Encapsulating Simulation Models With Geospatial Data Sets

Abstract

Traditionally, spatial data producers have used data specifications and summary statistics to report data quality information, while the onus of applying this quality information to account for spatial uncertainty has rested with the spatial data user. A conceptual framework is developed to encapsulate a stochastic simulation algorithm with a geospatial data set. This approach allows the user to automatically generate a set of equally probable realizations of the spatial phenomenon using the best information available. Responsibility for providing the simulation method and specific model parameters rests with the data producer. Illustrations using different forms of geospatial data are provided, and the feasibility of the approach is evaluated.