Simulations based on spatial interaction models have been widely applied to understand the strength of relationships between geographical elements, but many issues remain unclear and deviations between actual and simulated results have often been seriously underestimated. A high-precision Baidu migration process combined with mass relationships is applied in this study and enables the generation of regression coefficients of gravity model based on programmed large-scale regression simulations. A series of accuracy assessments are then developed for 2015 empirical projection daily regression coefficients that can be applied to Chinese spring interprovincial mobile gravity model variables as well as spatiotemporal research that utilizes regression coefficients within a heterogeneity research model. This approach also enables the error within the gravity model to be assessed in terms of floating population simulations. The results of this analysis lead to a number of clear conclusions, including the fact that parameter calibration complexity for the Chinese population mobility gravity model is reflected in the degree of influence asymmetry within spatial object interaction variables, and that the spatial heterogeneity of the variable regression coefficient increases in two distinct fashions. The first of these increases has to do with the overall influence of specific variables, including the fact that differences between proxies tend to be higher than inflow-outflow characteristics. In contrast, the second set of increases is related to economic levels, industrial scales, the proportion of the tertiary industry, and public service facilities. In this latter case, two-way population flow exerts a more profound influence on results and thus the scope of possible explanations for phenomena is more extensive. The regression coefficient for the existence of positive and negative proxy variables therefore relates to differences in spatial heterogeneity, including at the city level, and also assumes that floating population gravity model regression coefficients ignore spatiotemporal changes in the heterogeneity coefficient. This leads to spatial differences in estimated results and thus convergence trends, but further enables the identification of anisotropic interactions in extension space. The second main conclusion of this research is that the national scale population flow distance attenuation coefficient was 1.970 during the spring of 2015, while at the level of prefectural administrative units and given population outflow, the range encapsulated by this coefficient fell between 0.712 (Zhumadian) and 7.699 (Urumqi). Data also reveal a population inflow coefficient of 0.792 for this year that ranged as high as 8.223 in both Sanya and Urumqi. Population flow simulation results using the gravity model and including Baidu migration measured flow data were also subject to significant error. Third, the results of this analysis reveal a total fitting error of 85.54% in weighted absolute mean; the spatial interaction effect within this is responsible for a maximum error of 86.09% in actual and simulated flows, while relative outflow force and attractiveness encompass 57.73% and 49.34% of model error, respectively. These results show that the spatial interaction effect remains most difficult to model in terms of current factors.

According to previous studies, not only does the conditional gravity model based on ordinary least squares often bring about poor fitting of migration flows in reality, but also there exists overdispersion in the extended Poisson gravity model. Simultaneously, network autocorrelation usually exists in population migration data （e.g., the spatial interaction among migration flows). The problems mentioned above result in biased estimation. In order to capture network autocorrelation and deal with the issue of overdispersion, we build an eigenvector spatial filtering negative binomial gravity model (ESF NBGM) based on the data of 1% national population sample survey in 2015, to analyze the driving mechanism of interprovincial population migration flows in China. The results are as follows: (1) Positive spatial spillover effect exists in interprovincial population migration flows, and ESF can capture network autocorrelation in data, so as to reduce the estimated deviation of the model. Furthermore, eigenvectors ranking top 1.4% can properly interpret the spatial pattern of high network autocorrelation in data. (2) There exists overdispersion in China's interprovincial migration flows. Considering this problem, a negative binomial regression model is more suitable for the estimation of driving mechanism for population migration, together with statistical enhancement. (3) Network autocorrelation leads to overestimation of distance variables and underestimation of non-distance variables. The results of the improved model reveal that: chief factors the affect driving mechanism are regional population characters, social network, economic development and education level. Meanwhile, living environment and road network gradually become one of the most crucial pulling factors that influence migration flows. (4) Compared to previous studies, social network (i.e. migration stock) plays a more significant role in population migration flows, while the impact of spatial distance keeps weakening.

With the rapid development of regional integration, nowadays the regional inter-city migration gets the more attention of the scholars at home and abroad. Micro-blog, as one of the most popular application in China, has become a hotspot of research in areas such as sociology and computer. Check-in, as one of Micro-blog's functions, can reflect the flow of inter-city population in real time. We used the crawler program to collect the research samples in the Chengdu-Chongqing urban agglomeration in January 2014. The information includes the Micro-blog's unique ID number, the grid coordinates of Micro-blog sending place, and the city code of the registered place, etc. By running this program, a total of 804204 valid Micro-blog check-in data weare obtained from the Chengdu-Chongqing urban agglomeration. Based on Micro-blog checking areas, this study analyzeds the spatial structure of the Chengdu-Chongqing urban agglomeration. And Wwe combined the micro-blog data with the traditional socioeconomic data, in order to analyze the impact factors of the regional migration. The results indicates that the spatial structure of micro-blog shows the characteristics of "many centers of dual-core" group in this area. There are only two cities whose micro-blog flows are more than 100,000. They are Chengdu and Chongqing, forming athe “dual-core”. The direction of Micro-blog flow is affected by administrative division, and the intensity of Micro-blog flow presents a certain grade difference. The network shows an obvious hierarchy, and it closely correlatesnnects with the actual social-economic area closely, such as GDP, population size and the strength of traffic connection. For Chengdu and Chongqing, its GDP ranksed first and second,1, 2 respectively, with athe population size all of greater than 7.59 million and both as a regional transport hubs, it makes their micro-blogWeibo flows areintensity in ranked 1st and, 2nd, places respectively. Lastly, there are still some differences between Micro-blog's space and the actual geographic space inof Chengdu-Chongqing urban agglomeration. In the background of the national Yangtze River Economic Belt and China's new urbanization, we put the network information into the geographical space. Actually In this paper we discovered the spatial network characteristics of Chengdu-Chongqing urban agglomeration, and then this paper pointeds out the influence of socioeconomic factors on Micro-blog cyberspace flow. Of course, there may still be other factors behind Micro-blog's cyberspace, which need to be explored and analyzed in the future.

