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Outlier Detection, Spatial

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Encyclopedia of GIS
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Synonyms

Spatial Anomaly Detection

Definition

Spatial outliers or abnormal spatial patterns are those spatial objects whose non-spatial attribute values are markedly different from those of their spatial neighbors. The identification of spatial outliers can be used to reveal hidden but valuable knowledge in many applications. For example, it can help locate extreme meteorological events such as tornadoes and hurricanes, identify aberrant genes or tumor cells, discover highway traffic congestion points, pinpoint military targets in satellite images, determine possible locations of oil reservoirs, and detect water pollution incidents.

Historical Background

Data mining is a process used to dig out useful “nuggets of information” from large amounts of data stored either in databases, data warehouses, or other information repositories (Han and Kamber, 2001). These “nuggets” can be used to identify the patterns that occur frequently, illustrate the interesting associations among different...

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References

  • Anselin L (1994) Exploratory spatial data analysis and geographic information systems. In: New tools for spatial analysis. Eurostat, Luxemburg, pp 45–54

    Google Scholar 

  • Anselin L (1995) Local indicators of spatial association: Lisa Geogr Anal 27(2):93–115

    Article  Google Scholar 

  • Cerioli A, Riani M (1999) The ordering of spatial data and the detection of multiple outliers. J Comput Graph Stat 8(2):239–258

    MathSciNet  Google Scholar 

  • Haining R (1993) Spatial data analysis in the social and environmental sciences. Cambridge University Press, Cambridge

    Google Scholar 

  • Han J, Kamber M (2001) Data mining concepts and techniques. Morgan Kaufmann Publishers, San Francisco

    MATH  Google Scholar 

  • Koperski K, Adhikary J, Han J (1996) Spatial data mining: progress and challenges. In: Workshop on research issues on data mining and knowledge discovery (DMKD’96), Montreal, June 1996, pp 1–10

    Google Scholar 

  • Lu C-T, Liang LR (2004) Wavelet fuzzy classification for detecting and tracking region outliers in meteorological data. In: GIS ’04: Proceedings of the 12th annual ACM international workshop on geographic information systems, Washington, DC, 12–13 Nov 2004, pp 258–265

    Google Scholar 

  • Lu C-T, Chen D, Kou Y (2003) Algorithms for spatial outlier detection. In: Proceedings of the third IEEE international conference on data mining, Melbourne, 19–22 Nov 2003, pp 597–600

    Google Scholar 

  • Rigaux P, Scholl M, Voisard A (2001) Spatial databases: with application to GIS, 2nd edn. Morgan Kaufmann Publishers, San Francisco

    Google Scholar 

  • Shekhar S, Chawla S (2002) A tour of spatial databases. Prentice Hall, Upper Saddle River (2002)

    Google Scholar 

  • Shekhar S, Lu C-T, Zhang P (2003) A unified approach to detecting spatial outliers. GeoInformatica 7(2):139–166

    Article  Google Scholar 

  • Tobler W (1979) Cellular geography. In: Philosophy in geography. Dordrecht Reidel Publishing Company, Dordrecht/Holland, pp 379–386

    Chapter  Google Scholar 

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Kou, Y., Lu, CT. (2016). Outlier Detection, Spatial. In: Shekhar, S., Xiong, H., Zhou, X. (eds) Encyclopedia of GIS. Springer, Cham. https://doi.org/10.1007/978-3-319-23519-6_945-2

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  • DOI: https://doi.org/10.1007/978-3-319-23519-6_945-2

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  • Online ISBN: 978-3-319-23519-6

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