| In the three decades of rapid urbanization,extensive urban development and construction have led to the emergence of various urban diseases,hindering the quality of urban life and healthy development.Most of the urban diseases stem from the mismatch between urban space and the needs of the population.Therefore,the key to transforming urban development methods and improving urban space utilization efficiency lies in guiding the allocation of urban space resources with human needs as the value orientation.However,the composition of the population in the city is extremely complex,and the spatial requirements are also very different;and the employed population is the largest stable activity group in the city.Depicting the temporal and spatial characteristics of the activities of the employed population and analyzing their spatial activity needs can be used as a guide for the city to shift to a higher level.A critical step in quality planning.In previous studies,many scholars have carried out research on the employment and housing activities of the employed population,and formed a theoretical system and planning application method relative to the city.With the improvement of various facilities in the current city,the time and space choices of urban employment groups’ behavior activities are becoming more and more diversified,and the refined research on it has gradually become an emerging research topic in recent years.At the same time,in the context of smart city construction,the generation of a large amount of activity data provides support for refined activity spatiotemporal feature tracking and dynamic crowd spatiotemporal behavior network construction.How to establish a systematic cognition of the daily behaviors and activities of the employed people through big data methods,and then refine the identification of the spatial and temporal characteristics and needs of their activities,has become an important issue in the transformation of planning research.In order to study the diverse needs of urban employment groups in detail,based on the LBS positioning data,this paper analyzes the behavioral characteristics of the employment groups in the central area of the city,and depicts their multi-dimensional digital portraits.The content of this paper can be divided into three parts: theoretical basis and literature review,profile construction and behavioral network characteristics,and profile-based behavioral network analysis.Among them,the first chapter is the theoretical basis and literature review.It summarizes the existing research results and precise directions of the behavior of employed people,as well as the method path of using crowd portraits to describe crowd attributes and then analyze behavioral activity patterns.The second chapter is the construction method of portraits,expounds the classification characteristics of the attributes of the crowd,and summarizes the attribute categories based on the ontology dimension and the attribute categories and identification methods based on the behavior dimension.Firstly,based on the SPID algorithm,it identifies the stop points of crowd activities,constructs its behavior chain,and summarizes its typical behavior patterns through multi-day behavioral activity data;The third chapter takes the central area of Xinjiekou as an example,constructs a multi-dimensional population portrait of the employed population,and analyzes the behavioral spatial characteristics of various portrait populations based on the behavioral dimension,and constructs their behavioral activity network.The fourth chapter measures the temporal flow characteristics of the behavior of the employed population under the dimensions of the metropolitan area and the central area respectively,and uses the results of the crowd portrait construction to analyze the characteristics of the results;and based on the portrait composition characteristics of typical corridors and typical node activity areas.Features suggest possible strategies for planning responses.In the information age,big data analysis provides new cognitive tools and analytical perspectives for the study of complex urban issues.Using LBS and other big data to construct crowd portraits and analyze the spatiotemporal activity characteristics of employed people,its core goal is to study the increasingly complex behavioral regularity and spatial demands of urban crowds.Based on the existing research,this paper attempts to explore the application scenarios of crowd portraits as urban research methods;taking the central area,an area with a high concentration of employed people as an example,to construct a crowd portrait that depicts the ontology and behavior dimensions of employed people.And based on this method to analyze the spatiotemporal network of its behavior.Due to the insufficiency of existing data and technical methods,the analysis of urban space needs still has certain limitations.How to accurately analyze the behavior and spatial relationship of multi-faceted people is one of the important tasks of future research. |