In this paper, the urbanization of China's population was subdivided into "townization" and "cityization", and the indicators of "townization level" and "townization contribution rate" were adopted. From the perspective of different spatial scales and major function oriented zones, this paper conducted the system analysis on space-time disparity and influencing factors of the development of urban population in China from 1982 to 2015. The main conclusions included: (1) China's urban population's "townization level" and "townization contribution rate" continued to increase. In 2015, townization level was 41.8%, and the townization contribution rate was 55.1% during the period from 2010 to 2015. (2) The urbanization of China's urban population presented significant spatial and temporal differences. The townization-dominated counties and cities were mainly distributed in the central and western regions of China, accounting for more than 70% of the country's total land area. The cityization-dominated counties and cities were mainly concentrated in coastal urban agglomerations, and had a relatively small proportion in the national land area. (3) Looking into the future, China's urban population's "townization level" and "townization contribution rate" would increase steadily but slower and slower. It was necessary to strengthen the exploration of a differentiated development model of small towns based on the differentiation of major function oriented zones.

The unequal urban-rural relation in the pre-reform period has been shifted into urban areas in the form of unequal intra-urban relation between residents with local hukou and floating population without local hukou. Thus current urbanization of China is incomplete and not inclusive. To achieve complete urbanization in China, attention should be paid to three important aspects: the usual rural to urban migration, the integration or inclusion of floating population in urban areas, and the urban-rural integration in the urban periphery. The government and enterprises are partly responsible for the problems facing the temporary population. The paper discusses the basic theories of urbanization in the context of hukou system as well as the theories of urban integration of floating population. The author argues that the system approach should be used to study the urbanization and urban-rural integration issues. The approach can be applied to the planning, development, construction and expansion of people-nature symbio-tic systems at various scales. A new town example from Hong Kong is used to demonstrate what kind of sustainable communities may be planned and developed to meet the aspiration of residents in modern cities.

Under the background of human-oriented new-type urbanization, the citizenization of rural migrants attracted more and more attention from scholars and governments in recent years. On the basis of analyzing the China's urbanization and behavioral agencies, the paper indicated major difficulties facing the rural migrants in the process of social integration. The main findings are as follows: (1) the government, firm and individual are three main behavioral agencies in the process of urbanization in China, and their interaction is the main cause leading to the appearances of social exclusion. (2) The central government is mainly in charge of guiding the overall development of national urbanization by making top-level policies, while local governments play an important part in promoting local urbanization. However, by mean of the household registration system, local governments pay more attention to the economic development, and generally exclude the rural migrants from other administrative units to share the equal welfare together with the local residents. (3) Most China's firms mainly undertake labor-intensive industries, and most of them adopt low-wage and low-social security policies to decrease the productive cost. These measures result in low wages and low social security level for rural migrants and hinder their social integration. (4) The human capital characteristics of individuals also have an important influence on the social integration of floating population. Generally, the rural migrants with more human capitals (well-educated, younger, etc.) are more likely to integrate themselves into local society. Among the three behavioral agencies, the rural migrants are no doubt in the weakest status, and the institutional obstacles hinder them to embed in the urban society. In the end, some suggestions were proposed to promote the social integration of rural migrants. Firstly, we should deepen the reform of the household registration system, build an inclusive city, and promote the equalization of basic public services. Secondly, the government, firms and individuals should share the cost to realize citizenship.

The Guangdong-Hong Kong-Macao Greater Bay Area with economic geographical advantages is deemed to be the growth point that captivated the world for its impetus to the global economy. This article focuses on the nine main cities of the Pearl River Delta, analyzing the mutual influences among industry-population-space during the rapid development process of this urban agglomeration by constructing a vector auto regressive model and impulse response function and variance decomposition analysis. The results show that: The absorption effect for population in the development of industry in the urban agglomeration of the Pearl River Delta faded in the late stage. The acceleration that industry benefitted from population aggregation weakened in the middle and late periods. The spatial expansion effects on population aggregation were limited and have become negative in the late period. It concludes that in general a short-term mutual promoting development mechanism between industry-population-space was formed, but a long-term mechanism is yet to be developed. In order to promote the development of the Greater Bay Area of Guangdong-Hong Kong-Macao, the urban agglomeration of the Pearl River Delta should attract highly-qualified workforce on the basis of industrial upgrading, plan spatial growth according to the population aggregation, and construct a multilevel synergistic industrial space with complementary products and services. With these measures, the overall aims are to strengthen the synergistic development among industry, population, and space and promote the development of the Greater Bay Area of Guangdong-Hong Kong-Macao.

Urban population data are the basic data in various social and economy fields, and high-resolution spatialized urban population data are of great importance for the research in such fields. In this article, multi-source remote sensing data were used to extract the urban impervious surface changes in the Guangdong-Hong Kong-Macao (GHM) Greater Bay Area at a spatial resolution of 30 meters from 2007 to 2015. The Dasymetric mapping method was used to spatialize the population at different times to a resolution of 30 meters. We finally estimated the gridded population density distribution of 30 meters resolution, and analyzed the spatiotemporal changes of the urban population in the GHM Greater Bay Area from 2007 to 2015. Validated with Google Earth time series high-resolution images, the accuracy of the derived urban impervious surfaces in GHM is generally above 80%. Using the county-level demographic data, the consistency between the estimated population and the statistical data in the GHM Greater Bay Area was analyzed, and the correlation coefficient (R²) was generally above 0.7. Finally, according to the spatial distribution of urban population and the change of population density, urban expansion and population increase patterns of different cities in the GHM Greater Bay Area were analyzed. The research shows that the urban population of the GHM has special spatiotemporal characteristics: (1) Stable population distribution is observed for Hong Kong and Macao, but other urban areas have experienced expansion of population to different extents and in different directions. The population expansion of Guangzhou, Shenzhen, and Dongguan is most obvious. (2) The spatial distribution of urban population in GHM shows multi-scale and multi-center characteristics. In general, the population of GHM is concentrated in the core area centered at the Pearl River Estuary. The Zhaoqing, Jiangmen, and Huizhou areas are sparsely populated. In the core area, the distribution of urban population shows the characteristics of multi-center distribution on both urban and metropolitan scales. Hong Kong and Guangzhou have multiple urban centers, while Hong Kong, Macao, Shenzhen, and Guangzhou are the centers of the GHM. These four centers can drive the overall development of the GHM Greater Bay Area.

