Study Of The Spatial Differentiation Of Relocation Activity Degree In Inner City Based On Mobile Phone Signaling Data ——A Case Study Of Wuhan Metropolitan Area

Along with the rapid urbanization and the continuous expansion of urban scale in China since the reform and opening up,the autonomy of urban residents to move has been increasing.Within cities,urban expansion,suburban new town construction,old city reconstruction,urban villages and shanty towns demolition and reconstruction,as well as the migration of migrants and special groups are more frequent.The active mobility of urban residents and the complexity of social and economic environment aggravate the spatial differentiation of residential areas,making the migration problem more complex.Migration has gradually become the most important reason for the evolution of urban social space.In this context,it is of practical significance for analyzing the evolution process of urban spatial structure and enabling community governance from the perspective of human behavior to accurately grasp the residents' relocation activity degree,and its spatial distribution characteristics,and to explore the relevant influencing factors of the activity types.Taking Wuhan Metropolitan Area as an example,based on the mobile phone signaling data provided by Unicom Intelligent Footprint Data Platform in June 2017 and 2019,this paper proposes net activity index,total activity index and turnover rate index to quantitatively describe the relocation activity degree,and according to the classification and combination of the indicators,divides the residents' migration areas into12 types.Then,the spatial distribution characteristics and influencing factors of the residential areas are discussed,and the corresponding planning suggestions are put forward on the basis of summary and induction.The full text can be divided into four parts: basic research,research design,empirical research and planning strategy.The first part is the basic research,which mainly elaborates the research background,and makes clear the research purpose,significance,content and method of the planning.On the basis of defining the main body of the study,this paper combs the existing research from the aspects of migration scale,activity degree characteristics,influencing factors,traditional data and methods of migration,and the application of big data in migration.It is concluded that the current migration studies are mostly large-scale studies based on census and questionnaire data,and the characteristics are mostly distance,frequency,intensity and so on,and there are few studies on activity degree.However,the application of big data in residential research is only to identify the changes in the total population,and there are few comprehensive studies on the specific amount of immigration and emigration.Therefore,it is the focus of this study to carry out the research on the relocation activity degree based on the migration quantity identified by the big data of time-series mobile phone signaling.The second part is the research design,which mainly discusses the research area,research data and index construction.The core part is: based on the existing theory of activity degree and migration indicators of population sociology,this paper puts forward three important attributes of migration activity,and constructs a single indicator to measure it;Secondly,based on the two indexes of net activity degree and total activity degree and the three indexes of net activity degree,total activity degree and turnover rate,the index classification and combination are carried out by median method and quadrant method,and 6 and 12 spatial types of relocation activity degree are divided respectively.The third part of the empirical research is divided into two parts: the empirical research of spatial type division and the empirical research of influencing factors analysis.On the one hand,according to the identified urban migration population in each grid of Wuhan Metropolitan Area from 2017 to 2019,the spatial distribution of immigration and emigration,net activity degree,total activity degree and turnover rate of the study sample are described.Then based on the two index systems and three index systems respectively,the empirical research on the urban development area is carried out,and the scale,spatial distribution and internal residential type characteristics of the relocation activity degree type under the respective index combination division method are discussed.On the other hand,according to the results of spatial classification,combined with their respective residential characteristics,they were finally divided into six types as the dependent variable in the regression analysis;the 5D dimension index of the built environment was selected as the independent variable,and the disordered multi-classification Logistic regression was used to explore the related influencing factors of the activity degree types.The fourth part is the planning strategy: on the basis of the previous analysis,according to the two dimensions of active intensity and turnover rate in the relocation activity degree,the planning strategy of the main urban area and suburbs is discussed.This paper proposes an evaluation index system of residents' relocation activity degree based on time-series mobile phone signaling big data,and proves its effectiveness for the spatial classification of residents' migration by empirical research.The results can provide data support for relevant planning and decision-making departments to control the characteristics of population migration within the city,and provide reference for regional construction and governance in different areas of the city.