Impact of High Temperatures on Tourist Flows in Urban and Rural Areas: Climate Adaptation Strategies in China
The impact of high temperatures on tourist flows in urban and rural areas is both complex and multi-dimensional, yet research remains limited regarding their spatial and temporal differences. This study aims to analyze the changes in tourist flows between urban and rural areas under high-temperature...
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MDPI AG
2025-04-01
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| Series: | Agriculture |
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| Online Access: | https://www.mdpi.com/2077-0472/15/9/980 |
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| author | Man Wei Tai Huang |
| author_facet | Man Wei Tai Huang |
| author_sort | Man Wei |
| collection | DOAJ |
| description | The impact of high temperatures on tourist flows in urban and rural areas is both complex and multi-dimensional, yet research remains limited regarding their spatial and temporal differences. This study aims to analyze the changes in tourist flows between urban and rural areas under high-temperature conditions and to identify the key factors driving these patterns, contributing to climate-resilient tourism planning. Using Shanghai, China, as a case study, we constructed an attraction-based tourist flow model with Baidu migration data, integrating a self-organizing feature map for urban–rural classification and Pearson correlation analysis to examine influencing factors. The results showed that high temperatures significantly reduced tourist flows in both urban and rural areas, with a more pronounced impact observed in rural areas. This reduction altered spatial patterns, shifting from a multicentric distribution to an urban-centered concentration. Furthermore, high temperatures affected the timing of tourist flows differently across regions. In urban areas, tourist flows tended to start earlier, and key driving factors, such as facility services and economic levels, remained stable and continued to exert a dominant influence. In contrast, rural tourist flows were delayed under high-temperature conditions, with tourists showing a preference for cooler attractions further from urban centers. These findings highlight the need for targeted climate adaptation strategies, including improving cooling infrastructure in urban areas and promoting eco-friendly, sustainable tourism initiatives in rural regions. This study offers empirical evidence to support policy efforts aimed at fostering coordinated urban–rural tourism development and advancing sustainable adaptation to climate change. |
| format | Article |
| id | doaj-art-8cf0e1dc7d7b4daeb30e8022c16ac1d3 |
| institution | Kabale University |
| issn | 2077-0472 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
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| series | Agriculture |
| spelling | doaj-art-8cf0e1dc7d7b4daeb30e8022c16ac1d32025-08-20T03:52:56ZengMDPI AGAgriculture2077-04722025-04-0115998010.3390/agriculture15090980Impact of High Temperatures on Tourist Flows in Urban and Rural Areas: Climate Adaptation Strategies in ChinaMan Wei0Tai Huang1School of Social Science, Soochow University, Suzhou 215127, ChinaSchool of Social Science, Soochow University, Suzhou 215127, ChinaThe impact of high temperatures on tourist flows in urban and rural areas is both complex and multi-dimensional, yet research remains limited regarding their spatial and temporal differences. This study aims to analyze the changes in tourist flows between urban and rural areas under high-temperature conditions and to identify the key factors driving these patterns, contributing to climate-resilient tourism planning. Using Shanghai, China, as a case study, we constructed an attraction-based tourist flow model with Baidu migration data, integrating a self-organizing feature map for urban–rural classification and Pearson correlation analysis to examine influencing factors. The results showed that high temperatures significantly reduced tourist flows in both urban and rural areas, with a more pronounced impact observed in rural areas. This reduction altered spatial patterns, shifting from a multicentric distribution to an urban-centered concentration. Furthermore, high temperatures affected the timing of tourist flows differently across regions. In urban areas, tourist flows tended to start earlier, and key driving factors, such as facility services and economic levels, remained stable and continued to exert a dominant influence. In contrast, rural tourist flows were delayed under high-temperature conditions, with tourists showing a preference for cooler attractions further from urban centers. These findings highlight the need for targeted climate adaptation strategies, including improving cooling infrastructure in urban areas and promoting eco-friendly, sustainable tourism initiatives in rural regions. This study offers empirical evidence to support policy efforts aimed at fostering coordinated urban–rural tourism development and advancing sustainable adaptation to climate change.https://www.mdpi.com/2077-0472/15/9/980high-temperature impacttourist flowspatial patternsbig data analyticsdestination choicesustainable tourism |
| spellingShingle | Man Wei Tai Huang Impact of High Temperatures on Tourist Flows in Urban and Rural Areas: Climate Adaptation Strategies in China Agriculture high-temperature impact tourist flow spatial patterns big data analytics destination choice sustainable tourism |
| title | Impact of High Temperatures on Tourist Flows in Urban and Rural Areas: Climate Adaptation Strategies in China |
| title_full | Impact of High Temperatures on Tourist Flows in Urban and Rural Areas: Climate Adaptation Strategies in China |
| title_fullStr | Impact of High Temperatures on Tourist Flows in Urban and Rural Areas: Climate Adaptation Strategies in China |
| title_full_unstemmed | Impact of High Temperatures on Tourist Flows in Urban and Rural Areas: Climate Adaptation Strategies in China |
| title_short | Impact of High Temperatures on Tourist Flows in Urban and Rural Areas: Climate Adaptation Strategies in China |
| title_sort | impact of high temperatures on tourist flows in urban and rural areas climate adaptation strategies in china |
| topic | high-temperature impact tourist flow spatial patterns big data analytics destination choice sustainable tourism |
| url | https://www.mdpi.com/2077-0472/15/9/980 |
| work_keys_str_mv | AT manwei impactofhightemperaturesontouristflowsinurbanandruralareasclimateadaptationstrategiesinchina AT taihuang impactofhightemperaturesontouristflowsinurbanandruralareasclimateadaptationstrategiesinchina |