Dealing with Spatiotemporal Heterogeneity: The Generalized BME Model

  • Hwa-Lung YuEmail author
  • George Christakos
  • Patrick Bogaert
Part of the Advances in Spatial Science book series (ADVSPATIAL)


Geographical studies involving natural systems and their attributes (e.g., environmental processes, land use parameters, human exposure indicators, disease variables, and financial indexes) often need to quantitatively assess spatiotemporal dependence and generate informative maps of the attributes across space-time. These are important, indeed, goals of spatiotemporal systems modelling and data analysis introduced in a modern statistical framework by Christakos (1990, 1991a,b, 1992). Subsequent works include Goodall and Mardia (1994), Haas (1995), Bogaert (1996), Christakos and Hristopulos (1998), and Kyriakidis and Journel (1999). Among the more recent developments one should notice the works of Serre et al. (2003), Kolovos et al. (2002, 2004), Douaik et al. (2004), Christakos et al. (2002, 2005), Stein (2005), Law et al. (2006), Porcu et al. (2006, 2008), Yu et al. (2007a–c), Renshaw et al. (2008), and Ruiz-Medina et al. (2008a,b).


Hard Data Simulated Field Soft Information Soft Data Epistematics Knowledge 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Partial support for this work was provided by a grant from the California Air Resources Board, USA (Grant No. 55245A).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Department of Bioenvironmental Systems EngineeringNational Taiwan UniversityTaipeiTaiwan, R.O.C.

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