By Hengl, Tomislav
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Extra info for A Practical Guide to Geostatistical Mapping of Environmental Variables
In addition, it allows the separate interpretation of the two interpolated components. , 2007b). The emphasis on regression is important also because fitting of the deterministic part of variation (regression) is often more beneficial for the quality of final maps than fitting of the stochastic part (residuals). 139-141), in which five measurements are used to predict a value of the target variable (z) at an unvisited location (s0 ) (Fig. 4a). We extend this example by adding a hypothetical auxiliary data source: a raster image (10Ö10 pixels) (Fig.
This confuses the users and distracts them from using the right technique for their mapping projects. In this section, we will show that both universal kriging, kriging with external drift and regregression-kriging are basically the same technique. Matheron (1969) originally termed the technique Le krigeage universel, however, the technique was intended as a generalized case of kriging where the trend is modelled as a function of coordinates. Thus, many authors (Deutsch and Journel, 1998; Wackernagel, 2003; Papritz and Stein, 1999) reserve the term Universal Kriging (UK) for the case when only the coordinates are used as predictors.
3c) because it is a generalization of the two models and can be more universally applied. 3) will show discrete changes (Fig. 1) will typically lead to smooth maps (Fig. 3b). 2 Mechanical spatial prediction models As mentioned previously, mechanical spatial prediction models can be very flexible and easy to use. They can be considered to be subjective or empirical techniques because the user him/her-self selects the parameters of the model, often without any deeper statistical analysis. Most commonly, a user typically accepts the default parameters suggested by some software, hence the name mechanical models.