Residential segregation has been a severe and widespread phenomenon in mega cities along with fast urbanization in China. Migrants from rural area flock into developed cities especially coastal regions for better job opportunities, which provide essential cheap labor for urban growth. However, their housing problems could not be resolved in formal housing either hindered by institutional barrier or unreachable housing price. The housing segregation gradually formed as locals reside in formal gated communities while migrants crowd in informal housing like urban villages, which is characterized with lower rent but substandard living conditions. The housing segregation in China derives from household registration system (hukou). The Index of Dissimilarity (ID) only emphasizes the unevenness of population distribution but could not fully manifest the segregation characteristics in density, location, proximity, etc. Inspired by the work of Massey Denton in multi-dimensional segregation, this article applies three measures of housing segregation (Clustering, Centralization, and Concentration) based on the ID to analyze the segregation between urban residents with and without hukou. It examines the multi-dimensional housing segregation based on hukou status using data from China’s 6th national census in 2010. The typical migrant city Shenzhen was chosen to conduct the case study, and the segregation index of three dimensions was calculated based on 55 sub-districts for comparison. The multi-dimensional segregation indexes showed that Shenzhen has high segregation problems at the city scale, but more homogeneous inside each district. The history, industrial structure and socioeconomic background of each district play a crucial role in the segregation. The outside-custom area provides more chances in labor-dense sectors and attracts more migrants to reside in a large scale, while the inside-custom regions are more advanced in informatics and financial sectors, which results in scattered spots of migrants housing. Cluster analysis reveals the three types of segregation, each of which has its unique processual mechanisms, and policy prescriptions. The study shows that the housing segregation has multiple dimensions and scales. Thus two sets of people could be featured by a single ID yet to be clustered or dispersed, central or peripheral, or concentrated or deconcentrated. Migrants may occupy continuous neighboring blocks in peripheral area, or densely reside in few scattered urban villages in inner city, or congregate in factory dorms alongside each industrial zone. Based on segregation patterns, locations and density, local governments should take different measures like redevelopment of targeted urban villages, large-scale public housing construction or cooperation with factories in worker dormitory improvement accordingly. This article contributes an innovative and comprehensive perspective to conceptualize housing segregation, and provides policy recommendations to deal with the social problems that arise from segregation in China. With the advancement of big data, more practical real-time housing management measures could be developed for practitioners to provide human-centric housing planning and avoid the housing polarization.

A large floating population has entered urban areas under the rapid urbanization in China. However, their residential space pattern is strongly affected by residential self-selection, which has reconstructed the urban population distribution pattern and social space. This study examines urban floating population residential space pattern and its formation process, by using the floating population data of 2010 and 2015 in the yearbooks of Chengdu downtown block, and choosing influence variables from the perspective of behavioral decision made by the urban floating population. Therefore, the aims of this study are to analyze the influence of urban characteristic variables for residential self-selection and the influences' spatial differentiation, and to reveal process of space trade-offs in residential self-selection and its role in the formation of urban floating population residential space pattern. The results show that from 2010 to 2015, the urban floating population of Chengdu increased rapidly in the southern part of the downtown area and in the urban centers, and a significant space agglomeration situation featured by low-west and high-east is obviously reflected. Moreover, residential space pattern of urban floating population shows that the level of residential segregation is partially related to the residential space pattern of the registered population, but a notable degree of residential segregation has reduced from 2010 to 2015. More importantly, the study proves that the proportion of urban floating population in permanent residential population, residential land area, housing rent, public transportation, enterprise, hospital, drugstore, restaurant and marketplace have influences on floating population residential self-selection. In addition, the proportion of urban floating population in permanent residential population, residential land area and housing rent are the three significant variables in the spatial error model, but it is dramatically impacted by spatial autocorrelation of floating population statistic block. A major contribution of this study is that the spatial differentiation of the variables' influence on residential self-selection is verified by using geographic weighting regression (GWR), and it reveals the process of urban floating population space trade-offs on how to realize residential self-selection by weighting spatial variability of variables’ influence among different urban regions. That is to say, the spatial difference of living cost, employment opportunities, living environment and commuting costs have shaped the floating population residential space pattern, which is a complex reflection of the urban spatial perception, spatial trade-offs and spatial self-selection of floating population. It can help us to deeply understand the formation process of urban floating population residential space pattern, and provide references to promote community integration and urban management.

After the financial crisis in 2008, a new phenomenon “shrinkage” has appeared in Dongguan’s urban area, which manifested population size reducing in its towns. Although the economic recovery rapidly in the post-crisis period, the spatial separation of population growth and shrinkage is aggravating, accompanied by a series of changes in the demographic structure. Base on the perspective of demographic change, this article makes an in-depth analysis of the growth and shrinkage in Dongguan by using the Social Security Registration data. We summarize the characteristic of demographic changes in the size, age, gender and education after the financial crisis, and industrial economic structure of different towns. Moreover, we construct a panel regression model for exploring the factors and mechanisms that affect urban population growth and shrinkage. The result shows: 1) While the population size of Dongguan tends to growing in fluctuation, the population structure shows trends for migrant population localization, male and female more imbalance, younger and highly educated population. 2) Advanced manufacturing and modern service industries to promote city growing, and outward processing and manufacturing transformation failure will affect the city shrinking. 3) The spatial distribution shows the "growing in the north, shrinking in the south", forming a concentrated area where the central area growing, the northwest area and the southeastern area are shrinking. 4) Macroeconomic fluctuation, industrial transformation, technological innovation inputs and local development pathway have significant impacts on demographic growth and shrinkage in Dongguan.

