GEO GRA P HICAL RESEA RCH

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1 GEO GRA P HICAL RESEA RCH Vol124, o16 ov1, ,2, 1, 2, 2, 1 (11, ; 21, ) : 2003,,,,,,,, : ; ; ; : (2005) ,,,, [1 ] [2 ],,, [3 5 ],, [6 ] ; [7 ],, [8 ] ;, [9 11 ] ;, [12 ],,, 1,, : ; : : ( ) ; 863 (2002AA ) :, (19712),,,,, E2mail :

2 6 : 957,, [13 ],, [5 ] ;,,,, [14 ],,,,,, 111,,,,, (clumped) (random) ( uniform),,,, (Quadrat analysis) (earest neighbor analysis) K [15,16 ] 11111, ( ),, [ 17 ],,, K - S K - S, K - S D, : D = Max Oi - Ei (1) : Oi i, Ei ( ) i D D ( = 0105), D ( = 0105) K - S, D D ( = 0105),, 11112,, : d ( ) = n Min ( dij ) i : d ( ),, dij i j, Min ( dij ) i, I, (2)

3 (3) : I = d ( ) d ( ran) : I, d ( ), d ( ran), d ( ran) = 015 A/, A I 1, ; I 1,, z [18 ],, Ripley s K, Ripley s K, [18 ] Ripley s K( d) : : n, d, w ij ( d), A [19 ] K( d) = A n n w ij ( d) (4) i j n 2 (3) i j K( d) 0,, 0, K [ 20 ] : L ( ds) = K( ds) - ds (5) L ( ds), L ( ds), (simulation), 112,, [21 ],, Tobler, [22 ] [11 ],,, 11211,, (Join count statistics), Moran s I, Geary s C Getis G, Moran s I [5 ] Moran I,, 1 0,, :

4 6 : 959 I = S 0 W ( i, j) ( X i - gx) ( X j - gx) i = 1 j = 1 ( X i - gx) 2 i i = 1 :, X i, gx X i, S0 = W ( i, j) i = 1 j = 1 W ( i, j) i j,, W ( i, i) = 0 W ( n n),,,,, : W a ( i, j) =, : W d ( i, j) = 1 i j 0 i j 1 i j 0 Moran,, z [13 ] z ( I) = I - E( I) S ( I), S ( I) = var ( I) 11212,, [23,24 ], ( ) ( ),, Moran s I [14 ],, Getis G Geary s C [ 25 ], Moran I Moran I Anselin L I2 SA [14 ], (Local Indicators of Spatial Association) i, Ii : Ii = X i - gx S 3 (6) W ( i, j) ( X j - gx) (7) :, X i, gx, W ( i, j) (6), S3 = ( X 2 j ) / ( - 1) - gx 2 ; j =1,j i L ISA z z ( Ii) = Ii - E( Ii ), S ( Ii) = var ( Ii) S ( Ii) 113 j = 1,,,,,,

5 960 24, ( Kriging),,,,, : g ( h) = : ( h) h, z ( ua) ( h) 1 2 ( h) [ z ( a = 1 ua ) - z ( ua + h) ] 2 (8) ua ( 244 ) ARCGIS,, ( 1) 1 Fig11 The distribution of the new houses in Beijing , 13 8, Lee ArcView [26 ], : 261, 21509, S - K , 95 %, S - K , S - K

6 6 : 961,, [27,28 ] (3),, CrimeStat, 1 1 Tab11 earest neighbor analysis of houses in Beijing (m) (m) (m) Z , 2 Fig12 Different orders I of houses in Beijing Ripley s K (5), K, 0 20km,,, ( 3) K Fig13 Ripley s K of houses in Beijing (6), Moran I 0163, Z

7 p < 01001,,,, (7), GeoDA, Local Moran I,, ( ), ;, ;,, ;,, Moran I,, 4, Moran I,,, [ 12 ] Arc GIS, ( 4 5),,,, 5,, Arc GIS, (Ordinary Kriging), : (Mean) ; ( Mean Standardized) ; ( Root2Mean2 Square Standardized) 11018, 4 6 :, ;, ;, ; 3 (1),, ;, (2), K K

