Uncertainty analysis (UA) and Sensitivity analysis (SA) are prerequisites for model building. UA aims to quantify the overall uncertainty associated with the model response as a result of uncertainties in the model input. SA studies how the variation in the model output can be apportioned to different sources of variations. Both UA and SA have been successfully applied in many different fields. This paper describes the contribution that UA and SA can give in the field of GIS-based models. In the first part of the paper the fundamentals of UA and SA are introduced. The role UA and SA can play in the spatial modelling based on GIS is then addressed. In the last part, a general procedure to perform the two kinds of analysis on GIS-based models is proposed. An example of analysis of a simple hydrologic model is described. This research on GIS-based models, done at ISIS-JRC, provides effective tools for both the assessment of the quality of the model output and the optimisation of th
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