The space pattern of urban population distribution is a classical research topic of urban science and urban planning. In terms of the current research situation of urban population distribution, the LBS big data technology which is considered as a new method and tool to observe the urban spatial and temporal characteristics is introduced into the research of urban population distribution based on the traditional space syntax model. Then, a new idea of urban population distribution research with the integration of theoretical distribution and actual distribution is established. The case study in the central urban area of Hefei City shows that: the spatial clustering areas obtained respectively by space syntax model and LBS big data analyses are different in space. According to the comprehensive comparison of space syntax model and LBS big data analysis, the central urban area of Hefei City is divided into 3 types of population distribution including high density, medium density and low density. The high density zoning consists of the old town, Shushan district and Baohe district. The medium density zoning includes Binhu district, Luyang district and High-tech area. Meanwhile, the low density zoning consists of economic developing area and Yaohai district. Finally, the suggestions of population distribution development in different density partitions are proposed. The research shows that the timely and dynamic characteristics of LBS big data can make up for the shortcomings of traditional data and greatly broaden the source and timeliness of basic data. Obviously, this will enhance the accuracy of the study. And, more importantly, it will provide more accurate and efficient tools and methods combined with the classical space syntax model for the study of urban population distribution. In addition, it is hoped that this research can make some exploration and reference for expanding the practical application field of LBS big data.

Economic development zones play an important role in urban and regional development. They have become a magnet for capital and migrant flows, which stimulate various production relations, and gradually turn into new social space, with important significance to inclusive urban and regional development. Previous efforts of special economic zones, however, place great emphasis on economic development, with few considerations of social development. Although this problem has attracted much attention, there is lack of a systematic view of livelihood of migrants, which results in incomplete understanding and policy approaches to improve social inclusive development of economic development zones. With an empirical study on Nansha New District in Guangzhou, this paper attempts to establish a multidimensional analytical framework of livelihood space to facilitate an understanding of livelihood capital of migrants. The result shows that the livelihood space of migrants in the economic development zone has both expansion and compression compared to their hometowns or other areas. Migrants in Nansha have dramatically improved their livelihood. But compared to the locals, their livelihood capital is still lower. Overall, their economic space has been extended, while the policy space, public service space and residential space are compressed. The compression and extension of the livelihood space of migrants has the relationship of mutual restraint or promotion, which together constructs the unique livelihood space of migrants. The household registration system is an important influencing factor. In addition, the willingness of migrants to stay in the development zone has complex formation mechanism and livelihood capital shows little impact. Therefore, a better livelihood space of the migrants in the development zone is of great significance to improve the living conditions of industrial workers in the city and shape the development strategy of inclusive urban development. These findings can contribute to Lefebvre's theory of space production, pointing out that there is a continual process from production to social space and the latter is increasingly important.

The spatial and temporal coupling relationship between rural residential land and population is the theoretical base for optimizing rural land resources. This paper aims to analyze the sequential variation characteristics, spatial heterogeneity rules and coupling relationship types of Chinese rural land resource and population. Demographic data and land survey data are analyzed with elastic coefficient model. The main research results include: 1) During 2007-2015, rural residential land linearly increased at an average annual rate of 1.94%, and totally increased 257.27×10⁴ hm². 2) Per capita residential land area of rural population and agriculture population increased at an average annual rate of 4.61% and 1.98%, respectively, and the gap between them was widen at an average annual rate of 16.2%. 3) The coupling relationship between rural residential land and rural population was type G (land area increase, population decrease and the former grows less rapidly than the latter) unbalanced development at national scale, and was type G or type H (land area increase, population decrease and the former grows faster than the latter) unbalanced development in all provinces. The coupling relationship between rural residential land and agriculture population was type H unbalanced development at national scale, and was unbalanced in 93.55% provinces. The research results indicated that the coupling relationship between rural residential land and rural population was unbalanced development in China during 2007-2015. This research could provide scientific supports for optimizing rural land resources and promoting coordinated development of rural man-land relationship.

Urbanization is an inevitable trend of modernization and the fundamental transition in socioeconomic structure, human production and life style. China is undergoing a rapid and unprecedented urbanization process, and has achieved the short-term goals that European and American countries attained in the past decades or even centuries ago. This kind of rapid expansion has inevitably led to a serious imbalance between urban land expansion and urban population growth. We used the demographic-landscape urbanization coupling relationship index (ratio of the annual average growth rate of demographic permanent population and urban development land) to explore the spatio-temporal characteristics of demographic-landscape urbanization coupling situation, and further explain its driving forces during the past decade in China. All analyses, based on the demographic statistics and landscape dataset of 636 cities in China, aimed to identify and diagnose six coupling types. Furthermore, we made the macro pattern of urbanization development level more visible with the help of Kernel Density spatial analysis tool. Results show that: (1) Over the past decade, the average annual growth rate of urban development land in China was 1.65 times that of the urban population, and demographic-landscape urbanization coupling situation was poorly coordinated. (2) We found that there is a spatial dependency between demographic urbanization and landscape urbanization. Moreover, the spatial agglomeration center of high-density urban population showed a gradual westward moving trend. Meanwhile, urbanization development mode shifted from "land lag" to "population lag". (3) Generally, the area of per capita urban development land has exceeded the standard threshold; and 41.96% of the cities currently have a development land area per capita more than five times of the ideal value. (4) The proportion of three coordination types was 73.25%, which is much higher than that of three incoordination types (26.75%). Among them, "Both Growth and Uncoordinated Type" took the largest proportion of 43.27%, which reflects the uncoordinated relationship between demographic urbanization and landscape urbanization. This situation will continue or even is intensified in the years to come. Additionally, the cities located at the edge of urban agglomeration seemed to be more uncoordinated than cities at the center. This is probably because that the cities at the edge of urban agglomeration, which had a small population and low property price, relied more on the "land finance" to earn their main source of urban economic income. (5) Economic development level, population size, governmental decision-making behaviors, geographical location and regional disparity were all driving factors of demographic-landscape urbanization. In addition, there are few obvious differences in the mechanism and effect of these factors. To sum up, urban population and land use management in the new era should get more attention according to the new trend in system diagnosis and comprehensive analysis, thus to provide a scientific basis in development decision for new urbanization and urban-rural integration strategy as well as the rural revitalization strategy.

