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A Spatial Statistical Approach to Residential Differentiation (II): Exploratory Spatial Data Analysis Using a Local Spatial Separation Measure  

Lee, Sang-Il (Department of Geography Education, Seoul National University)
Publication Information
Journal of the Korean Geographical Society / v.43, no.1, 2008 , pp. 134-153 More about this Journal
Abstract
The main purpose of the research is to illustrate the value of the spatial statistical approach to residential differentiation by providing a framework for exploratory spatial data analysis (ESDA) using a local spatial separation measure. ESDA aims, by utilizing a variety of statistical and cartographic visualization techniques, at seeking to detect patterns, to formulate hypotheses, and to assess statistical models for spatial data. The research is driven by a realization that ESDA based on local statistics has a great potential for substantive research. The main results are as follows. First, a local spatial separation measure is correspondingly derived from its global counterpart. Second, a set of significance testing methods based on both total and conditional randomization assumptions is provided for the local measure. Third, two mapping techniques, a 'spatial separation scatterplot map' and a 'spatial separation anomaly map', are devised for ESDA utilizing the local measure and the related significance tests. Fourth, a case study of residential differentiation between the highly educated and the least educated in major Korean metropolitan cities shows that the proposed ESDA techniques are beneficial in identifying bivariate spatial clusters and spatial outliers.
Keywords
exploratory spatial data analysis (ESDA); spatial separation measure; local statistics; residential segregation; spatial dependence;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 Anselin, L., 1995, Local indicators of spatial association: LISA, Geographical analysis, 27(2), 93-115   DOI
2 Bailey, T. C., 1994, A review of statistical spatial analysis in geographical information systems, in Fotheringham, A. S. and Rogerson, P. (eds.), Spatial analysis and GIS, Taylor & Francis, London, 13-44
3 Feitosa, F. F., Camara, G., Monteiro, A. M. V., Koschitzki, T., and Silva, M. P. S., 2007, Global and local spatial indices of urban segregation, International Journal of Geographical Information Science, 21(3), 299-323   DOI   ScienceOn
4 Fotheringham, A. S., 2000, Context-dependent spatial analysis: a role for GIS-, Journal of Geographical Systems, 2(1), 71-76   DOI
5 Fotheringham, A. S. and Charlton, M., 1994, GIS and exploratory spatial data analysis, an overview of some research issues, Geographical Systems, 1(4), 315-327
6 Hubert, L. J., 1987, Assignment Methods in Combinatorial Data analysis, Marcel Dekker, New York
7 Lee, S.-I., 2001b, Spatial association Measures for an ESDa-GIS Framework: Developments, Significance Tests, and applications to Spatiotemporal Income Dynamics of U.S. Labor Market areas, 1969-1999, Ph.D. Dissertation, Department of Geography, The Ohio State University
8 Lee, S.-I., 2004b, Spatial data analysis for the U.S. regional income convergence, 1969-1999: A critical appraisal of $\beta$-convergence, Journal of the Korean Geographical Society, 39(2), 212-228
9 Lee, S.-I., 2004c, A generalized significance testing method for global measures of spatial association: an extension of the Mantel test, Environment and Planning A, 36(9), 1687-1703   DOI
10 Maly, M. T., 2000, The neighborhood diversity index: a complementary measure of racial residential settlement, Journal of Urban affairs, 22(1), 37- 47   DOI   ScienceOn
11 Openshaw, S. and Clarke, G., 1996, Developing spatial analysis functions relevant to GIS environments, in Fischer, M., Scholten, H., and Unwin, D. (eds.), Spatial analytical Perspectives on GIS, Taylor & Francis, London, 21-37
12 Rogerson, P. A., 1999, The detection of clusters using a spatial version of the chi-square goodness-of-fit statistic, Geographical analysis, 31(1), 130-147   DOI
13 Sokal, R. R., Oden, N. L., and Thomson, B. A., 1998, Local spatial autocorrelation in a biological model, Geographical Analysis, 30(4), 331-354   DOI
14 Wise, S., Haining, R., and Signoretta, P., 1999, Scientific visualization and the exploratory analysis of area data, Environment and Planning A, 31(10), 1825-1838   DOI
