interpolation based on a weighted mean of nearby data, with weights determined by a continuity model. Within this framework, spatial modeling is primarily concerned with interpolation, yielding a single “best” representation of the unknown variable at unsampled locations. Although uncertainty is formally quantified through the kriging variance, it remains implicitly summarized around the estimated mean, and the spatial variability away from this mean is not explicitly reproduced. Journel and collaborators (Journel & Huijbregts, 1978; Journel, 1983; Journel & Alabert, 1989) developed a probabilistic framework for stochastic simulation, shifting the focus of geostatistical modeling from deterministic to probabilistic. Rather than producing a single “best” interpolation, stochastic simulation generates multiple equiprobable realizations representing possible spatial scenarios.
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