Based on multiple types of data and using qualitative and quantitative analysis, the paper analyzes the spatial-temporal characteristics and influencing factors of population changes in Beijing-Tianjin-Hebei (BTH) region from the two aspects of population distribution patterns and population floating in long and short periods. The main results are summed up as follows: (1) BTH region presents an obvious population distribution characteristic, which is influenced by physiographical conditions and traffic location factors; Beijing-Tianjin region reflects the prominent circle features, which is due to social and economic development; and Hebei lacks a mature regional sub-center. From 2000 to 2010, the population of this region is characterized by a significant growth. (2) Over a long period of time, the vitality of population floating has increased and the pattern of population floating is more concentrated. Over a short period of time, Beijing and Tianjin have become the hottest cities of population inflow and outflow respectively in China. The population floating among Beijing, Tianjin and Langfang is the most active, while the Beijing-centered population floating is relatively active. (3) The main influencing factors of the spatial-temporal change of population over a long period of time include human capital accumulation, industrial structure, urbanization, initial economic development level, rurality and public services, geographical location, central city radiation and topographic relief. Holidays and seasons are the important superimposed factors that affect the direction and quantity of short-term population movements.

Based on the national census data of 2000 and 2010 as well as population sample survey of 2005 and 2015, this article utilizes the interaction value to analyze the dynamics of floating population in China. The analysis of "population floating system" demonstrates that: (1) Floating population shows great aggregation, in which exist several "population floating systems". (2) The development of the Yangtze River Delta and the Bohai Economic Rim has witnessed the northward trend of the floating population. (3) The improving inter-provincial connections among the western region has gradually strengthened its importance in China since 2010. In addition, the unidirectional interaction value can not only indicate the scale of the population flows but also explain their directions: (1) The largest unidirectional interaction flow occurs mainly between provinces in eastern China and those in central or western China which are exporters of labor forces. Even though eastern China gathered most of the floating population, some provinces have gradually lost their dominance in attracting population from central and western China. (2) The floating population in China presents a "asymmetric bilateral pattern". With the decline of the three major population centers, return flows have become remarkable. (3) Some sub-centers of floating population emerged in the central and western regions, though they are still developing. (4) Population nearby floating has become increasingly prominent in the western region. According to the analysis above, population research can benefit from the interaction value model by considering the inter-provincial population flows among the whole system and presenting their directions. Meanwhile, making comparison of population flows between 2010-2015 for a better understanding of the new characteristics and patterns of floating population is meaningful in formulating population policies and promote regional coordination.

While population maps are important tools for people to perceive the regularities of population distribution, different scales of population maps cause map readers' cognitive difference in the regularities of spatial distribution of population. In this paper, eye movement parameters such as number of fixations, fixation duration and number of correct answers were selected in the population map cognitive experiment by eye movement tracking to test the significance of the difference, and the results were analyzed from the perspective of spatial differentiation regularities. By exploring the influence of different scales including province and county (city) on map readers' cognition of the distribution regularities of population, it is concluded that different scales of population maps have a significant impact on readers' perception based on the significant difference analysis. When perceiving the characteristics of spatial distribution of population and the population quantity, more details and information are provided by county (city)-scale population maps, which is beneficial to readers' understanding of the spatial differentiation regularities of population, with less average number of fixations, shorter average fixation duration, more correct number of answers for each question and higher cognitive efficiency. The impact of scale on the cognition of the population spatial distribution and the population size was discussed. The acquired cognitive rules of the scale can be used in designing the demographic maps and shortening readers' cognition time, which is convenient for readers to extract valid information from the demographic maps, thus to improve the map usability. Besides, through the analysis of eye movement parameters like the fixations points, fixation time and number of correct answers, as well as the significance test, quantitative researches of the scale effects on the population distribution were carried out. The perspective drawing of the fixations hotspot can be used to visualize the cognitive spatial differentiation of the readers. And the results are no longer limited to the simple qualitative expression, which is of great significance for the use of different scales of demographic maps to express population distribution characteristics and regularities. In addition to adopting the hierarchical mapping method to draw the population maps, this thesis also has conducted experiments on the readers' cognition of the spatial distribution regularities of population with different population density maps at different scales. Since it can reflect the population distribution more precisely and more visually, the results of this research may be further improved. And in the further work, the above population map needs further studying.

