Migration Networks Pattern of China’s Floating Population from the Perspective of Complex Network

Since China’s reform and opening-up,the growing disparity between urban and rural areas and regions has led to massive migration.With China’s Rural Revitalization Strategy and the industrial transfer from the eastern coastal areas to the inland,the migration direction and pattern of the floating population have undergone certain changes.Using the 2017 China Migrants Dynamic Survey(CMDS),excluding Hong Kong,Macao,and Taiwan regions of China,organized by China’s National Health Commission,the relationship matrix of the floating population is constructed according to the inflow place of the interviewees and their outflow place(the location of the registered residence)in the questionnaire survey.We then apply the complex network model to analyze the migration direction and network pattern of China’s floating population from the city scale.The migration network shows an obvious hierarchical agglomeration.The first-,second-,third-and fourth-tier distribution cities are municipalities directly under the central government,provincial capital cities,major cities in the central and western regions and ordinary cities in all provinces,respectively.The migration trend is from the central and western regions to the eastern coastal areas.The migration network has‘small world’characteristics,forming nine communities.It shows that most node cities in the same community are closely linked and geographically close,indicating that the migration network of floating population is still affected by geographical proximity.Narrowing the urban-rural and regional differences will promote the rational distribution this population.It is necessary to strengthen the reform of the registered residence system,so that the floating population can enjoy urban public services comparable to other populations,and allow migrants to live and work in peace.

An Enhanced Multiview Transformer for Population Density Estimation Using Cellular Mobility Data in Smart City

This paper addresses the problem of predicting population density leveraging cellular station data.As wireless communication devices are commonly used,cellular station data has become integral for estimating population figures and studying their movement,thereby implying significant contributions to urban planning.However,existing research grapples with issues pertinent to preprocessing base station data and the modeling of population prediction.To address this,we propose methodologies for preprocessing cellular station data to eliminate any irregular or redundant data.The preprocessing reveals a distinct cyclical characteristic and high-frequency variation in population shift.Further,we devise a multi-view enhancement model grounded on the Transformer(MVformer),targeting the improvement of the accuracy of extended time-series population predictions.Comparative experiments,conducted on the above-mentioned population dataset using four alternate Transformer-based models,indicate that our proposedMVformer model enhances prediction accuracy by approximately 30%for both univariate and multivariate time-series prediction assignments.The performance of this model in tasks pertaining to population prediction exhibits commendable results.

Research on Cultural Consumption and Urban Integration of Floating Population

This paper examined the relationship between cultural consumption and the floating population’s integration into host cities based on data from China’s Seventh National Population Census and the 2018 China Migrants Dynamic Survey(CMDS).The findings indicate that improving the floating population’s consumption level and quality,especially the quality of development-oriented cultural consumption,can significantly improve the level of their integration.Moreover,development-oriented cultural consumption has a positive effect on the floating population’s integration and social participation,while entertainment-oriented cultural consumption facilitates their integration mainly by improving their sense of well-being.These findings could guide policymakers in developing targeted cultural consumption policies,implementing specific regional industry adjustments,and expanding domestic consumption demand.

Designing an Elderly-Friendly City in Cardiff: Cultivating Sense of Security for the Aging Population: Transforming Butetown for the Entertainment, Health, and Diversification of the Elderly

As an important part of urban construction,elderly-friendly construction is crucial to the formation of an elderly-friendly society,which has been widely recognized internationally.Especially after the COVID-19 pandemic,various organizations around the world have called for changes in public space and urban building planning,with an emphasis on the accessibility of green spaces.This underscores the complexity and difficulty of integrating vulnerable groups of the elderly into cities and using infrastructure and public space.

Origin Distribution Patterns and Floating Population Modeling:Yiwu City as a Destination

Existing quantitative migration studies are mainly at the inter-region or inter-province level for lacking of detailed geo-referenced migration data.Meanwhile,few of them integrate explorative spatial data analysis and spatial regression model into migration analysis.Based on aggregated registered floating population data from 2005 to 2008,the phenomena that population floating to Yiwu City in Zhejiang Province is analyzed at the provincial and county levels.The spatial layout of Yiwu's pull forces is proved as a V-shaped pattern excluding Sichuan Province based on map visualization method.Using the migration ratio in 2007 as an explanatory variable,two models are compared using ordinary least square,spatial error model and spatial lag model methods for county-level data in Jiangxi and Anhui provinces.The model with migration stock provides an improved fitting over the model without migration stock according to the model fitting results.The floating population flocking into Yiwu City from Jiangxi is determined mostly by migration stock while the determinant factors are migration stock and distance to Yiwu City for Anhui.The distance-decay effect is true for migration flow from Anhui to Yiwu City while the distance rule is not confirmed in Jiangxi with the best fitting model.The correlation between per capita net income of rural labor forces and migration ratio is not significant in Jiangxi and significant but at the 0.1 level only in Anhui.Further analysis shows that the distance,income and man-land ratio are important factors to explain population floating at earlier stage.However,as the dynamic population floating process evolves,the determinant factor would be migration stock.

