人口数据格网化是目前人口空间分布研究的热点。本文对国内外人口数据格网化模型研究进行总结,重点剖析几种主要的人口数据格网化模型。研究表明:人口数据格网化模型从单纯的、静态的格网化方法,逐步向自然、经济社会因素综合影响下的空间模型过渡,朝着动态模型方向发展;随着格网化数据应用领域的不断拓展,以不同级别格网为基本统计单元的人口数据生产将是人口数据获取的一个重要发展趋势。

Grid transformation of population data is the focus of population spatial distribution. National and international grid transformation models of population data are summarized:during the grid transformation of population data, factors affecting population distribution are paid more and more attention. GIS and RS become the main technologies of grid transformation of population data. Base on these,the following main grid transformation models of population data are analyzed especially:area weighted model, kernel estimate model, land use affected models, gravity model and multi-sources information fusion model. Furthermore, this paper makes comparison on different grid transformation models of population data from the aspects of modeling factors, data sources, strongpoint, shortcoming, application scale, application case and validation result. Results show:the grid transformation models of population data are gradually changing from one-fold grid methods to models influenced integrative by natural, economic social factors, and to dynamic models. In addition, with expand of application fields of the grid data, population data product on the basis of different level grid is the trend of population data acquirement.