Urban population distribution and activities are always the hot research topics. Identifying the spatial-temporal variation and predicting future trends are of great significance for estimating population accurately, making policy effectively, and warning of population booming timely. With the availability of data and the development of data processing technique, multisource data with both spatial and temporal features, such as mobile signaling data, have been used in population studies. In this paper, q-statistic was firstly applied as an exploratory analysis, then Bayesian spatial-temporal models were used to evaluate patterns of urban population and make prediction of future trends. The Chaoyang, Beijing in 2017 was selected as empirical study of this model. The spatially stratified heterogeneity was detected by q-statistic in Geodetector firstly. Then we explored the overall spatial variation, overall time trend and the departures of the local trends from the overall trend of resident population in Chaoyang by use of Bayesian spatial-temporal hierarchical model. Secondly, we applied Bayesian Gaussian predictive process to predict the resident population in December of 2017 by incorporating other relevant influential factors. The results show the perfect spatial stratified heterogeneity for resident population in Chaoyang, and the overall spatial variation demonstrates an increasing trend of population from center to the outside along the main ring road in Beijing. The overall time trend is still growing all over Chaoyang district, while the local trends, which departure from the overall trend of resident population, are different between each sub-districts in Chaoyang. Moreover, the spatial distribution of predicted resident population shows a high consistency with the observed resident population, and the prediction accuracy can be well accepted on the scale of Chaoyang district. However, prediction accuracy shows obvious difference on scale of sub-districts, with the worst prediction accuracy in the capital airport area. These findings show that Bayesian hierarchical model and Bayesian Gaussian predictive process are reliable in empirical study of population evaluation and prediction by effective application of multisource spatial-temporal data. Researches in this paper can be an excellent theoretical and practical support for mining multisource spatial-temporal data and assisting multiscale analysis with Bayesian spatial-temporal model, and provide an important basis for population controlling and early warning in urban population management.

With the population aging being ahead of economic development, the problem of pension resources configuration among aging population will stand out continually. The three provinces in the northeast of China are the moderate districts of aging. It is noted that there are national strategic meanings and demonstration effects to study the spatial distribution feature of aging population and the optimal configuration of pension resources. Taking 34 prefecture level cities and 2 administrative areas as the research objects, the spatial evolution features of population aging in the administrative regions in the 3 major years were characterized, based on the spatial autocorrelation analysis according to the statistical data of aging population. The pension resources configuration of 36 objects in 2015 were evaluated by using comprehensive index model and the spatial matching relationship between 36 groups’ aged people and pension resources was identified on the basis of geographic concentration. The results demonstrated that the degree of population aging in the administrative regions in 2005, 2010, and 2015 were deepening gradually. The high density areas were expanding from the southwest to the northeast and the spatial correlation features are enhancing; the high agglomeration areas were widening from the south to the north; and the “dilution” of population aging in the northeast in the future will face severe challenges. The pension resources in regional center cities and the cities with the government’s supports are richer than the peripheral cities. There is an obvious correlation of spatial distribution between aging population and pension resources. The concentration of aging population and pension resources is reduced from the south to the north. Among them, the whole area of Liaoning Province is both a concentrated area of aging population and pension resources. There is a diverse matching relationship between the south and the north, and the development level of the ‘Liaozhongnan’ urban agglomeration is significantly higher than that of the ‘Ha-Chang’ urban agglomeration. The most cities still face the two extreme problem, i. e. , a waste of and a short of pension resources.

Since the central government proposed "balancing basic public services" in 2006 and the 2009 World Bank Development Report advocated "equal coverage of residents' access to public services," improving facility accessibility and spatial distribution have increasingly become one of the development goals for regional governments and hot topics for academic research. In Shanghai Municipality, accessibility of medical facilities in different regions within the city needs to be examined urgently because it is closely related to people's livelihood, health, and social justice. Based on the accessibility of tertiary, secondary, and community hospitals in Shanghai, this study analyzed the accessibility of medical facilities in different areas of the city, and the variation between the registered and floating populations. Improved potential model and multivariate linear regression model are used accordingly. The study further explored the influencing mechanism of individual accessibility of medical treatment. The results are as follows. First, the inner city is characterized by the highest regional accessibility of medical facilities, and accessibility is gradually reduced from the inner city to the suburbs. The fluctuation of hospital accessibility is relatively clear in the suburban area. Anting Town, Huaxin Town, and some other towns in the west of Shanghai still lack of medical facilities. Second, registered population's accessibility of medical treatment is better than that of floating population, and the most obvious difference between the two groups is found in the fringe of the central urban area and the inner suburban areas. Compared to the Pudong area, floating population in the Puxi area is facing more difficulties in seeking medical care. Third, residential location significantly affects accessibility of medical treatment. For the registered population, community hospitals are more accessible in outer suburbs, and secondary hospitals are more accessible in the fringe of the central urban area compared with the inner suburbs. For the floating population, the above variation is not significant. No matter which regions they live, they are generally facing severe medical accessibility problems. Finally, socioeconomic and institutional factors also have impacts on accessibility to medical facilities. Middle-aged and elderly residents with higher education have better access to medical facilities. Housing property rights and medical insurance are much related to registered population's medical accessibility, while economic factors matter more for floating population. This study provides some suggestions for the relevant government departments to identify areas lacking medical facilities and improve the spatial distributions of medical and public transport facilities, thus helping to achieve the goal of equal access of health care. Future studies need to consider the integrated impact of spatial and institutional factors on residents' medical preferences and behaviors.

Migrants' hukou transfer intention of the western ethnic minority regions has great implications not only for the overall urbanization level, but also for national unity and harmony in the society. Based on the dynamic monitoring data in 2012 from Xinjiang Autonomous Region and using a binary logistic regression model, this study analyzed the similarities and differences between the willingness of migrants to migrate in different regions and ethnic minority groups and their influential factors. According to the results, migrants' hukou transfer intention reached a high level, and more than half of respondents were willing to transfer their hukou to cities where they reside. This proportion is slightly higher in northern Xinjiang than in the south, and the related value is higher in ethnic minorities than Han nationality. The modeling result shows that Xinjiang barely had any attraction to highly educated and economically well-to-do migrants. Ethnic type, time of residence, and social integration degree are found to be the core factors in the dynamic system concerning migrants' hukou transfer intention. As well, there are different factors in different regions and ethnic groups in Xinjiang, when migrants make transfer decisions. But there is no regional or inter-group difference concerning social integration factors. Elevated social integration significantly helped to heighten transfer intention.

