railings, and rocks are negatively correlated with satisfaction, and the negative effect increases in that order. The mean satisfaction score of the quality of street space for the elderly’s recreational physical activities in three central districts of Guangzhou (Yuexiu, Liwan, and Haizhu) is 2.6, among which Xingang street gets the highest quality score (2.92), and Hailong street has the lowest quality score (2.32). These findings are useful for providing suggestions to governors and city designers for street space optimization. |
| first_indexed | 2024-03-09T13:35:29Z |
| format | Article |
| id | doaj.art-da1e1f20c8934d08839350999ef33abf |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-09T13:35:29Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-da1e1f20c8934d08839350999ef33abf2023-11-30T21:13:39ZengMDPI AGISPRS International Journal of Geo-Information2220-99642022-04-0111424110.3390/ijgi11040241Evaluation of Street Space Quality Using Streetscape Data: Perspective from Recreational Physical Activity of the ElderlyYing Du0Wei Huang1Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, ChinaTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, ChinaThe quality of street space has attracted attention. It is important to understand the needs of different population groups for street space quality, especially the rapidly growing elderly group. Improving the quality of street space is conducive to promoting the physical leisure activities of the elderly to benefit to their health. Therefore, it is important to evaluate street space quality for the elderly. The existing studies, on the one hand, are limited by the sample size of traditional survey data, which is hard to apply on a large scale; on the other hand, there is a lack of consideration for factors that reveal the quality of street space from the perspective of the elderly. This paper takes Guangzhou as an example to evaluate the quality of street space. First, the sample street images were scored by the elderly on a small scale; then the regression analysis was used to extract the street elements that the elderly care about. Last, the street elements were put into the random forest model to assess street space quality io a large scale. It was found that the green view rate and sidewalks are positively correlated with satisfaction, and the positive effect increases in that order. Roads, buildings, sky, vehicles, walls, ceilings, glass windows, runways, railings, and rocks are negatively correlated with satisfaction, and the negative effect increases in that order. The mean satisfaction score of the quality of street space for the elderly’s recreational physical activities in three central districts of Guangzhou (Yuexiu, Liwan, and Haizhu) is 2.6, among which Xingang street gets the highest quality score (2.92), and Hailong street has the lowest quality score (2.32). These findings are useful for providing suggestions to governors and city designers for street space optimization.https://www.mdpi.com/2220-9964/11/4/241Streetscape imagestreet space qualitythe elderlyrecreational physical activitydeep learningmachine learning |
| spellingShingle | Ying Du Wei Huang Evaluation of Street Space Quality Using Streetscape Data: Perspective from Recreational Physical Activity of the Elderly ISPRS International Journal of Geo-Information Streetscape image street space quality the elderly recreational physical activity deep learning machine learning |
| title | Evaluation of Street Space Quality Using Streetscape Data: Perspective from Recreational Physical Activity of the Elderly |
| title_full | Evaluation of Street Space Quality Using Streetscape Data: Perspective from Recreational Physical Activity of the Elderly |
| title_fullStr | Evaluation of Street Space Quality Using Streetscape Data: Perspective from Recreational Physical Activity of the Elderly |
| title_full_unstemmed | Evaluation of Street Space Quality Using Streetscape Data: Perspective from Recreational Physical Activity of the Elderly |
| title_short | Evaluation of Street Space Quality Using Streetscape Data: Perspective from Recreational Physical Activity of the Elderly |
| title_sort | evaluation of street space quality using streetscape data perspective from recreational physical activity of the elderly |
| topic | Streetscape image street space quality the elderly recreational physical activity deep learning machine learning |
| url | https://www.mdpi.com/2220-9964/11/4/241 |
| work_keys_str_mv | AT yingdu evaluationofstreetspacequalityusingstreetscapedataperspectivefromrecreationalphysicalactivityoftheelderly AT weihuang evaluationofstreetspacequalityusingstreetscapedataperspectivefromrecreationalphysicalactivityoftheelderly |