A New Urban Vitality Analysis and Evaluation Framework Based on Human Activity Modeling Using Multi-Source Big Data
A quantitative study of urban vitality brings new insights for evaluating the external construction environment and internal development power of cities. However, it still has limited knowledge of the relations between people’s diverse urban life and urban vitality, although urban activities are oft...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-10-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/9/11/617 |
| _version_ | 1827703609502990336 |
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| author | Shaojun Liu Ling Zhang Yi Long Yao Long Mianhao Xu |
| author_facet | Shaojun Liu Ling Zhang Yi Long Yao Long Mianhao Xu |
| author_sort | Shaojun Liu |
| collection | DOAJ |
| description | A quantitative study of urban vitality brings new insights for evaluating the external construction environment and internal development power of cities. However, it still has limited knowledge of the relations between people’s diverse urban life and urban vitality, although urban activities are often used as the proxy for urban vitality. This paper aims to deeply mine the content of urban social life and reveal the driving mechanism of urban vitality after inspecting human activities. We propose a general framework for exploring the spatial pattern and driving mechanism of urban vitality using multi-source big data. It builds a mapping relationship between various urban activities and urban vitality aspects, including economic and social. In addition, the physical environment (static) and human–land interaction (dynamic) indicators are designed to analyze the driving mechanism of urban vitality using the Geographically Weighted Regression model. The results show that the spatial pattern and driving factors of urban vitality are heterogeneous over space regarding both the economic and social aspects of our experimental study. This work provides us with multiple perspectives to understand the connotation of urban vitality and urges us to develop rational strategies to make the city more vital, coordinated, and sustainable. |
| first_indexed | 2024-03-10T15:23:20Z |
| format | Article |
| id | doaj.art-2294e264f8564a6088a8d5ec67e66522 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T15:23:20Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-2294e264f8564a6088a8d5ec67e665222023-11-20T18:16:31ZengMDPI AGISPRS International Journal of Geo-Information2220-99642020-10-0191161710.3390/ijgi9110617A New Urban Vitality Analysis and Evaluation Framework Based on Human Activity Modeling Using Multi-Source Big DataShaojun Liu0Ling Zhang1Yi Long2Yao Long3Mianhao Xu4Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, ChinaKey Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, ChinaKey Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, ChinaKey Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, ChinaKey Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, ChinaA quantitative study of urban vitality brings new insights for evaluating the external construction environment and internal development power of cities. However, it still has limited knowledge of the relations between people’s diverse urban life and urban vitality, although urban activities are often used as the proxy for urban vitality. This paper aims to deeply mine the content of urban social life and reveal the driving mechanism of urban vitality after inspecting human activities. We propose a general framework for exploring the spatial pattern and driving mechanism of urban vitality using multi-source big data. It builds a mapping relationship between various urban activities and urban vitality aspects, including economic and social. In addition, the physical environment (static) and human–land interaction (dynamic) indicators are designed to analyze the driving mechanism of urban vitality using the Geographically Weighted Regression model. The results show that the spatial pattern and driving factors of urban vitality are heterogeneous over space regarding both the economic and social aspects of our experimental study. This work provides us with multiple perspectives to understand the connotation of urban vitality and urges us to develop rational strategies to make the city more vital, coordinated, and sustainable.https://www.mdpi.com/2220-9964/9/11/617urban vitalityhuman activity recognitionmulti-source big dataspatial formspatial interaction |
| spellingShingle | Shaojun Liu Ling Zhang Yi Long Yao Long Mianhao Xu A New Urban Vitality Analysis and Evaluation Framework Based on Human Activity Modeling Using Multi-Source Big Data ISPRS International Journal of Geo-Information urban vitality human activity recognition multi-source big data spatial form spatial interaction |
| title | A New Urban Vitality Analysis and Evaluation Framework Based on Human Activity Modeling Using Multi-Source Big Data |
| title_full | A New Urban Vitality Analysis and Evaluation Framework Based on Human Activity Modeling Using Multi-Source Big Data |
| title_fullStr | A New Urban Vitality Analysis and Evaluation Framework Based on Human Activity Modeling Using Multi-Source Big Data |
| title_full_unstemmed | A New Urban Vitality Analysis and Evaluation Framework Based on Human Activity Modeling Using Multi-Source Big Data |
| title_short | A New Urban Vitality Analysis and Evaluation Framework Based on Human Activity Modeling Using Multi-Source Big Data |
| title_sort | new urban vitality analysis and evaluation framework based on human activity modeling using multi source big data |
| topic | urban vitality human activity recognition multi-source big data spatial form spatial interaction |
| url | https://www.mdpi.com/2220-9964/9/11/617 |
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