Family Planning Management Of the Floating Population in Xi'an City

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The “Floating Population” in Lhasa City

Lhasa,to some extent,is regarded as a holiday city.It is hard to meet people when they are in a rush. Whenever a pilgrimage procession passes by,you can always see the pilgrims holding their praying wheels, followed by dogs,while they walk peacefully along the path of the pilgrimage.On the edges of streets and laneways,tea bars are teeming with people playing cards or chatting.Once they sit down,they might easily let half a day slip by.

Character and Causes of Population Distribution in Shenyang City,China

Character of population distribution is one of the focuses studied by urban geography. Using the fifth national census data as basic data and using areal interpolation method, this paper analyzes character of urban population dis- tribution of Shenyang City, Northeast China, in terms of three aspects of statistical character, spatial auto-correlation and spatial structure. Furthermore, this research analyzes the factors affecting the population distribution of the city. The main conclusions include: 1) There is an obvious structure character of population distribution in the grid with a grain of 300m, which is appropriate scale when researching population distribution in Shenyang City. 2) Urban population dis- tribution has the character of assembling while population density distribution takes on variability in Shenyang City. 3) Population density distribution shows spatial auto-correlation within 7.36km. Spatial heterogeneity of population density is low. 4) Urban center, population distribution barycenter and population density maximum points separate each other. Population density distribution has multi-cores character. 5) Layout of governments, primary schools, middle schools, colleges, hospitals and marketplaces affects population distribution directly. With the increase of distance to these factors, population density decreases as logarithm.

Spatial and Temporal Changes of Floating Population in China Between 1990 and 2000

By studying the county-level census data of 1990 and 2000, we analyzed the spatial and temporal changes in the floating population in China between 1990 and 2000. The results of the analysis revealed the following characteris- tics. First, the spatial distribution of the migrants (referred to as 'floaters' in this paper) became increasingly concentrated in the cities during the 1990s. Second, the number of floaters increased rapidly during this period, and the area in which the floaters settled expanded quickly into four population explosion belts: the coast, the Changjiang River Delta, the Beijing-Guangzhou Railway and national border belts. Third, the number of inter-province floaters increased rapidly and exceeded that of intra-province floaters in the 1990s. In addition, to obtain a quantitative relationship between the number of floaters and 10 socio-economic variables by using statistical methods and also to find the chiefly important pulling factors of the migration destination, the authors selected approximately 100 cities with the largest population of floaters. Consequently, we found that four factors-GDP, passenger trips per 10,000 persons, per capita GDP and foreign direct investment-could provide an explanation for 83.7% of the number of floaters in 2000. The GDP showed the highest correlation with the number of floaters, suggesting that a highly developed economy is the most important factor that attracts floaters. Furthermore, a fairly close relationship between the number of floaters and the GDP was also found in 2000 for all the counties.

Spatial Pattern of Long-term Residence in the Urban Floating Population of China and its Influencing Factors

Exploring long-term residence among the urban floating population is crucial to understanding urban growth in China,particularly since the 2008 financial crisis.By using China Migrants Dynamic Survey data for 2012–2014,China Labor-force Dynamics Survey data for 2014–2016,and macroscale urban matched data,we analyzed the spatial pattern of long-term residential behavior in China’s urban floating population in 2012–2016 and developed an urban spatial utility equilibrium model containing‘macro’urban factors and‘micro’individual and household factors to explain the pattern.The results first revealed that long-term residence is defined as≥6 yr for the urban floating population in China.Second,members of this population are more likely to be long-term residents of the megacities in the three urban agglomerations in eastern China as well as of small and medium-sized cities in western and northeastern China,whereas short-term residence is more likely in cities in central China and near the three urban agglomerations.Third,urban population density and housing prices,both have a significant U-shaped effect,are main factors affecting the spatial pattern of long-term residence.

