DOI: 10.3724/SP.J.1047.2010.00040

Journal of Geo-information Science (地球信息科学学报) 2010/12:1 PP.40-47

The Grid Scale Effect Analysis on Town leveled Population Statistical Data Spatialization

The gird scale effect is one of the basic issues on population data spatialization.For the demand of all kinds of spatial population data in the fields of resources and environment and global change models,a lot of researches have been done based on remote sensing and GIS technology both at home and abroad.But the models used are mostly on global (such as GPW,1995,5km),national (such as national population database,2000,1km) or provincial scale,and their resolution ranges from 1km to several kilometers.In recent years,there are studies on local distribution of population by using of high-resolution images.For all the researches,both the method of data source selection according to specific application and the analysis on production suitability are deficient.So,many uncertainties exit in population data application,especially in county level and secondary or tertiary rivers.To solve the problems mentioned above,in this article we mainly propose the method of scale effect analysis on population data spatialization.Taking Yiwu City,Zhejiang Province as the study area,using CBERS and IRS-P5 images we extract land use information and build a spatialization model to the statistical population data of rural towns,then get a set of population data gird ranging from 20m to 1km.Moreover,by comparing population data by grid and statistical population data in rural towns,the grid scale effect analysis is made; by comparing population data by grid and statistical population data in villages,the remote sensing data source scale effect analysis is made.The result of scale effect analysis shows: by using CBERS as data source,the suitable grid scale of production is 200m and its precision is 76%; by using P5 as a data source,the suitable grid scale of production is 100m and its precision is 84%.The method of scale effect analysis in spatial distribution of statistical population is argued in this paper and it can provide basic technical solutions and examples to optimum scale selection in the process of humanistic factors (such as population) spatialization.

Key words:population,spatialization,grid,scale effect

ReleaseDate:2014-07-24 00:18:32

[1] 胡焕庸.论中国人口之分布[M].北京:科学出版社,1983.

[2] 江东,杨小唤,王乃斌,等.基于RS、GIS的人口空间分布研究[J].地球科学进展,2002,17(5):734-738.

[3] 叶宇,刘高焕,冯险峰.人口数据空间化表达与应用[J].地球信息科学,2006,8(2).

[4] Tobler W,Deichmann U,Gottsegen J,Maloy K.The Global Demography Project[R].Technical Report TR-95-6.National Center for Geographic Information and Analysis,Department of Geography,University of California: Santa Barabara,1995.

[5] Tobler W,Deichmann U,Gottsegen J,Maloy K.World Population in a Grid of Spherical Quadrilaterals[J].Int.J.Popul.Geogr.1997,3: 203-225.

[6] Balk D,Brickman M,Anderson B,Pozzi F,Yetman G.Estimates of Future Global Population Distribution to 2015[EB].Palisades,NY: CIESIN,Columbia University,2005.Available online:

[7] Balk D,Pozzi F,Yetman G,Deichmann U,Nelson A.The Distribution of People and the Dimension of Place: Methodologies to Improve the Global Estimation ofUurban Extents[EB].Draft version.Palisades,NY: CIESIN,Columbia University,2004.Available online:

[8] Balk D,Yetman G.The Global Distribution of Population: Evaluating the Gains in Resolution Refinement,Documentation for GPW v3[EB].Palisades,NY: CIESIN,Columbia University,Available online,2004.

[9] CIESIN (Center for International Earth Science Information Network),Columbia University,Centro Internacional de Agricultura Tropical (CIAT).Gridded Population of the World Version 3 (GPWv3): Population Grids[EB].Palisades,NY: Socioeconomic Data and Applications Center (SEDAC),Columbia University,2005.Available online:

[10] Salvatore M,Pozzi F,Ataman E,Huddleston B,Bloise M.Mapping Global Urban and Rural Population Distributions[M].Rome:FAO,2005.

[11] Balk D L,Deichmann U,Yetman G,Pozzi F,Hay S I.Determining Global Population Distribution: Methods,Applications and Data[J].Adv.Parasit.2006,62:119-156.

[12] Dobson J E,Bright E A,Coleman,P R,Durfee RC,Worley B A.LandScan: A Global Population Database for Estimating Populations at Risk[J].Photogramm.Eng.Rem.Sens.2000,66:849-857.

[13] Bhaduri B,Bright E,Coleman P,Dobson J.LandScan: Locating People Is What Matters[J].Geoinformatics 2002,5: 34-37.

[14] 杨小唤,江东,王乃斌,等.人口数据空间化的处理方法[J].地理学报,2002,57(增刊):70-75.

[15] 廖顺宝,孙九林.基于GIS的青藏高原人口统计数据空间化[J].地理学报,2003,58(1):25-33.

[16] 王英安,岳天祥.基于格网生成方法的山东省人口分布密度空间分布模拟[J].曲阜师范大学学报,2004,30(3):91-93.

[17] 李素,庄大方.基于RS和GIS的人口估计方法研究综述[J].地理科学进展,2006,25(1).

[18] 杜国明,张树文.面向防洪救灾的人口统计数据空间化研究[J].长江流域资源与环境,2007,16(2):265-268.

[19] Yang Xiaohuan,Huang Yaohuan,Dong Pinliang,Jiang Dong,Liu Honghui.An Updating System for the Gridded Population Database of China Based on Remote Sensing,GIS and Spatial Database Technologies[J].Sensors, 2009,9(3): 1128-1140.