Using crowdsourcing images to assess visual quality of urban landscapes: A case study of Xiamen Island
Urban landscapes significantly affect human life and well-being. Visual factors are the most critical factors affecting environmental satisfaction and urban landscape quality. Previous studies have been focused on the single influence of landscape indicators on visual quality and ignored the relatio...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-10-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X23009354 |
| _version_ | 1797683085129547776 |
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| author | Zhuoxu Qi Jin Duan Hangying Su Zhengxi Fan Wenlong Lan |
| author_facet | Zhuoxu Qi Jin Duan Hangying Su Zhengxi Fan Wenlong Lan |
| author_sort | Zhuoxu Qi |
| collection | DOAJ |
| description | Urban landscapes significantly affect human life and well-being. Visual factors are the most critical factors affecting environmental satisfaction and urban landscape quality. Previous studies have been focused on the single influence of landscape indicators on visual quality and ignored the relationship between indicators and landscape characteristics that may collectively contribute to visual quality. This study captures the public perception of urban landscape through social media image data and develops a new indicator model system based on structural equation modeling to assess the visual quality of urban landscape on Xiamen Island. Four visual characteristics (i.e., disturbance, complexity, naturalness, and artificial environment) are proposed to describe the composition of the urban landscape. The results show that: (1) Naturalness is the most important characteristic affecting the visual quality of the urban landscape, with a standardized factor loading of 0.82. (2) Artificial environment and complexity indirectly influence the visual quality of the urban landscape through naturalness and together form a coherent urban landscape. (3) Although disturbance has a direct effect on the visual quality of the urban landscape, most of the explained paths still affect the visual quality indirectly through naturalness. The results from this study highlight the importance of focusing on the relationship between the landscape indicators and characteristics and enhancing the understanding of urban landscape quality, with results that can potentially be used as a method for assessing future urban landscape changes and the effects of urban landscape policy decisions. |
| first_indexed | 2024-03-12T00:10:22Z |
| format | Article |
| id | doaj.art-9e106febfdb14cbb8b478b26d2a49616 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-03-12T00:10:22Z |
| publishDate | 2023-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-9e106febfdb14cbb8b478b26d2a496162023-09-16T05:29:58ZengElsevierEcological Indicators1470-160X2023-10-01154110793Using crowdsourcing images to assess visual quality of urban landscapes: A case study of Xiamen IslandZhuoxu Qi0Jin Duan1Hangying Su2Zhengxi Fan3Wenlong Lan4School of Architecture, Southeast University, Department of Urban Planning, Nanjing 210096, ChinaSchool of Architecture, Southeast University, Department of Urban Planning, Nanjing 210096, China; Corresponding author at: 2 Sipailou Road, Xuanwu District, Nanjing 210096, China.College of Architecture and Urban Planning, Tongji University, 1239 Siping Road, Yangpu District, Shanghai 200000, ChinaSchool of Architecture, Southeast University, Department of Urban Planning, Nanjing 210096, ChinaSchool of Architecture, Southeast University, Department of Urban Planning, Nanjing 210096, ChinaUrban landscapes significantly affect human life and well-being. Visual factors are the most critical factors affecting environmental satisfaction and urban landscape quality. Previous studies have been focused on the single influence of landscape indicators on visual quality and ignored the relationship between indicators and landscape characteristics that may collectively contribute to visual quality. This study captures the public perception of urban landscape through social media image data and develops a new indicator model system based on structural equation modeling to assess the visual quality of urban landscape on Xiamen Island. Four visual characteristics (i.e., disturbance, complexity, naturalness, and artificial environment) are proposed to describe the composition of the urban landscape. The results show that: (1) Naturalness is the most important characteristic affecting the visual quality of the urban landscape, with a standardized factor loading of 0.82. (2) Artificial environment and complexity indirectly influence the visual quality of the urban landscape through naturalness and together form a coherent urban landscape. (3) Although disturbance has a direct effect on the visual quality of the urban landscape, most of the explained paths still affect the visual quality indirectly through naturalness. The results from this study highlight the importance of focusing on the relationship between the landscape indicators and characteristics and enhancing the understanding of urban landscape quality, with results that can potentially be used as a method for assessing future urban landscape changes and the effects of urban landscape policy decisions.http://www.sciencedirect.com/science/article/pii/S1470160X23009354Visual quality assessmentsUrban landscape visual characteristicsVisual landscape indicatorsStructural equation modelXiamen Island |
| spellingShingle | Zhuoxu Qi Jin Duan Hangying Su Zhengxi Fan Wenlong Lan Using crowdsourcing images to assess visual quality of urban landscapes: A case study of Xiamen Island Ecological Indicators Visual quality assessments Urban landscape visual characteristics Visual landscape indicators Structural equation model Xiamen Island |
| title | Using crowdsourcing images to assess visual quality of urban landscapes: A case study of Xiamen Island |
| title_full | Using crowdsourcing images to assess visual quality of urban landscapes: A case study of Xiamen Island |
| title_fullStr | Using crowdsourcing images to assess visual quality of urban landscapes: A case study of Xiamen Island |
| title_full_unstemmed | Using crowdsourcing images to assess visual quality of urban landscapes: A case study of Xiamen Island |
| title_short | Using crowdsourcing images to assess visual quality of urban landscapes: A case study of Xiamen Island |
| title_sort | using crowdsourcing images to assess visual quality of urban landscapes a case study of xiamen island |
| topic | Visual quality assessments Urban landscape visual characteristics Visual landscape indicators Structural equation model Xiamen Island |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X23009354 |
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