Vol112, No11 Feb1, 2010 JOURNAL OF GEO2INFORMATION SC IENCE , CBERS IRS - P5, ;, : ; : E2mail: lreis1ac1cn [ 6-13 ]

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1 JOURNAL OF GEO2INFORMATION SC IENCE Vol112, No11 Feb1, 2010, 3, (, ) :,,,,,, CBERS IRS - P5, ;,, 20m 1km ;,, CBERS, 200m, 76% ; P5, 100m, 84% : ; ; ; 1 [ 4-5 ], GIS, [ 6-13 ], ( km, GPW ) ( [ 1 ] km ),, 1km 5km [ ],,, ( ),,, [ 2 ],,,,, CBERS P5,,,, [ 3 ], ; 20 90,, : ; : : 863 (2006AA ) : ( ),,, GIS E2mail: yej@ lreis1ac1cn 3 : ( ),,,, GIS E2mail: yangxh@ lreis1ac1cn

2 1 : 41,, 2 (1) P5, 7,,, , 1105km 2, 73km 2 72, 421,,,,, (2) 3 : : CBERS - 02 CCD 1, 1915m ; IRS - P5 6, 215m 2007 : 2007 (3) 1915m CBERS 215m,, 2007 ( 1), 1 10, 6, 1 CBERS( a) P5 ( b) 2007 Fig11 Landuse of Yiwu in 2007 extracted by CBERS ( a) and P5 ( b), (4) CBERS P5,, 2007,,, : P i n = a j j =1 s ij, P i i ; a j

3 j ( /km 2 ) ; j ( km 2 ) ; s ij i n = 3, 3,,, a j,,,,,,,, a j, a ij :, a ij = P i a P j i a ij i j ( P /km 2 ), P i i, P i i a ij,,,, ( 2), 3 311,,,,,,,, :, CBERS EP = ( pop j - pop t ) 1km 500m 200m 100m pop t 100% ; P5 200m 100m 50m 20m EP, pop j, pop t 2 CBERS - 200m ( a) P5-100m ( b) Fig12 Population distribution of Yiwu based on CBERS - 200m ( a) and P5-100m ( b)

4 1 : CBERS CBERS 1km 500m 200m 100m,, ( 1), 1km 14131% 100m 1124%, 1km 500m 56% ; 500m 200m 76% ; 200m 100m 19%, 200m, 1 ( CBERS) Tab11 The error between popula tion by gr id and sta tistica l popula tion ( CBERS) 1km ( % ) 500m ( % ) 200m ( % ) 100m ( % ) ( 3), 0, 200m 1km 50% 100m 5%, 1km, 0 ; 500m, 0 ; 200m 100m 313 P5 P5 200m 100m 50m 20m,, 0,, 200m, 0 ( 4), ( 2), 200m 2178% 20m 1163%, 1km 10% 200m 100m 40%; 100m 50m 100m 5%, 1km 500m 1%; 50m 20m 1%, 1km, 100m, 500m ; 200m 100m, < 5%, 200m,, CBERS ( 5), 0 200m 8% 20m 4%, 200m, 0 ; 100m 50m

5 m, 0 100m, 0 ( 6), 200m 5% 20m 5%, 200m, ; 100m 50m 20m, < 5%,, 100m,, P5, 100m 314,, 30, CBERS 200m P5 100m,, CBERS - 200m P5-100m ( 3) : CBERS - 200m 24%, 76% ; P5-100m 16%, 84% 2 ( P5) Tab12 The error between popula tion by gr id and sta tistica l popula tion ( P5) 200m ( % ) 100m ( % ) 50m ( % ) 20m ( % )

6 1 : 45 3 CBERS - 200m P5-100m Tab13 The accuracy of CBERS - 200m and P5-100m data CBERS ( % ) P5-100 ( % ) CBERS IRS - P5,, 20m 1km ;, : (1) : CBERS, 200m; IRS - P5, 100m (2) : CBERS, 76% ; IRS - P5, 84% , : [ 1 ]. [M ]. :, [ 2 ],,,. RS GIS [ J ]., 2002, 17 (5) :