With the rapid development of urbanization in China, the area of urban construction land has been increasing, when a large number of agricultural population keep transferring to cities. The purpose of this paper is to explore the influence of agricultural population transfer on the growth of urban construction land,which is of great significance for promoting the construction of new urbanization and achieving the real transfer of agricultural population.Based on the statistical data of 11 cities in Jiangxi province from 2006 to 2015,the fixed effect and the random effect model were used to study the influence of the agricultural population transfer on the increase of urban total construction land and different types of urban construction land. The results show that the transfer of agricultural population in Jiangxi had a significant positive impact on the growth of urban construction land, and passed the test under one percent level. What's more, the transfer of agricultural population also exerted significant effects on the growths of urban industrial-commercial land, urban residential land and traffic-green-square land, and quite obvious in the scope of ten percent,one percent and five percent respectively, and the influence coefficients correspondingly were 0.167, 0.155, and 0.135. However, with the transfer of agricultural population, there has been no significant growth in urban public facilities-service land.There are regional differences among different cities, when the increase of different types of construction lands are impacted by the agricultural population transfer.Thus, it is concluded that the transfer of agricultural population will enhance the total amount of urban construction land. Thus, according to the process of agricultural population transfer, the government should moderately increase the urban public facilities land, rationally layout different types of urban construction land, for effectively promoting the construction of new urbanization and finally realizing the urbanization of agricultural population.

With the shift of urban function and the upgrade of industrial structure, the floating population structure has undergone a profound change. The floating population community is pyramidally diversified and its formation mechanism is becoming increasingly complicated. Taking Beijing as the study area, and synthesizing GIS spatial analysis, mathematical statistics analysis and spatial econometric model, this paper investigates the spatial differentiation of floating population communities in Beijing. On this basis, it explores the formation mechanism of floating population communities by synthesizing community and individual factors. The results show the following: (1) Floating population communities in Beijing circle the Forbidden City and present the dual characteristics of urban and rural areas. Meanwhile, they demonstrate obvious differentiation among spatial classes. (2) The spatial differentiation of floating population communities is the combined result of the floating population's demand and housing supply, as well as the result of community and individual factors. (3) Community factors are the external driving forces of the spatial differentiation of floating population communities. Specifically, economic factors are the basic driving force; public transportation factors are the spatial leading driving force; institutional factors are the fundamental driving force; and spatial spillover effects are the dominant driving force. (4) Individual factors are the internal driving forces of the spatial differentiation of floating population communities. Specifically, the family life cycle is the direct driving force; the socio economic status is the major driving force; the migration feature is the underlying driving force; and the basic public service demand is the insensitive driving force. This study provides a scientific basis for the government's administrative and management strategy, and advances the effective and efficient transformation and upgrade of floating population communities.

The spatio-temporal characteristics of demographic distribution in China from 2000 to 2010 were analyzed systematically from the perspective of urban agglomeration, using the methods of barycenter model, spatial autocorrelation and Theil index. The 19 urban agglomerations mentioned in the country's 13th Five-Year Plan (2016-2020) are studied in this paper. Results show that the distribution center of permanent population is moving further towards the southeast where developed urban agglomerations are concentrated. Urban agglomeration is a high value area of population density and population growth, but a low value area of natural population growth. Urban agglomeration is also the most active area of China's population flow, and the effect of population space agglomeration and diffusion is also remarkable. The spatial distribution pattern of China's population is closely related to the distribution and development of urban agglomerations. Meanwhile, the development of urban agglomerations has brought a large population into urban agglomeration or its core cities, and the distribution of population in urban agglomeration has increased significantly. Because of the attraction effect of urban agglomeration on population, the geographical difference of population density in China is further expanded. The development level of urban agglomeration in China is very different, and the urban agglomeration in different stages of development show different effects of population agglomeration and diffusion. Urban agglomerations in stage of the higher development degree, mainly located in eastern coastal densely populated areas, are featured by strong demographic attractiveness, and overall population agglomeration, hence gradually form a hierarchy. At the same time, urban agglomerations in stage of the lower development degree are mainly distributed in the central and western regions, where the population is sparse, with the city being less appealing to population. These urban agglomerations present the core edge diffusion characteristic, and the urban system structure is not stable yet.

A sustainable new type of urbanization in China should be "people-oriented." Migrants are the main body of new urban residents, and their subjective wellbeing is one of the significant criteria for measuring the quality of urbanization. A plethora of literature has shed light on the low quality of migrants' lives, however, little research has been done to understand how migrants evaluate their own lives in host cities, and no study has been undertaken to link migrants' subjective wellbeing with their residential environments. Using the data collected from a questionnaire survey in Guangzhou and multilevel linear models, this study examined the determinants of migrants' subjective wellbeing in host cities. It particularly focused on the extent to which and how migrants' social ties and residential environment influence their subjective wellbeing. The results indicate that in general, migrants have a lower level of subjective wellbeing than local residents, and the cognitive and emotional components of migrants' subjective wellbeing are influenced by different factors. Social support and neighborhood environment matter in determining the cognitive component of migrants' wellbeing (life satisfaction), but the emotional component of their wellbeing (positive and negative affects) is influenced partly by some of the selected variables of neighborhood social or built environments, and no evidence shows any impact of social support. Meanwhile, dwelling conditions also show an impact on migrants' life satisfaction and negative affect.

