Showing papers on "Data aggregator published in 1991"
TL;DR: A proposed general framework learning to live with errors in spatial databases and the traditional and modern look at Tissot's indicatrix are proposed.
Abstract: Error modelling for the map overlay operation modelling error in overlaid categorical maps user considerations in landscape characterization knowledge-based approaches to determining and correcting areas of unreliability in geographical databases observations and comments on the generation and treatment of error in digital GIS data developing confidence limits on errors of suitability analyses in geographical information systems distance calculations and errors in geographical databases inclusion of accuracy data in a feature based, object- orientated data model accuracy and bias issues in surface representation modelling error in objects and fields frame independence spatial analysis modelling locational uncertainty via hierarchical tesselation minimum cross-entropy convex decompositions of pixel-indexed stochastic matrices - a geographical application of the Ising model the traditional and modern look at Tissot's indicatrix real data and real problems - dealing with large spatial databases the small number problems and the accuracy of spatial databases demand point approximations for location problems modelling realibility on statistical surfaces by polygon filtering scale-independent spatial analysis the effect of data aggregation on a poisson model of Canadian migration statistical methods for inference between incompatible zonal systems statistical effect of spatial data transformations - a proposed general framework learning to live with errors in spatial databases.
346 citations