7 [ 3 ],,. [ J ]., 2006, 8 (2). [ 4 ] Tobler W, Deichmann U, Gottsegen J,Maloy K. The Global Demography Project[ R ]. Technical Report TR National Center for Geographic Information and Analysis, Department of Geography, University of California: Santa Barabara, [ 5 ] ToblerW, Deichmann U, Gottsegen J,Maloy K. World Popu2 lation in a Grid of Spherical Quadrilaterals[ J ]. Int. J. Pop2 ul. Geogr. 1997, 3: [ 6 ]Balk D, B rickman M, Anderson B, Pozzi F, Yetman G. Esti2 mates of Future Global Population D istribution to 2015 [ EB ]. Palisades, NY: C IESIN, Columbia University, Available online: http: / / sedac. ciesin. columbia. edu / gpw / documentation. jsp#. [ 7 ]Balk D, Pozzi F, Yetman G, Deichmann U, Nelson A. The D istribution of Peop le and the D imension of Place: Method2 ologies to Imp rove the Global Estimation ofuurban Extents [ EB ]. D raft version. Palisades, NY: C IESIN, Columbia U2 niversity, Available online: http: / / beta. sedac. cie2 sin. columbia. edu / gpw / documentation. jsp. [ 8 ]Balk D, Yetman G. The Global D istribution of Population: Evaluating the Gains in Resolution Refinement, Documenta2 tion for GPW v3 [ EB ]. Palisades, NY: C IESIN, Columbia University, Available online, http: / / beta. sedac. cie2 sin. columbia. edu / gpw / documentation. jsp. [ 9 ]C IESIN (Center for International Earth Science Information Network), Columbia University, Centro Internacional de Ag2 ricultura Trop ical (C IAT). Gridded Population of the World Version 3 ( GPW v3 ) : Population Grids [ EB ]. Palisades, NY: Socioeconom ic Data and App lications Center ( SE2 DAC), Columbia University, Available online: ht2 tp: / / sedac. ciesin. columbia. edu /gpw. [ 10 ] Salvatore M, Pozzi F, A taman E, Huddleston B, B loise M. Mapp ing Global U rban and Rural Population D istributions [M ]. Rome: FAO, [ 11 ]Balk D L, Deichmann U, Yetman G, Pozzi F, Hay S I. De2 term ining Global Population D istribution: Methods, App li2 cations and Data[ J ]. Adv. Parasit. 2006, 62: [ 12 ]Dobson J E, B right E A, Coleman, P R, Durfee RC,Worley B A. LandScan: A Global Population Database for Estima2 ting Populations at R isk[ J ]. Photogramm. Eng. Rem. Sens. 2000, 66: [ 13 ]Bhaduri B, B right E, Coleman P, Dobson J. LandScan: Lo2 cating Peop le Is W hat Matters [ J ]. Geoinformatics 2002, 5: [ 14 ],,,. [ J ]., 2002, 57 ( ) : [ 15 ],. GIS [ J ]., 2003, 58 (1) : [ 16 ],. [ J ]., 2004, 30 (3) : [ 17 ],. RS GIS [ J ]., 2006, 25 (1). [ 18 ],. [ J ]., 2007, 16 (2) : [ 19 ] Yang Xiaohuan, Huang Yaohuan, Dong Pinliang, J iang Dong, L iu 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) : The Gr id Sca le Effect Ana lysis on Town leveled Popula tion Sta tistica l Da ta Spa tia liza tion YE J ing, YANG Xiaohuan, J IANG Dong ( Institute of Geographical Sciences & N atural Resources Research, CAS, B eijing , China) Abstract: 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 resear2 ches 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 p rovincial scale, and their resolution ranges from 1km to several kilometers. In recent years, there are studies on lo2 cal distribution of population by using of high2resolution im ages. For all the researches, both the method of data

8 1 : 47 source selection according to specific app lication and the analysis on p roduction suitability are deficient. So, many uncertainties exit in population data app lication, especially in county level and secondary or tertiary rivers. To solve the p roblem s mentioned above, in this article we mainly p ropose the method of scale effect analysis on population data spatialization. Taking Yiwu City, Zhejiang Province as the study area, using CBERS and IRS2P5 images we ex2 tract land use inform ation 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 statisti2 cal population data in rural towns, the grid scale effect analysis is m ade; 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 p roduction is 200m and its p recision is 76% ; by using P5 as a data source, the suitable grid scale of p roduction is 100m and its p recision is 84%. The method of scale effect analysis in spatial distribution of statistical population is argued in this paper and it can p rovide basic technical solutions and examp les to op timum scale selection in the p rocess of humanistic factors ( such as population) spatialization. Key words: population; spatialization; grid; scale effect