Identifying node-corridor-network of tourist flow and influencing factors using GPS big data: A case study in Gansu and Qinghai provinces, China
Due to constraints in data and technological approaches, there is a deficiency in the analysis of spatial patterns and formation mechanisms of large-scale destination tourist flows at the provincial level. This study leverages open GPS trajectory big data and employs grid units to meticulously chara...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843224006277 |
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| author | Zhiyu Zhang Fuyuan Wang Longtao Deng |
| author_facet | Zhiyu Zhang Fuyuan Wang Longtao Deng |
| author_sort | Zhiyu Zhang |
| collection | DOAJ |
| description | Due to constraints in data and technological approaches, there is a deficiency in the analysis of spatial patterns and formation mechanisms of large-scale destination tourist flows at the provincial level. This study leverages open GPS trajectory big data and employs grid units to meticulously characterize the spatial patterns and associated formation mechanisms of regional-scale tourist flows in Qinghai and Gansu Provinces. The findings reveal the following: (1) Regional tourist flows exhibit a distinct “point-axis-ring” agglomeration distribution pattern. (2) The “Gansu-Qinghai Tourist Grand Loop” has emerged as a predominant regional tourism corridor. Within this loop, there are smaller, high-density sub-loops centered on specific tourist attractions. (3) Ecology, service and scenic area are the three major influencing mechanisms for spatial differentiation of tourist flow in Gansu-Qinghai region. The findings can provide significant insights for the prioritization of regional tourism route marketing and planning, the configuration of tourism service facilities, etc. |
| format | Article |
| id | doaj-art-612fb910ac744c54a6fe072b8594ce41 |
| institution | DOAJ |
| issn | 1569-8432 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj-art-612fb910ac744c54a6fe072b8594ce412025-08-20T02:52:23ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322024-12-0113510427110.1016/j.jag.2024.104271Identifying node-corridor-network of tourist flow and influencing factors using GPS big data: A case study in Gansu and Qinghai provinces, ChinaZhiyu Zhang0Fuyuan Wang1Longtao Deng2Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, No.11 Datun Rd., Chaoyang District, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Regional Sustainable Development Modeling, Chinese Academy of Sciences, No.11 Datun Rd., Chaoyang District, Beijing 100101, ChinaInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, No.11 Datun Rd., Chaoyang District, Beijing 100101, China; Key Laboratory of Regional Sustainable Development Modeling, Chinese Academy of Sciences, No.11 Datun Rd., Chaoyang District, Beijing 100101, China; Corresponding author at: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, No.11 Datun Rd., Chaoyang District, Beijing, China.School of Computer Science and Technology, Beijing Jiaotong University, No.3 Shangyuancun, Haidian District, Beijing 100044, ChinaDue to constraints in data and technological approaches, there is a deficiency in the analysis of spatial patterns and formation mechanisms of large-scale destination tourist flows at the provincial level. This study leverages open GPS trajectory big data and employs grid units to meticulously characterize the spatial patterns and associated formation mechanisms of regional-scale tourist flows in Qinghai and Gansu Provinces. The findings reveal the following: (1) Regional tourist flows exhibit a distinct “point-axis-ring” agglomeration distribution pattern. (2) The “Gansu-Qinghai Tourist Grand Loop” has emerged as a predominant regional tourism corridor. Within this loop, there are smaller, high-density sub-loops centered on specific tourist attractions. (3) Ecology, service and scenic area are the three major influencing mechanisms for spatial differentiation of tourist flow in Gansu-Qinghai region. The findings can provide significant insights for the prioritization of regional tourism route marketing and planning, the configuration of tourism service facilities, etc.http://www.sciencedirect.com/science/article/pii/S1569843224006277GPS trajectoryBig dataTourist flowSpatial networkGansu-Qinghai Region |
| spellingShingle | Zhiyu Zhang Fuyuan Wang Longtao Deng Identifying node-corridor-network of tourist flow and influencing factors using GPS big data: A case study in Gansu and Qinghai provinces, China International Journal of Applied Earth Observations and Geoinformation GPS trajectory Big data Tourist flow Spatial network Gansu-Qinghai Region |
| title | Identifying node-corridor-network of tourist flow and influencing factors using GPS big data: A case study in Gansu and Qinghai provinces, China |
| title_full | Identifying node-corridor-network of tourist flow and influencing factors using GPS big data: A case study in Gansu and Qinghai provinces, China |
| title_fullStr | Identifying node-corridor-network of tourist flow and influencing factors using GPS big data: A case study in Gansu and Qinghai provinces, China |
| title_full_unstemmed | Identifying node-corridor-network of tourist flow and influencing factors using GPS big data: A case study in Gansu and Qinghai provinces, China |
| title_short | Identifying node-corridor-network of tourist flow and influencing factors using GPS big data: A case study in Gansu and Qinghai provinces, China |
| title_sort | identifying node corridor network of tourist flow and influencing factors using gps big data a case study in gansu and qinghai provinces china |
| topic | GPS trajectory Big data Tourist flow Spatial network Gansu-Qinghai Region |
| url | http://www.sciencedirect.com/science/article/pii/S1569843224006277 |
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