{"title":"探索绿色景观指数与跑步活动之间的关系:利用 Strava 和谷歌街景数据对日惹和新加坡进行的案例研究","authors":"Firman Afrianto, M. S. Roychansyah, Y. Herwangi","doi":"10.14710/jpk.11.1.58-70","DOIUrl":null,"url":null,"abstract":"The Development of Geospatial Data and Volunteered Geographic Information (VGI) has been significant and can be utilized in urban and regional planning. One of the notable data sources includes Google Street View and Strava running activity data. This research investigates the potential correlation between the presence of green spaces, measured by the Green View Index (GVI) using Google Street View data, and the level of running activity recorded by Strava, a popular running application. The novelty of this study lies in the integration of GVI analysis with Google Street View and Strava data, providing a comprehensive understanding of the relationship between green environments and physical activity by leveraging Big Data. In this research, two locations are compared: Yogyakarta, identified to have a low GVI category, and Singapore, identified to have a high GVI category. The findings reveal a moderate negative correlation between GVI and the Strava running index in Yogyakarta, while a moderate positive correlation is observed in Singapore. These results contribute to the growing research on urban vitality and emphasize the importance of integrating green spaces into urban planning and development using big data. This study serves as a foundation for further research on the relationship between green environments and various forms of physical activity, contributing to the development of healthier and more sustainable cities in the future.","PeriodicalId":31633,"journal":{"name":"Jurnal Pengembangan Kota","volume":"18 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"EXPLORING THE RELATIONSHIP BETWEEN GREEN VIEW INDEX AND RUNNING ACTIVITY: A CASE STUDY OF YOGYAKARTA AND SINGAPORE USING STRAVA AND GOOGLE STREET VIEW DATA\",\"authors\":\"Firman Afrianto, M. S. Roychansyah, Y. Herwangi\",\"doi\":\"10.14710/jpk.11.1.58-70\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Development of Geospatial Data and Volunteered Geographic Information (VGI) has been significant and can be utilized in urban and regional planning. One of the notable data sources includes Google Street View and Strava running activity data. This research investigates the potential correlation between the presence of green spaces, measured by the Green View Index (GVI) using Google Street View data, and the level of running activity recorded by Strava, a popular running application. The novelty of this study lies in the integration of GVI analysis with Google Street View and Strava data, providing a comprehensive understanding of the relationship between green environments and physical activity by leveraging Big Data. In this research, two locations are compared: Yogyakarta, identified to have a low GVI category, and Singapore, identified to have a high GVI category. The findings reveal a moderate negative correlation between GVI and the Strava running index in Yogyakarta, while a moderate positive correlation is observed in Singapore. These results contribute to the growing research on urban vitality and emphasize the importance of integrating green spaces into urban planning and development using big data. This study serves as a foundation for further research on the relationship between green environments and various forms of physical activity, contributing to the development of healthier and more sustainable cities in the future.\",\"PeriodicalId\":31633,\"journal\":{\"name\":\"Jurnal Pengembangan Kota\",\"volume\":\"18 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Pengembangan Kota\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14710/jpk.11.1.58-70\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Pengembangan Kota","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14710/jpk.11.1.58-70","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
EXPLORING THE RELATIONSHIP BETWEEN GREEN VIEW INDEX AND RUNNING ACTIVITY: A CASE STUDY OF YOGYAKARTA AND SINGAPORE USING STRAVA AND GOOGLE STREET VIEW DATA
The Development of Geospatial Data and Volunteered Geographic Information (VGI) has been significant and can be utilized in urban and regional planning. One of the notable data sources includes Google Street View and Strava running activity data. This research investigates the potential correlation between the presence of green spaces, measured by the Green View Index (GVI) using Google Street View data, and the level of running activity recorded by Strava, a popular running application. The novelty of this study lies in the integration of GVI analysis with Google Street View and Strava data, providing a comprehensive understanding of the relationship between green environments and physical activity by leveraging Big Data. In this research, two locations are compared: Yogyakarta, identified to have a low GVI category, and Singapore, identified to have a high GVI category. The findings reveal a moderate negative correlation between GVI and the Strava running index in Yogyakarta, while a moderate positive correlation is observed in Singapore. These results contribute to the growing research on urban vitality and emphasize the importance of integrating green spaces into urban planning and development using big data. This study serves as a foundation for further research on the relationship between green environments and various forms of physical activity, contributing to the development of healthier and more sustainable cities in the future.