Abstract
This paper uses a spatial statistics method based on the calculation of spatial autocorrelation as a possible approach for modeling and quantifying the distribution of urban land price in Changzhou City, Jiangsu Province. GIS and spatial statistics provide a useful way for describing the distribution of urban land price both spatially and temporally, and have proved to be useful for understanding land price distribution pattern better. In this paper, we apply the statistical analysis method to 8379 urban land price samples collected from Changzhou Land Market, and it is turned out that the proposed approach can effectively identify the spatial clusters and local point patterns in dataset and forms a general method for conceptualizing the land price structure. The results show that land price structure in Changzhou City is very complex and that even where there is a high spatial autocorrelation, the land price is still relatively heterogeneous. Furthermore, lands for different uses have different degrees of spatial autocorrelation. Spatial autocorrelation of commercial lands is more intense than that of residential and industrial lands in regional central district. This means that treating land price as integration of homogeneous units can limit analysis of pattern, over-simplifying the structure of land price, but the methods, just as the autocorrelation approaches, are useful tools for quantifying the variables of land price.
Similar content being viewed by others
References
ALAN Gelfand, MARK Ecker, JOHN Knight et al., 2004. The Dynamics of Location in Home Price [J]. Journal of Real Estate Finance and Economics, 29(2): 149–166.
ANA Militino, LOLA Ugarte, GARCIA-REINALDOS L, 2004. Alternative models for describing spatial dependence among residential selling prices [J]. Journal of Real Estate Finance and Economics, 29(2): 193–209.
ANSELIN Luc, 1995. Local indicators of spatial association—LISA [J]. Geographical Analysis, 27(2): 93–115.
ANSELIN Luc, 1998. GIS research infrastructure for spatial analysis of real estate markets [J]. Journal of Housing Research, 9(1): 113–133.
ASTRON, 2004. Developing a Methodology to Capture Land Value Uplift around Transport Facilities [M]. Edinburgh, Scotland: Scottish Executive, 118.
BASU Sabyasachi, THIBODEAU Thomas G, 1998. Analysis of spatial autocorrelation in house prices [J]. Journal of Real Finance and Economics, 17(1): 61–85.
BRADFORD Case, JOHN Clap, ROBIN Dubin et al., 2004. Modeling spatial and temporal house price patterns: a comparison of four models [J]. Journal of Real Estate Finance and Economics, 29(2): 167–191.
CSB (Changzhou Statistical Bureau), 2004. Changzhou Statistical Yearbook [R]. Beijing: China Statistics Press. (in Chinese)
DAVID D, BRZESKI W Jan, 2001. Spatial regression analysis of commercial land price gradients [EB/OL]. http://www.usc.edu/schools/sppd/lusk/research/pdf/wp_2001-1008.pdf.
DIANE M Pearson, 2002. The application of local measures of spatial autocorrelation for describing pattern in North Australian Landscapes [J]. Journal of Environmental Management, 64: 85–95.
DUBIN Robin A, 1992. Spatial autocorrelation and neighborhood quality [J]. Regional Science and Urban Economics, 22: 433–52.
GILLEN Kevin, THIBODEAU Thomas, WACHTER Susan, 2001. Anisotropic autocorrelation in house prices [J]. Journal of Real Finance and Economics, 23(1): 5–30.
GOODCHILD M F, 1986. Spatial Autocorrelation [M]. Norwich, UK: GeoBooks, 56.
JAMES Lesage, KELLEY Pace, 2004. Models for spatially dependent missing data [J]. Journal of Real Estate Finance and Economics, 29(2): 233–254.
MCCOY Jill, JOHNSTON Kevin, KOPP Steve et al., 2001. Using ArcGISTM Spatial Analyst [M]. Redlands, CA: Environmental System Research Institute.
SUN Yan, LI Man-chun, LIU Zhong-gong et al., 2004. Design and implementation of Changzhou (Jiangsu Province) urban land price dynamic monitoring information system [J]. Journal of Nanjing University (Natural Sciences), 40(3): 389–393. (in Chinese)
TOBLER Waldo, 1979. Philosophy in Geography [M]. Dordrecht, Netherlands: D Reidel Publishing Company, 379–386.
Author information
Authors and Affiliations
Additional information
Foundation item: Under the auspices of the National Natural Science Foundation of China (No. 40371091), Land Monitoring Project of the Ministry of Land and Resources of P. R. China (No. 2005-6.1-6)
Biography: LIU Zhong-gang (1974–), male, a native of Chaoyang of Liaoning Province, Ph.D. candidate, specialized in GIS designing and application, spatial statistics and modeling. E-mail: lzg_com@sina.com
Rights and permissions
About this article
Cite this article
Liu, Zg., Li, Mc., Sun, Y. et al. Study on spatial autocorrelation of urban land price distribution in Changzhou city of Jiangsu Province. Chin. Geograph.Sc. 16, 160–164 (2006). https://doi.org/10.1007/s11769-006-0011-8
Received:
Issue Date:
DOI: https://doi.org/10.1007/s11769-006-0011-8