GeoInformatica

, Volume 15, Issue 3, pp 399–416 | Cite as

Controlling patterns of geospatial phenomena

  • Tomasz F. Stepinski
  • Wei Ding
  • Christoph F. Eick
Article

Abstract

Modeling spatially distributed phenomena in terms of its controlling factors is a recurring problem in geoscience. Most efforts concentrate on predicting the value of response variable in terms of controlling variables either through a physical model or a regression model. However, many geospatial systems comprises complex, nonlinear, and spatially non-uniform relationships, making it difficult to even formulate a viable model. This paper focuses on spatial partitioning of controlling variables that are attributed to a particular range of a response variable. Thus, the presented method surveys spatially distributed relationships between predictors and response. The method is based on association analysis technique of identifying emerging patterns, which are extended in order to be applied more effectively to geospatial data sets. The outcome of the method is a list of spatial footprints, each characterized by a unique “controlling pattern”—a list of specific values of predictors that locally correlate with a specified value of response variable. Mapping the controlling footprints reveals geographic regionalization of relationship between predictors and response. The data mining underpinnings of the method are given and its application to a real world problem is demonstrated using an expository example focusing on determining variety of environmental associations of high vegetation density across the continental United States.

Keywords

Predictors–response relationship Association analysis Mapping predicting relationship Vegetation density Data mining 

Notes

Acknowledgements

The work is supported in part by the National Science Foundation under Grant IIS-0812271. A portion of this research was conducted at the Lunar and Planetary Institute, which is operated by the USRA under contract CAN-NCC5-679 with NASA. This is LPI Contribution No.1532.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Tomasz F. Stepinski
    • 1
  • Wei Ding
    • 2
  • Christoph F. Eick
    • 3
  1. 1.Lunar and Planetary InstituteHoustonUSA
  2. 2.Department of Computer ScienceUniversity of Massachusetts BostonBostonUSA
  3. 3.Department of Computer ScienceUniversity of HoustonHoustonUSA

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