Linking migrant enclave residence to employment in urban China: The case of Shanghai

Liu, Cathy Yang; Chen, Jie; Li, Huiping

doi:10.1080/07352166.2017.1413286

Cited by 35 publications

(20 citation statements)

References 41 publications

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“…With an average population of 3,854 people per square kilometers in urban areas, Shanghai has become the first city in China and fifth in the world regarding its population with around 0.66 million people moving in annually. Its population reaching from 16.74 million to 23.02 million during the last decade from 2000 to 2010, increased by 37.53% with more than 24 million residents at the end of 2015 [46]. The main reason for this growth is the large number of migrants and tourists, which made up 39% of the total population of Shanghai in 2010.…”

Section: Study Areamentioning

confidence: 99%

RETRACTED: Spatiotemporal Analysis of Tourists and Residents in Shanghai Based on Location-Based Social Network’s Data from Weibo

Khan

Wan

2020

IJGI

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The aim of this study is to analyze and compare the patterns of behavior of tourists and residents from Location-Based Social Network (LBSN) data in Shanghai, China using various spatiotemporal analysis techniques at different venue categories. The paper presents the applications of location-based social network’s data by exploring the patterns in check-ins over a period of six months. We acquired the geo-location information from one of the most famous Chinese microblogs called Sina-Weibo (Weibo). The extracted data is translated into the Geographical Information Systems (GIS) format, and compared with the help of temporal statistical analysis and kernel density estimation. The venue classification is done by using information regarding the nature of physical locations. The findings reveal that the spatial activities of tourists are more concentrated as compared to those of residents, particularly in downtown, while the residents also visited suburban areas and the temporal activities of tourists varied significantly while the residents’ activities showed relatively stable behavior. These results can be applied in destination management, urban planning, and smart city development.

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Section: Study Areamentioning

confidence: 99%

RETRACTED: Spatiotemporal Analysis of Tourists and Residents in Shanghai Based on Location-Based Social Network’s Data from Weibo

Khan

Wan

2020

IJGI

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“…With an average population of 3854 people per square kilometer in urban areas, Shanghai has become the first city in China and fifth in the world for population density, and around 0.66 million people move in annually. Its population grew from 16.74 million to 23.02 million during the last decade from 2000 to 2010, increasing by 37.53% and more than 24 million residents by the end of 2015 [59]. The main reason for this growth is the large number of migrants, who made up 39% of the total population of Shanghai in 2010.…”

Section: Study Areamentioning

confidence: 99%

Location-Based Social Network’s Data Analysis and Spatio-Temporal Modeling for the Mega City of Shanghai, China

Khan

Wan

2020

IJGI

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The aim of the current study is to analyze and extract the useful patterns from Location-Based Social Network (LBSN) data in Shanghai, China, using different temporal and spatial analysis techniques, along with specific check-in venue categories. This article explores the applications of LBSN data by examining the association between time, frequency of check-ins, and venue classes, based on users’ check-in behavior and the city’s characteristics. The information regarding venue classes is created and categorized by using the nature of physical locations. We acquired the geo-location information from one of the most famous Chinese microblogs called Sina-Weibo (Weibo). The extracted data are translated into the Geographical Information Systems (GIS) format, and after analysis the results are presented in the form of statistical graphs, tables, and spatial heatmaps. SPSS is used for temporal analysis, and Kernel Density Estimation (KDE) is applied based on users’ check-ins with the help of ArcMap and OpenStreetMap for spatial analysis. The findings show various patterns, including more frequent use of LBSN while visiting entertainment and shopping locations, a substantial number of check-ins from educational institutions, and that the density extends to suburban areas mainly because of educational institutions and residential areas. Through analytical results, the usage patterns based on hours of the day, days of the week, and for an entire six months, including by gender, venue category, and frequency distribution of the classes, as well as check-in density all over Shanghai city, are thoroughly demonstrated.

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“…The villages and their surrounding areas contain the floating population for diverse purposes, such as residence, employment, pension and entertainment. The connections with cities and their surrounding areas are complex [13][14][15][16][17]. The characteristics of suburban space are also more sophisticated because of population activities [18,19].…”

Section: Introductionmentioning

confidence: 99%

Spatial Characteristics of Population Activities in Suburban Villages Based on Cellphone Signaling Analysis

Zhou¹,

Hou²,

Dong³

2019

Sustainability

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There are frequent population flow and complex spatial structures in suburban villages. Understanding the spatial characteristics of population activities in suburban villages helps to coordinate the relationship between urban and rural areas and guide the development of suburban villages and the formulation of sound policies. Taking the rural area of Qin and Han New City as the research object, this paper constructs a population time-space analysis framework of “population attribute-activity characteristics-spatial analysis” based on cellphone signaling data. According to the characteristics of the population activity curve, K-means clustering algorithm was used to classify rural space and analyze their characteristics. This study has shown that migrants, who are showed as young and energetic, account for 49.8% of the local registered population per day. Bidirectional flow of residents and commuters is generally presented in urban and rural areas. The urban-rural relation curve was characterized by “double peaks”. The changes in the population in each village and the intensity of urban-rural relation were affected by location, industry and land use. The village population activity curve was classified into three categories, and nine characteristic villages are formed combined with the activity function. The research results can provide a scientific basis for urban and rural planning, spatial planning, industrial guidance and the facility layout.

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Linking migrant enclave residence to employment in urban China: The case of Shanghai

Cited by 35 publications

References 41 publications

RETRACTED: Spatiotemporal Analysis of Tourists and Residents in Shanghai Based on Location-Based Social Network’s Data from Weibo

RETRACTED: Spatiotemporal Analysis of Tourists and Residents in Shanghai Based on Location-Based Social Network’s Data from Weibo

Location-Based Social Network’s Data Analysis and Spatio-Temporal Modeling for the Mega City of Shanghai, China

Spatial Characteristics of Population Activities in Suburban Villages Based on Cellphone Signaling Analysis

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