Abstract
We propose a method of modeling regional changes in local spatial association and classifying the changing regions based on the similarity of time-series signature of local spatial association. For intuitive recognition of time-series local spatial association, we employ Moran scatterplot and extend it to QS-TiMoS (Quadrant Sequence on Time-series Moran Scatterplot) that allows for examining temporal context in local spatial association using a series of categorical variables. Based on the QS-TiMoS signature of nodes and edges, we develop the similarity measures for “state sequence” and “clustering transition” of time-series local spatial association. The similarity matrices generated from the similarity measures are then used for producing the classification maps of time-series local spatial association that present the history of changing regions in clusters. The feasibility of the proposed method is tested by a case study on the rate of land price fluctuation of 232 administrative units in Korea, 1995-2004.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Anselin, L.: Local Indicators of Spatial Association - LISA. Geographical Analysis 27(2), 93–115 (1995)
Anselin, L.: The Moran Scatterplot as an ESDA Tool to Assess Local Instability in Spatial Association. In: Fisher, M., Scholten, H.J., Unwin, D. (eds.) Spatial Analytical Perspectives on GIS, pp. 111–125. Taylor & Francis, London (1996)
Bailey, T.C., Gatrell, A.C.: Interactive Spatial Data Analysis. Longman Scientific & Technical, Essex (1995)
Bera, R., Claramunt, C.: Topology-based Proximities in Spatial Systems. Journal of Geographical Systems 5(4), 353–379 (2003)
Boots, B.: Developing Local Measures of Spatial Association for Categorical Data. Journal of Geographical Systems 5(2), 139–160 (2003)
Fotheringham, A.S.: Trends in Quantitative Methods I: Stressing the Local. Progress in Human Geography 21(1), 88–96 (1997)
Fotheringham, A.S., Brunsdon, C.: Local Forms of Spatial Analysis. Geographical Analysis 31(4), 340–358 (1999)
Geary, R.C.: The Contiguity Ratio and Statistical Mapping. Incorporated Statistician 5(3), 115–145 (1954)
Getis, A., Ord, J.K.: The Analysis of Spatial Association by Use of Distance Statistics. Geographical Analysis 24(3), 186–206 (1992)
Lee, J., Wong, D.: Statistical Analysis with ArcView GIS. John Wiley & Sons, New York (2001)
Levenshtein, V.I.: Binary Codes Capable of Correcting Deletions, Insertions, and Reversals. Soviet Physics-Doklandy 10(8), 707–710 (1966)
Miller, H.J.: Tobler’s First Law and Spatial Analysis. Annals of the Association of American Geographers 94(2), 284–289 (2004)
Moran, P.: The Interpretation of Statistical Maps. Journal of Royal Statistical Society 10(2), 243–251 (1948)
Ord, J.K., Getis, A.: Local Spatial Autocorrelation Statistics: Distribution Issues and an Application. Geographical Analysis 27(4), 286–306 (1995)
Park, K.-H.: A Study on the Effect of Spatial Proximity Weight Matrices on the Spatial Autocorrelation Measures: The Case of Seoul Administrative Units. Research of Seoul & Other Cities 5(3), 67–83 (2004)
Rey, S.J.: Spatial Empirics for Regional Economic Growth and Convergence. Geographical Analysis 33(3), 195–214 (2001)
Tobler, W.: A Computer Movie Simulating Urban Growth in the Detroit Region. Economic Geography 46(2), 234–240 (1970)
Ward, J.: Hierarchical Grouping to Optimize an Objective Function. Journal of the American Statistical Association 58(301), 236–244 (1963)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ahn, JS., Lee, YW., Park, KH. (2006). Classification of Changing Regions Based on Temporal Context in Local Spatial Association. In: Todorovski, L., Lavrač, N., Jantke, K.P. (eds) Discovery Science. DS 2006. Lecture Notes in Computer Science(), vol 4265. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893318_6
Download citation
DOI: https://doi.org/10.1007/11893318_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46491-4
Online ISBN: 978-3-540-46493-8
eBook Packages: Computer ScienceComputer Science (R0)