Wenting Zhang , Haochun Guan , Shan Li , Bo Huang , Wuyang Hong , Wenping Liu
{"title":"街道尺度的建筑环境对城市公园游览量的影响:武汉案例研究","authors":"Wenting Zhang , Haochun Guan , Shan Li , Bo Huang , Wuyang Hong , Wenping Liu","doi":"10.1016/j.apgeog.2024.103374","DOIUrl":null,"url":null,"abstract":"<div><p>The COVID-19 pandemic has changed human life globally. Existing studies have revealed that citizens' visitations to urban parks varied before and after the COVID-19 outbreak. However, few studies have examined how street-scale built environments (SBEs) on routes affect visitations to urban parks at varying COVID-19 risk levels. In this study, a stated-preference survey was conducted to investigate 3,218 visitors' changes in urban park visitation under various COVID-19 risk levels. In addition to park visit influencing factors, including park features, neighborhood built environment, socio-demographic attributes, and travel distances, multiple SBE indexes on visitors' routes to parks were obtained from 34,780 Baidu Map street view images using a deep neural network (DeepLabv3+) method. The results suggest that a high GVI and high traffic congestion on the route from the visitor's home to the urban park led to an increased probability of visiting the urban park by 188.1% (p = 0.044, OR = 2.881) and a decreased probability by 32.3% (p = 0.049, OR = 0.677), respectively. The high probability of visitation was also associated with socio-demographic attributes (including male gender, high income, high and medium education levels, and the elderly) and short travel distances.</p></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"171 ","pages":"Article 103374"},"PeriodicalIF":4.0000,"publicationDate":"2024-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The impact of street-scale built environments on urban park visitations: A case study in Wuhan\",\"authors\":\"Wenting Zhang , Haochun Guan , Shan Li , Bo Huang , Wuyang Hong , Wenping Liu\",\"doi\":\"10.1016/j.apgeog.2024.103374\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The COVID-19 pandemic has changed human life globally. Existing studies have revealed that citizens' visitations to urban parks varied before and after the COVID-19 outbreak. However, few studies have examined how street-scale built environments (SBEs) on routes affect visitations to urban parks at varying COVID-19 risk levels. In this study, a stated-preference survey was conducted to investigate 3,218 visitors' changes in urban park visitation under various COVID-19 risk levels. In addition to park visit influencing factors, including park features, neighborhood built environment, socio-demographic attributes, and travel distances, multiple SBE indexes on visitors' routes to parks were obtained from 34,780 Baidu Map street view images using a deep neural network (DeepLabv3+) method. The results suggest that a high GVI and high traffic congestion on the route from the visitor's home to the urban park led to an increased probability of visiting the urban park by 188.1% (p = 0.044, OR = 2.881) and a decreased probability by 32.3% (p = 0.049, OR = 0.677), respectively. The high probability of visitation was also associated with socio-demographic attributes (including male gender, high income, high and medium education levels, and the elderly) and short travel distances.</p></div>\",\"PeriodicalId\":48396,\"journal\":{\"name\":\"Applied Geography\",\"volume\":\"171 \",\"pages\":\"Article 103374\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Geography\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0143622824001796\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geography","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0143622824001796","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY","Score":null,"Total":0}
The impact of street-scale built environments on urban park visitations: A case study in Wuhan
The COVID-19 pandemic has changed human life globally. Existing studies have revealed that citizens' visitations to urban parks varied before and after the COVID-19 outbreak. However, few studies have examined how street-scale built environments (SBEs) on routes affect visitations to urban parks at varying COVID-19 risk levels. In this study, a stated-preference survey was conducted to investigate 3,218 visitors' changes in urban park visitation under various COVID-19 risk levels. In addition to park visit influencing factors, including park features, neighborhood built environment, socio-demographic attributes, and travel distances, multiple SBE indexes on visitors' routes to parks were obtained from 34,780 Baidu Map street view images using a deep neural network (DeepLabv3+) method. The results suggest that a high GVI and high traffic congestion on the route from the visitor's home to the urban park led to an increased probability of visiting the urban park by 188.1% (p = 0.044, OR = 2.881) and a decreased probability by 32.3% (p = 0.049, OR = 0.677), respectively. The high probability of visitation was also associated with socio-demographic attributes (including male gender, high income, high and medium education levels, and the elderly) and short travel distances.
期刊介绍:
Applied Geography is a journal devoted to the publication of research which utilizes geographic approaches (human, physical, nature-society and GIScience) to resolve human problems that have a spatial dimension. These problems may be related to the assessment, management and allocation of the world physical and/or human resources. The underlying rationale of the journal is that only through a clear understanding of the relevant societal, physical, and coupled natural-humans systems can we resolve such problems. Papers are invited on any theme involving the application of geographical theory and methodology in the resolution of human problems.