Simulation Analysis on Spatial Pattern of Urban Population in Shenyang City,China in Late 20th Century

The spatial distribution of urban population can reflect significantly urban functions and development status. Shenyang, as a typical old industrial city in China, has experienced considerable changes in spatial distribution of population in the process of urban transformation, resulting in the change of urban spatial structure. Based on the sub-district data of Chinese national population censuses in 1982, 1990 and 2000, this study simulates the evolution pattern of spatial distribution of urban population in Shenyang City. Using statistical method and exploratory spatial data analysis (ESDA), we found that the population distribution, on the whole, has presented a balanced and decentralized trend since the 1980s, which characterizes with Chinese suburbanization. Furthermore, based on the investigation of the pattern of population distribution, it is concluded that the negative exponential model fitted the distribution best, and population concentration in the inner suburb kept increasing gradually, meanwhile, the spatial structure of population distribution has presented a polycentric feature since the 1980s. The parameters of the model show that population in the urban core concentrate significantly all the time. The increase of population in the inner suburb influences the population distribution pattern more and more importantly, but the concentration intensity of population cores in inner suburb is still low.

Floating Population Increase and Its Influence on the Urban Population Situation:A Case Study in Beijing

Floating population is a special population group in China resulting from the implementation of household registration system. This paper uses a set of floating population survey data, population censuses data and statistical data to analyze the increase and influence of floating population on the urban population situations in Beijing. It is found that Beijing has experienced a rapid increase of floating population since the 1990s and that the increase of this group has become the key factor of the current population expansion in the city. Its distribution in the urban regions intensified and extended the suburbanization process of the capital. In addition, the population structures of sex, age, education and employment in Beijing have changed to some extent due to the influx of floating population.

Spatio-temporal characteristics and influencing factors of urban floating population in China from 2011 to 2015

Although China’s urban floating population is mainly concentrated in developed cities,from the central and western cities to the eastern developed cities,but the characteristics of the floating population in different cities are significantly different.This paper systematically investigates the spatiotemporal characteristics and influencing factors of the floating population in different levels of cities.The results show that the regional imbalance to further strengthen,accumulation and dispersion trend has become increasingly obvious,liquidity is positively correlated and city level scale,and urban agglomeration and the core city is still polarization center of floating population.Flow range is closely related to urban hierarchy:the higher the intra-urban grade,the more tend to inter-provincial flow;the lower the city grade,the more tend to intra-urban mobility.Short-term(1-2 years)and long-term(more than 7 years)flow-time coexist.The short-term liquidity increases with the city grade,and the long-term liquidity decreases with the city level.Farmers are still the main body of the floating population.Younger age,lower education level,low-skilled,high gender ratio employees are the most basic demographic characteristics of the floating population,although there are differences between different cities.The main reason for affecting the floating population is seeking jobs and doing business.

Migration Laws of Floating Population in Mianyang

Based on the overall analysis of the floating population among big and medium-sized cities in China,this paper, by means of statistics and questionnaires, makes a systematical study on the migratory features of the floating population in Mianyang, its employment structure, migrating causes and channels. According to the findings, the author finds a fact that with the strategy of Western Development, and with the construction of science and technology city of Mianyang, the migrating in Mianyang conforms to the general patterns of the migration, which has happened in those big and medium-sized cities in China.In addition,the city has a new but unique feature — economic factor, as the driving force of population migration, is quite distinct from that of those citiesin eastern areas of China.

Ecological Optimum Population of Binzhou City Based on PEER Model

Taking into account the regional carrying capacity,the population capacity and optimum population of Binzhou City from 2007 to 2017 under certain economic,resource and environmental conditions were calculated based on PEER model.The results show that the population capacity of Binzhou City during 2007-2017 ranged from 6.03 million to 6.43 million,and ecological optimum population was between 5.05 million and 5.34 million.The actual population of the city was between 3.74 million and 3.94 million.The impact of the "two-child" policy on population growth was small,and there was still room for population growth.The population pressure index was greater than 0.7 and less than 1,showing that economic and resource population carrying capacity had certain surplus but were still not optimistic.Environmental pressure index was relatively high,and population carrying capacity was low.

Demand for and Accessibility to Reproductive Health Service of Urban Floating Population

Summary： The demand for knowledge of productive health and the current status of productive health services provided by relevant governmental institutions were qualitatively and quantitatively studied. The study identified the key factors that influenced the demand for the productive health services and results of the services. It also discussed the effective approaches to control, planning and sustainable development of the reproductive health services for the floating populations.

