Raster Representations Of Spatial Attributes With Uncertainty Assessment Using Nonlinear Stochastic Simulation
24 September 2001
Carlos Alberto Felgueiras; Suzana Druck Fuks; Antonio Miguel Vieira Monteiro
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.
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