The Simulation Of Chinese Population Density, Error Analysis And Software System Research

The population is an important factor for the sustainable development of one region and our country has so much people, therefore, the method research to obtain the region population indexes is one of the focus problems in the academic field. Statistics about population indexes, is taken by the census and the method of the sampling mostly now to compute with a current population in some district. Because our country is broad and natural environment is various, the sampling population data can't reflect the condition of national population distribution accurately. But the census is an enormous system engineering in a scale and it need longer time with the enormous manpower, material resources and financial power. It has longer renewing period, so we can't acquire the dynamic population data in time. For this, this article will emphasize on the research of estimating the spatial distribution of Chinese population density by the Simulated Population Density model (SPD). The SPD model is made by the Institute of Geographical Sciences and Natural Resources Research of Chinese Academy of Sciences. It combines social economic factors, such as city and transportation foundational facilities, with nature factors, for example the Digital Elevation Model (DEM) and Net Primary Productivity (NPP) of plants to simulate the spatial distribution of population density of China by the advanced grid generation technology. The method of the model retrieval breaks down the traditional population density statistics method according to the administrative area boundary and changes to evenly distributed and same size grid units to compute the population density. It enriches the methods to obtain the population density indexes and increases the accurate degree and application fields of the indexes. So, it will benefit to the decision process of the population and economic policy, benefit to the sustainable development of regions.The main contents of this article is divided into three parts:In the first part we systematically discuss the theoretical foundation and the technique of the Simulated Population Density model (SPD), explain each one of the model variables, the formulas and the simulation result. In the part, we first introduce the significance and theoretical foundation of the simulation in the spatial distribution of population density basing on the grid generation technique. Then we review the current condition of domestic and international research in that field, detailedly expatiate the selection, pretreatment and computation method of the main variables in the SPD model.In the second part, we adopt a few typical error analysis methods, primarily including the relativity analysis and the regression analysis, to analyses the relative error and absolute error of the time error, spatial data error and statistic data error of the raw input data in the model. Then, we take each influence factors in the model into the relativity analysis and the regression analysis. Finally, we synthesize the results of the above error analysis to figure out the theoretic accuracy of that model as 87%.The third part is mainly about the software system developed and used in the simulating calculation and error analysis process of SPD model. The software adopted completely the thought of metadata database management with the Object Oriental Programming (OOP)technique, set up a simple modelbase management system, got out a integrated computing system for models management, error analysis and charts output and so on. In this part we detailedly discuss the framework, functions and system integrated methods of the software.The main purpose of this article is to research the new method to express the spatial distribution of region population density that is an important economic element, by using the grid generation technique and the data fusion theory. The main research method is to achieve the simulation and spatial expression of the population density index with the help of computer tools. Finally, We got the map of the spatial di...