{"title":"韩国城市扩张对都市圈通勤模式的影响","authors":"Nayoung Ryu, Insu Hong","doi":"10.16879/JKCA.2020.20.3.073","DOIUrl":null,"url":null,"abstract":"The purpose of this paper is to analyze the impacts of urban sprawl on the commuting patterns of the Metropolitan Regions in Korea. Sprawl related indexes and socio-economic metrics as explanatory variables and commuting patterns using a privately-owned car (Model 1) and public transportation (Model 2) as dependent variables construct two OLS models. Spatial regression models and GWR models reflecting spatial dependence and/or spatial heterogeneity are also executed to investigate the relationship between urban sprawl and commuting patterns. The results are as follows. First, the goodness-of-fit of both models improve from OLS to spatial regression and GWR. Second, density among sprawl indexes is strongly significant related with commuting patterns. Street accessibility in Model 1 and land use mix in Model 2 are slightly related with commuting patterns in specific regions. Third, GWR models show significant socio-economic variables in certain regions which are not detected in OLS or spatial regression models.","PeriodicalId":132041,"journal":{"name":"Journal of the Korean Cartographic Association","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Impacts of Urban Sprawl on the Commuting Patterns of the Metropolitan Regions in Korea\",\"authors\":\"Nayoung Ryu, Insu Hong\",\"doi\":\"10.16879/JKCA.2020.20.3.073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The purpose of this paper is to analyze the impacts of urban sprawl on the commuting patterns of the Metropolitan Regions in Korea. Sprawl related indexes and socio-economic metrics as explanatory variables and commuting patterns using a privately-owned car (Model 1) and public transportation (Model 2) as dependent variables construct two OLS models. Spatial regression models and GWR models reflecting spatial dependence and/or spatial heterogeneity are also executed to investigate the relationship between urban sprawl and commuting patterns. The results are as follows. First, the goodness-of-fit of both models improve from OLS to spatial regression and GWR. Second, density among sprawl indexes is strongly significant related with commuting patterns. Street accessibility in Model 1 and land use mix in Model 2 are slightly related with commuting patterns in specific regions. Third, GWR models show significant socio-economic variables in certain regions which are not detected in OLS or spatial regression models.\",\"PeriodicalId\":132041,\"journal\":{\"name\":\"Journal of the Korean Cartographic Association\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Korean Cartographic Association\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.16879/JKCA.2020.20.3.073\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Korean Cartographic Association","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.16879/JKCA.2020.20.3.073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Impacts of Urban Sprawl on the Commuting Patterns of the Metropolitan Regions in Korea
The purpose of this paper is to analyze the impacts of urban sprawl on the commuting patterns of the Metropolitan Regions in Korea. Sprawl related indexes and socio-economic metrics as explanatory variables and commuting patterns using a privately-owned car (Model 1) and public transportation (Model 2) as dependent variables construct two OLS models. Spatial regression models and GWR models reflecting spatial dependence and/or spatial heterogeneity are also executed to investigate the relationship between urban sprawl and commuting patterns. The results are as follows. First, the goodness-of-fit of both models improve from OLS to spatial regression and GWR. Second, density among sprawl indexes is strongly significant related with commuting patterns. Street accessibility in Model 1 and land use mix in Model 2 are slightly related with commuting patterns in specific regions. Third, GWR models show significant socio-economic variables in certain regions which are not detected in OLS or spatial regression models.