Influencing Factors and Urbanization Effects of the Spatial Pattern of Floating Population in Anhui Province

Based on the population census data,this paper analyzed the influencing factors and urbanization effects of the floating population in Anhui Province using ArcGIS spatial analysis,factor analysis,multiple liner regression,and spatial autocorrelation,and reached the following conclusions:① From 2000 to 2010,the floating population in Anhui Province was concentrated in cities dotted the Huai River and the Yangtze River,and Hefei City absorbed the most inter-provincial floating population and intra-provincial floating population.② The overall economic strength had the greatest impact on attracting floating population,while the income level factor has less impact on attracting floating population.The overall economic strength and the strength of science,education,culture,and health of prefecture-level cities in Anhui Province were more attractive to the intra-provincial floating population and less attractive to the inter-provincial floating population.③ Population mobility promoted urbanization.Large cities could attract more migrants from counties.The urban population system in Anhui Province was generally developing towards the concentration of large cities,while the proportion of the county population in the total population was decreased.

The Population Carrying Capacity of Water Resources in Yulin City

Assessing the water resource carrying capacity is beneficial for measuring the scale of industry and population agglomeration,and also avoiding the contradiction between increasing people and decreasing available water resource,due to the expansion of industry and city size.Based on the prediction model of optimum population development size,by using hydrological data,also with the demographic data from 1956 to 2010,this article analyzes and predicts the urban moderate scale under the limit of the water resource in the future of Yulin City by GIS. The main conclusions are as follows. There is growing tendency of water resources overloading. According to the result of model simulation,by2015,the overload rate of population size will be 1. 04. By 2020,the overload rate of population size will grow up to 1. 08. The oversized population mainly comes from cities and towns. The overload rate for cities and towns in 2015 and 2020 is 1. 89 and 1. 73,respectively. With the expansion of cities and industries,suburban areas could have a great potential for carrying population,because lots of suburban people may move to cities and towns according to prediction. In view of the above-mentioned facts,the population size should be controlled in a reasonable range.

The Analysis on social determinants of health of the floating population

Health literacy refers to the individual obtaining and understanding and dealing with the basic health information and/or services and the ability of use the information and services to make good health decisions.At present, research works related to health literacy in our country are in the initial stage, the information of floating population health literacy is blank, the Chinese Health Education Center （formerly the Chinese Disease Prevention and Control Center Health Education） Ministry of Social welfare studies undertaken special ＂Chinese public health Literacy survey and evaluation System ＂to develop a suitable evaluation index system of health literacy of the public, used for evaluation of our country＇ s public health literacy level. October to December 2007, the Chinese health education center of this set of evaluation index in Jinan Shandong province examines the health literacy status of floating population, analysis the influence factors of health literacy of the floating population, for the national macroeconomic regulation and control of the floating population, the rational allocation of health resources, determine priority health work, and provide evidence for health related policies and regulations of the floating population.

Influencing Factors of Long-Term Residence Intention of Highly Educated Inter-Provincial and Intra-Provincial Floating Population From the Perspective of Social Integration:Take Guangdong Province for Example

Floating population plays an important role in the development of cities,regions,and countries.The economic growth path with Guangdong characteristics is inseparable from the support of highly educated groups.Studying the long-term residence intention of the highly educated floating population is helpful for the city to attract and retain talents.From the perspective of social integration,using CMDS 2017 data and taking Guangdong Province for example,this paper studies the influencing factors of long-term residence intention through SPSS logistic regression,taking intra-provincial and inter-provincial floating population with a bachelor’s degree or above as sample.The main conclusions are:(1)Marital and childbearing status is the primitive influencing factor of long-term residence intention among intra-provincial and inter-provincial floating population.Samples with high income,under social insurance system,being female and having non-agricultural hukou,are tend to prefer long-term residence.Samples who connect with the locals and participate in social public welfare are more likely to stay.(2)Personal age and city livability have a significant positive impact on the long-term residence intention of the inter-provincial highly educated floating population,but agricultural hukou and self-employed laborer status will weaken the long-term residence intention of this group.(3)Participation in townsmen/alumni association has a positive effect on the long-term residence intention of the intra-provincial highly educated floating population,and connection with outlanders also promotes the long-term residence intention of this group.(4)The long-term residence intention of inter-provincial highly educated floating population is usually based on reality,therefore they pay more attention to the development,changes,and livability of the destination city.However,the long-term residence intention of intra-provincial highly educated floating population is usually based on perception,so they pay more attention to whether they like the city.Compared with intra-provincial flows,inter-provincial flows have higher economic and emotional migration costs,more institutional barriers,and more life adaptation problems.Therefore,the government should introduce targeted measures to promote social integration and improve long-term residence intention.