15 Wong, D. W. S., 2002, Modeling local segregation: a spatial interaction approach, Geographical & Environmental Modelling, 6(1), 81-97   DOI
16 Good, I. J., 1983, The philosophy of exploratory data analysis, Philosophy of Science, 50(2), 283-295   DOI   ScienceOn
17 Wong, D. W. S., 2003, Spatial decomposition of segregation indices: A framework toward measuring segregation at multiple levels, Geographical analysis, 35(3), 179-194   DOI
18 Cliff, A. D. and Ord, J. K., 1981, Spatial Processes: Models & applications, Pion Limited, London
19 Lee, S.-I., 2005, Between the quantitative and GIS revolutions: Towards an SDA-centered GIScience, Journal of Geography Education, 49, 268-284
20 Anselin, L., 1996, The Moran scatterplot as an ESDA tools to assess local instability in spatial association, in Fischer, M., Scholten, H., and Unwin, D. (eds.), Spatial analytical Perspectives on GIS, Taylor & Francis, London, 111-125
21 Goodchild, M. F., Haining, R., Wise, S., et al., 1992, Integrating GIS and spatial data analysis: problems and possibilities, International Journal of Geographical Information Systems, 6(5), 407-423   DOI
22 Openshaw, S., 1990, Spatial analysis and geographical information systems: a review of progress and possibilities, in Scholten, H. and Stillwell, J. (eds.), Geographical Information Systems for Urban and Regional Planning, Kluwer, Dordrecht, 153-163
23 Chung, S.-Y. and Brown, L. A., 2007, Racial/ethnic residential sorting in spatial context: Testing the exploratory frameworks, Urban Geography, 28(4), 312-339   DOI
24 Tukey, J. W., 1977, Exploratory Data analysis, addison- Wesley, Reading, MA
25 Getis, A. and Ord, J. K., 1996, Local spatial statistics: an overview, in Longley, P. and Batty, M. (eds.), Spatial analysis: Modelling in a GIS Environment, GeoInformation International, Cambridge, 261-277
26 Hubert, L. J., 1984, Statistical applications of linear assignment, Psychometrika, 49(4), 449-473   DOI
27 Tiefelsdorf, M., 1998, Some practical applications of Moran's I's exact conditional distribution, Papers in Regional Science, 77(2), 101-129   DOI
28 Brown, L. A. and Chung, S.-Y., 2006, Spatial segregation, segregation indices and the geographical perspective, Population, Space and Place, 12(2), 125-143   DOI   ScienceOn
29 Unwin, D. J., 1996, GIS, spatial analysis and spatial statistics, Progress in Human Geography, 20(4), 540-551   DOI
30 이상일, 2007, '거주지 분화에 대한 공간통계학적 접근 (I): 공간 분리성 측도의 개발,' 대한지리학회지, 42(4), 616-631   과학기술학회마을
31 Oden, 1995, adjusting Moran's I for population density, Statistics in Medicine, 14(1), 17-26   DOI   ScienceOn
32 Fotheringham, A. S., 1997, Trends in quantitative methods I: stressing the local, Progress in Human Geography, 21(1), 88-96   DOI
33 Lee, S.-I., 2001a, Developing a bivariate spatial association measure: an integration of Pearson' s r and Moran's I, Journal of Geographical Systems, 3(4), 369-385   DOI
34 Lee, S.-I., 2008, A generalized randomization approach to local measures of spatial association, Geographical analysis, under revision
35 Anselin, L., 1998, Exploratory spatial data analysis in a geocomputational environment, in Longley, P. A., Brooks, S. M., McDonell, R., and MacMillan, B. (eds.), Geocomputation: a Primer, John Wiley & Sons, Chichester, West Sussex, 77-94
36 Anselin, L., Syabri, I., and Smirnov, O., 2002, Visualizing multivariate spatial correlation with dynamically linked windows, in Anselin, L. and Rey, S. (eds.), New Tools for Spatial Data analysis: Proceedings of the Specialist Meeting, Center for Spatially Integrated Social Science (CSISS), University of California, Santa Barbara
37 Boots, B. and Tiefelsdorf, M., 2000, Global and local spatial autocorrelation in bounded regular tessellations, Journal of Geographical Systems, 2(3), 319-348   DOI
38 Lee, S.-I., 2004a, Exploratory spatial data analysis of $\sigma$- convergence in the U.S. regional income distribution, 1969-1999, Journal of the Korean Urban Geographical Society, 7(1), 79-95
39 Fischer, M. M. and Nijkamp, P., 1992, Geographic information systems and spatial analysis, Annals of Regional Science, 26(1), 3-17   DOI
40 최은영, 2004, 서울시 거주지 분리 심화와 교육환경의 차별화, 서울대학교 대학원 사회교육과(지리전공) 박사학위논문
41 Leung, Y., Mei, C.-L., and Zhang, W.-X., 2003, Statistical test for local patterns of spatial association, Environment and Planning A, 35(4), 725-744   DOI