The spatial distribution of population at fine-scale has increasingly become research hotspot and a difficulty issue in the field of population geography. It has practical application value and scientific significance for relevant researches, such as disaster assessment, resource allocation and construction of smart cities. The population is concentrated in the urban area. Revealing the population distribution difference in this area is the core content of spatializing population data at the fine scale. In this paper, the urban area of Xuanzhou District was selected as the research area. The population distribution vector data at residential building scale was established by proposing a spatialization method based on urban public facility elements. The method classified residential building patches. And it treated residential building patches as population distribution locations in geographical space with community boundary and community-level demographic data as the control unit. A multiple regression model of patch area and population was constructed. The spatialization method used in this study can reveal the detailed information about the population distribution in urban area. Results show that: ① The population distribution data, obtained by adopting urban public facility elements, is proved to be high accurate and reliable. The number of patches with estimated population in a reasonable range is 35.4% of 779 residential building patches. And the proportion of patches with relative errors of ±20% in population estimation is 61.2%. Moreover, the Chengdong community and Sijia community served as accuracy verification units, the absolute relative error of population estimation in these communities is less than 9%; ② Urban public facility elements, especially primary and secondary schools and kindergartens, vegetable markets and fruit shops, are important factors for accurate estimation of population within a residential building. Their estimation accuracy of number of people is high ifor multi-storied building, but lower for moderate high-rise building.

This paper is aimed at exploring the determinants of population growth in Chinese urban areas. With the method of exploratory spatial data analysis and the data of traditional population census between 1990 and 2010, we could delve into the spatial distribution characteristics of the population growth rate and the multivariable spatial dependency during the past twenty years in Chinese city-level. Based on a thorough interpretation of population data, we are able to discover an existing spatial dependency between different cities. Obviously, spatial relations should not be negligible, because the spatial dependency is much stronger within cities living in shorter distance. It is more reasonable to use spatial regression model for our work, therefore, we use spatial lag regression model, spatial error model and classical linear regression model with spatial filtering to explore the influences of economic factors, climate factors, sociocultural factors and topography factors on population growth rate. It is showed that the classical linear regression model with spatial filtering can simulate the urban population growth rate batter than other models in our outcomes. The findings also suggest that economy is the most pivotal factors in population growth, such as the total amount of economy reflected by density of urban nightlight index plays an important role in driving population growth. Meanwhile other factors are following as well. Climatic variation is another systematic and significant factor affecting the rates of urban population growth. Some weather-related movement appears. People are willing to leave the unpleasant places and move to the places with nice weather. For example, with the increase of July heat index, there is a more and more stronger negative impact on population growth. The research shows that Chinese population growth is a complex question. There is a comprehensive action of multi-factor in generating the model of regional population growth. It is necessary to consider the different effects of economic development and climate conditions on the population growth in the researches on corresponding modeling and formulation of policy.

The dynamic moving and spatial coupling of gravity center of county-level population distribution, economic development,and grain production in Henan Province has been researched in this article, and discussed the relationship between social development and above three factors based on the social theory, gravity center calculation and spatial coupling analysis model. The result showed that the spatial gravity centers of county-level economical development, population distribution and grain production have been moving in the north of geometric center of Henan Province. The consistency level changed sharply, and the spatial inconsistency pattern was very significant during the past 23 years. Before 2000, the spatial coupling level between county-level population distribution and grain production was high, and after 2000, the spatial coupling level changed among the gravity center of county-level economic development, population distribution and grain production. The gravity center of grain production and economic development moved oppositely in the southeast-northwest direction, and the influence of grain production to the gravity move of economic development has been decreasing, while the coupling level between the gravity centers of population distribution and economical development has been increasing during the same time. The social development in the eastern Henan shows a low-level spatial equilibrium with the coexistence of inversion phenomenon between grain production and government receipts and grain production and people’s livelihood. The social development level in rural counties obviously lags behind that in urban areas. The spatial pattern of social inequality at county level in Henan driven by the factors, such as regional economic development, social policies, spatial strategy, and path dependence, is tabbed the constitutive characteristic in the period of comprehensive socioeconomic transformation in China. Consequently, two steps on how to improve the county-level population distribution, economic development and grain production are proposed. On the one hand, based on the cognitive of China breadbasket, the farmland protection, technical support, policy tilt to grain yield should be forcefully developed to ensure the grain production scale in Henan and regional grain safe. On the another hand, some reasonable policies must be proposed to encourage the deep process of agricultural products and foster the development of township enterprise, to accept more surplus labor in rural society.

Aging population has been more and more complex as well as one of new normal and core issues which the social development must face in China. Based on the population census data in 2000 and 2010, this study explores the regional differences of Chinese ageing population in terms of the degree, pace, social economic impact, and analyzes its driving mechanism using the Geographical Weighed Regression Model (GWR). The results show as follows: 1) During 2000-2010, Chinese population as a whole has entered the stage of ageing, and most of regions stay at the early stage. 2) Except for Shanghai, all other regions are experiencing the acceleration of ageing, and the regional disparity in the degree of ageing is decreasing. 3) The demand for the elder support has increased rapidly. 4) The overall density of aged population remains at the low level, but the local density increases from the west to the east, with the high density zones cluster in a few eastern municipalities. 5) The degree of population aging and spatial layout in China province are the comprehensive results of population natural growth, population growth, mechanical growth and economic level and so on. Among them, the primary leading factor has changed from GDP per capita to emigration rate. In the early stage of economic development, per capita GDP plays a decisive role in promoting. With the development of economy, the influence of per capita GDP on the aging population has decreased. The phenomenon of “not getting rich before getting old” appears, what’s more the phenomenon of “decoupling” between GDP per capita and aging appears in some areas. The rate of population emigration is positively related to population aging, which promoting the degree and speed of population aging as well as increasing the burden on the elderly in the central and western regions. 6) The comprehensive effects of spatial heterogeneity of the mechanism coefficients has promoted the population aging roughly divided the spatial pattern from North-South (with the Yangtze River Basin as the boundary) to East-West differentiation (with the central region as the boundary) in China. The provincial population migration fundamentally restricts the current spatial pattern of China’s population aging. The comprehensive effects of various factors on the central and western regions are slightly stronger than those in the east. 7) The largest population emigration areas are still in the Central and Western Regions, which leading to faster growth rate in the Central and Western Region than in the east and increasing the burden on the elderly rapidly and greater than that in the east. However, the eastern region is the largest population immigration area in china. Natural growth rate has become the main mechanism to curb the rapid development of population aging in the eastern region.