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Statistical Descriptions of Spatial Patterns

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Encyclopedia of GIS

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Definition

Spatial statistics can be defined as a statistical description of spatial data and a spatial pattern or process. Spatial statistics allow a quantitative description along with indications of statistical significance in observational data on a pattern or a process operating in space. This quantitative and statistical description allows the exploration and modeling of spatial patterns and processes and their relationships with other spatial phenomena. Spatial statistics differ from traditional statistics in that spatial statistics integrate space and spatial relationships in the analysis. Spatial statistics can be used with continuous data as well as three different types of object data: points, lines, and areas [1]. Different spatial statistics can be used depending on the type of data available. Lastly, spatial statistics are closely related to a broader term “spatial analysis”, which includes spatial data visualization in a geographic information systems (GIS) environment,...

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Recommended Reading

  1. Bailey, T.C., Gatrell, A.C.: Interactive Spatial Data Analysis. Prentice Hall, Harlow, UK (1995)

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Author information

Authors and Affiliations

  1. GIS Training and Research Center, Idaho State University, Pocatello, ID, USA

    Temuulen Tsagaan Sankey

Authors
  1. Temuulen Tsagaan Sankey
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Editor information

Editors and Affiliations

  1. Faculty of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, 55455, USA

    Shashi Shekhar (McKnight Distinguished University Professor) (McKnight Distinguished University Professor)

  2. Management Science and Information Systems Department, Rutgers Business School Newark and New Brunswick Rutgers, the State University of New Jersey, Newark, NJ, 07102, USA

    Hui Xiong (Assistant Professor) (Assistant Professor)

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© 2008 Springer-Verlag

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Sankey, T. (2008). Statistical Descriptions of Spatial Patterns. In: Shekhar, S., Xiong, H. (eds) Encyclopedia of GIS. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35973-1_1351

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