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This version was published on August 1, 2006
Journal of Information Science, Vol. 32, No. 4, 316-323 (2006)
DOI: 10.1177/0165551506065806

A total entropy model of spatial data uncertainty

Y. F. Shi

School of Architecture Engineering, Shandong University of Technology, Zibo, China, shyf{at}sdut.edu.cn, yufeng788{at}163.com

F. X. Jin

President Office, Shandong University of Science and Technology, Qingdao, China

M. Y. Li

Department of College English Teaching, Shandong University of Technology, Zibo, China

Uncertainty is inherent in spatial data and spatio-temporal phenomena. Spatial data uncertainty generally refers to error, inexactness, fuzziness and ambiguity. The goals of research on spatial data uncertainty are to investigate how uncertainties arise, or are created and propagated in the spatial data process. Based on information theory, considering the characteristics of randomicity of positional data and fuzziness of attribute data and taking entropy as a measure, this paper proposes the stochastic entropy model of spatial positional data uncertainty and fuzzy entropy model of spatial attribute data uncertainty. Usually, both randomicity and fuzziness exist in spatial data simultaneously, so their co-uncertainty is also investigated and quantified in this paper. A novel spatial data uncertainty measure, total entropy, is presented. Total entropy can be used as a uniform measure to quantify the total spatial data uncertainty caused by stochastic uncertainty and fuzzy uncertainty.

Key Words: spatial data uncertainty • total entropy • stochastic entropy • fuzzy entropy • uniform measure


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