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Abstract Details
Activity Number:
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7
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Type:
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Invited
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Date/Time:
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Sunday, July 31, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Environmental and Ecological Statistics
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Abstract - #300319 |
Title:
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Statistical Geoinformatics for Human Environment Interface
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Author(s):
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Wayne Lawrence Myers*+ and G. P. Patil
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Companies:
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Penn State University and Penn State University
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Address:
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Land & Water Research Bldg, Univ. Park, PA, 16802,
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Keywords:
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GeoInformatics ;
Spatial Analysis ;
GIS ;
Prioritization ;
Multivariate ;
Complexity
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Abstract:
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Geographic Information Systems (GIS) are built upon disparate sets of spatial constructs for representation of data jointly in location and attribute domains. Spatial statistics often contributes assumptions regarding process properties to the constructs of location and attribution. Most concerns regarding humans in relation to environment have a multivariate nature. Inference can entail formulation of models regarding response variable(s) in relation to contexts, or interest may lie directly in the complexities of the multivariate context. Disparate spatial constructs impede coordinating components in space and time for joint analysis. We impose point purviews on the contextual complex whereby coordination is accomplished by strategic imputation. Such a point purview can be considered as a poly-process, and spatial support is generalized to semi-support for variables involved. Different
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