8 6 : 963, (3), ;, Krige,, (4), 2003,,,, : [ 1 ] Haggett P1 The Geographical Structure of Epidemics1 ew York : Clarendon Press, [ 2 ],, 1 1, 2005,24 (1) : [ 3 ] Anselin L1 The future of spatial analysis in t he social sciences1 Geographic Information Sciences, 1999,5 (2) : [ 4 ],, 1 1, 1999, 18 (2) : [ 5 ],,, 1 1, 2000, 55 (1) : [ 6 ] Haining R1 Spatial Data Analysis in t he Social and Environmental Sciences1 Cambridge, U1 K1,Cambridge Univer2 sity Press,19911 [ 7 ] Pace R Kelley, Ronald Barry,C F Sirmans. Spatial statistics and real estate1 Journal of Real Estate Finance and E2 conomics,1998,17 (1) :5 131 [ 8 ],, 1 1, 2002, 21 (6) : [ 9 ], 1 Kriging 1,2001,21 (5) : [ 10 ],, 1 1,2003,25 (4) :85 92 [ 11 ],, 1 1 ( ),2003,28 (5) : ,5971 [ 12 ],,, 1 1,2004,24 (1) :7 131 [ 13 ] Cliff A, Ord J1 Spatial Processes :Models and Applications. Pion, London,19811 [ 14 ],,, 1 1, 2005,24 (3) : [ 15 ] Diggle P J1 Statistical Analysis of Spatial Point Patterns1 London :Academic Press, [ 16 ] Fort heringham A S,Brunsdon C,Charlton M1 Qualitative Geography : Perspectives on Spatial Data Analysis1 Lon2 don : SA GE Publications [ 17 ] Clark P J, Evans F C1 Distance to nearest neighbor as a measure of spatial relationships in populations1 Ecology, 1954,35 (4) : [ 18 ] Ripley B D1 Spatial Statistics1 Chichester : John Wiley, [ 19 ] Ripley B D1 Modelling spatial patterns1 J1 R1 Stat1 Soc1 B1, 1977,39 : [ 20 ] Cressie 1 Statistical for Spatial Data1 ew York : Wiley,1989 [ 21 ] Anselin L1 Spatial econometrics1 In :Baltagi B (ed1). Companion to Econometrics1 Oxford : Basil Blackwell, [ 22 ] Tobler W A1 A computer movie simulating urban growt h in t he Detroit region1 Economic Geography, 1970, 46 ( 2) : [ 23 ] Anselin L1 Local indicators of spatial association L ISA1 Geographical Analysis, 1995,27 (2) : [ 24 ] Getis A, Ord J K1 The analysis of spatial association by use of distance statistics1 Geographical Analysis, 1992, 24 (3) : [ 25 ] Ord J K, Getis A1 Local spatial autocorrelation statistics : distributional issues and an application1 Geographical A2

9 nalysis,1995, 27 : [ 26 ] Lee J,Wong D W S1 Statistical Analysis wit h ArcView GIS1 ew York : John Wiley & Sons, Inc1, [ 27 ],,, 1 1,2002,21 (1) : [ 28 ] 1 1, 2003, 23 (3) : Application of spatial analysis to the research of real estate :taking Beijing as a case ME G Bin 1,2, ZHA GJing2qiu 1, WA G Jin2feng 2, ZHA G Wen2zhong 2, HAO Wei2qiu 1 (11 College of Art s & Sciences, Beijing Union University, Beijing , China ; 21 Institute of Geographic Sciences and atural Resources Research, CAS, Beijing , China) Abstract :In social and enviro nmental sciences, researcher s are interested in t he analysis and modeling of t he spatial data1 Unlike ordinary data, t he locations of t he observation are also concerned as well as the values relating to t he object s in spatial data analysis1 Real es2 tate has gone through a dramatic growt h in China t hese years,and t here were a lot of re2 searches on t he develop ment of real estate1 But most of t he st udies just considered the so2 cial and economic attributes of t he real estate1 The location of t he real estate was not f ully considered1 Wit h the develop ment of t he Geograp hical Information Sciences ( GISc), t he t heories and met hods about spatial dada analysis developed too1 And t here are more tools and softwares focused on spatial analysis, which improved t he application of t he spatial da2 ta analysis1 In t his paper, the way of spatial data analysis, such as point pattern analysis, spatial correlatio n analysis and spatial interpolatio n were reco mmended and used in t he st udy about t he real estate in Beijing, t he capital of China1 By using t he quadrat analysis, nearest neighbor analysis and Ripley s K f unction, t he clumped pattern of t he real estate in Beijing is found1 The Moran s I, which is often used to test t he spatial autocorrelation, al2 so suggest s t hat there is significant spatial autocorrelation in t he price of t he house in Bei2 jing1 This means t hat the research about t he price of t he house in Beijing must concern a2 bo ut t his important characteristic1by use of ordinary kirging, t he spatial pattern of t he house price in Beijing was simulated, and the result s also show that t he price has some in2 teresting relationship wit h t he develop ment of t he city it self1 Key words :point pat tern analysis ; spatial autocorrelatio n ; spatial interpolatio n ; real estate

Identifying Schools for the Fruit in Schools Programme

1 Identifying Schools for the Fruit in Schools Programme Introduction This report identifies New Zeland publicly funded schools for the Fruit in Schools programme. The schools are identified based on need.