Difference: Papers20100623113639 (1 vs. 2)

Revision 22010-07-23 - TWikiAdminUser

Changed:
<
<
META TOPICPARENT name="GeostatisticsPapers"
>
>
META TOPICPARENT name="AI_GEOSTATSPapers"
 Title: Raster Representations Of Spatial Attributes With Uncertainty Assessment Using Nonlinear Stochastic Simulation

Date:

Authors: Carlos Alberto Felgueiras; Suzana Druck Fuks; Antonio Miguel Vieira Monteiro

Link: http://www.geocomputation.org/2001/papers/felgueiras.pdf

Abstract:

Reference: Proceedings of the 6th International Conference on GeoComputation University of Queensland, Brisbane, Australia, 24 - 26 September 2001. CD-ROM produced by: David V. Pullar. Publisher: "GeoComputation CD-ROM". ISBN 1864995637

Raster representations of thematic and numerical spatial attributes are very common in a GIS environment for computational simulation and analysis of spatial processes. This paper addresses the problem of predictions with uncertainty assessment for GIS raster representations created from a set of sample points of spatial attributes. The realizations of a stochastic simulation process, over numerical attribute samples, are used for inferencing the attribute values and the related uncertainties at non-sampled spatial locations. A case study, using elevation sample data, is presented in order to illustrate the used methodology with real data.

-- TWikiAdminUser - 2010-06-16

Revision 12010-06-23 - TWikiAdminUser

 
META TOPICPARENT name="GeostatisticsPapers"
Title: Raster Representations Of Spatial Attributes With Uncertainty Assessment Using Nonlinear Stochastic Simulation

Date:

Authors: Carlos Alberto Felgueiras; Suzana Druck Fuks; Antonio Miguel Vieira Monteiro

Link: http://www.geocomputation.org/2001/papers/felgueiras.pdf

Abstract:

Reference: Proceedings of the 6th International Conference on GeoComputation University of Queensland, Brisbane, Australia, 24 - 26 September 2001. CD-ROM produced by: David V. Pullar. Publisher: "GeoComputation CD-ROM". ISBN 1864995637

Raster representations of thematic and numerical spatial attributes are very common in a GIS environment for computational simulation and analysis of spatial processes. This paper addresses the problem of predictions with uncertainty assessment for GIS raster representations created from a set of sample points of spatial attributes. The realizations of a stochastic simulation process, over numerical attribute samples, are used for inferencing the attribute values and the related uncertainties at non-sampled spatial locations. A case study, using elevation sample data, is presented in order to illustrate the used methodology with real data.

-- TWikiAdminUser - 2010-06-16

 
This site is powered by the TWiki collaboration platform Copyright © by the contributing authors. All material on this collaboration platform is the property of the contributing authors.
Ideas, requests, problems regarding TWiki? Send feedback