人口统计数据的空间转换

SPATIAL TRANSFORMATION FOR STATISTICAL POPULATION DATA

在经济和社会研究中 ,所要研究的区域之上经常没有数据 ,而这些数据需要由已知区域的数据求得 ,即统计数据需要空间转换 ,这就通常涉及到面积内插。本文从GIS的角度研究如何解决人口内插问题 ,认为面积内插和GIS中的叠加分析是一致的。在传统的面积内插方法的基础上提出了基于人口真实分布的面积内插方法 ,并推导出了公式。同时提出了人口密度的递归算法 ,即把居住区分为人口稀疏地区和人口稠密地区 ,估计出人口稀疏地区的人口密度 ,就可以求出人口密集地区的人口密度 ;再把人口密集区分为新的人口稀疏区和密集区 ,此过程反复直至求出接近于人口真实分布的人口模型。

In economic, social and urban studies, areal units under analysis frequently differ from areal units over which data are compiled. Most area based analyses, hence face an unavoidable problem of transferring data across different zonal systems, that is, statistical population data requiring a spatial transformation. This is so called areal interpolation. This paper studies population interpolation based on GIS. A areal interpolation with population real distribution is pointed out based on traditional areal interpolation by partitioning the zone into 'occupied' and unoccupied' classes. The new formula is deducde. A population density algorithm is developed based on recursion as well. (1) The study region is partionde into two subregions-a sparsely populated region and a more densely populated one. (2) Through estimation the population density of sparsely populated region, the population density of a more densely populated region can be calculated. (3) The more densely populated region is divided into two subregions- a new sparsely populated region and a new more densely populated one if necessary. This process can take many iteration until the real population distribution model is obtained.