Research On The Temporal And Spatial Distribution Of Urban Day And Night Population Based On Architectural Space

In recent years,cities of our country have been developing rapidly and urban population is increasing fast.However,the problems existing in development of cities are all centered on the core element "human".Therefore,it is of great significance to understand the high temporal-spatial resolution distribution of urban population because many aspects like city planning,commercial layout,transportation,risk evaluation,emergency rescue and smart city construction need the support of population distribution information.For a long time,the information concerning population distribution mainly originates from the population statistics obtained from census or sampling statistics,which however has many shortcomings.For example,the statistics is difficult to gather;the data of certain regions and years are not complete;the statistics units are mainly divided based on administrative regions,and difficult to integrate with the data of other regions.Besides,previous research is mainly centered on the interannual scale overall distribution of urban population while those on day and night population distribution of micro-regions is absent.Nowadays,with the development of mobile positioning big data and ubiquitous sensor network,new methods are available to get high temporal-spatial resolution distribution of urban population.For instance,the application"Easy Travel" thermal data of population that is based on the position big data of Tencent can perfectly display the crowd assembling situation.Therefore,this thesis,in order to get the high temporal-spatial resolution distribution of urban population,conducts simulation for urban micro-region population distribution based on construction space by integrating urban construction data and the thermal data of "Easy Travel".This thesis implements detailed analysis for multiple elements which exert influence on the temporal-spatial distribution of urban population,establishes building classification system applicable to research on population distribution,and presents detailed classification for buildings in research areas in combination with function parcel data,remote-sensing image,street view map,field research,etc.Besides,it collects the thermal data of population of different time during workdays and weekends,analyzes the thermal value’s change characteristics of construction spaces at different time by combining specifically-classified construction data and adopting the ArcGIS software,and discusses the attractive degree of different time to people,thereby establishing models to simulate the population distribution of different construction spaces during workdays and weekends.In the process of research,the 24 hours of a day is divided into several periods in accordance with the different activity levels of people at different time reflected by thermal data,due to which randomness and subjectivity which were frequently seen in previous research are avoided.The simulation result shows that population distribution change in different buildings is obvious in daytime.During 7:00-9:00,a large number of people transfer from residential buildings to other buildings and keep relatively high thermal value while during 18:00-22:00,people gradually go back to the residential buildings.Meanwhile,the thermal values of different kinds of buildings are different according to unit construction area during daytime:commercial buildings,office buildings,education and scientific research buildings tend to have higher thermal value while more obvious changes are seen in administrative office and education and scientific research buildings in different periods.By contrast,during nighttime,the thermal data can hardly reflect true population distribution situation as people’s activity level is low,and even the people are all assumed to live in residential buildings,their distribution is closely related to the floors they live on.The comparison of population distribution of different time during workdays and weekends demonstrates that population is more extensively distributed at weekends,with the thermal value of entertainment spaces like commercial buildings increasing while that of administrative and office buildings experiencing negative growth.In this paper,the population distribution of different types of building space in different periods of working day and weekend is simulated and analyzed by using the thermal data of"suitable for travel",in order to provide some reference for other related research.