Methods : Uncertainty

Glossary adjustment theory: the theory of errors in survey measurements frequentist: holding to the view that probability must be defined through experiment, as a proportion of events fuzzy set: a set defined by membership in a specific class, with membership allowed to be partial Gaussian (or Normal) distribution: a description of the relative sizes of errors in repeated measurements, a mathematical function resembling a bell geostatistics: the theory of regionalized variables, or spatial variables subject to spatial dependence metadata: the description or documentation of a data set Monte Carlo simulation: simulation of multiple realizations of a statistical model, for example by tossing a coin rough set: a set defined by a mix of full and partial membership subjectivist: holding to the view that probability can be defined subjectively, as a value that determines individual behavior Taylor series expansion: a form of approximation of a nonlinear function Tobler's First Law: nearby things are more similar than distant things, a widely observed tendency of geographic information Synopsis The representations that constitute the bulk of geographic knowledge must leave their users uncertain to some degree about the nature of the real world. Knowledge of geographic uncertainty is essential in geographic research, in decision making, and in everyday life. A variety of methods have been devised for measuring the degree of uncertainty inherent in geographic information. Models of uncertainty make use of the theoretical constructs of fuzzy and rough sets, spatial statistics, and geostatistics. Much progress has been made in recent years in developing methods for visualizing uncertainty, and for analyzing its propagation into the results of geographic research. Progress has also been made on the description of quality in data documentation, and in the use of data set quality as a dimension of the processes of search and discovery,