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phytosociological surveys and (or) other vegetation analysis approaches that are strongly affected by disturbances (Barnes et al. 1998). Apart other deficits, the collection of this kind of data and analysis are expensive (see Smith et al. 1997), compared to the parameters used in the present study, since no background information regarding the tree age or other difficult to access information are needed. Moreover, in a quite high degree, the site classification using these parameters is not influenced by disturbances.
The boosting method for creating a collective classifier for site qualities, obviously will give far more accurate classifications of site productivity if a more sophisticated scheme of data collection is used. Since site productivity may present significant spatial variation (Skovsgaard and Vanclay 2013), a stand can exhibit more than one site productivity categories. Consequently, stand area must be divided in parts, regarding some characteristics that strongly influence productivity. Topography is such a factor. Thus, in the first step, a stand is divided in rather homogenous areas regarding the shape of the terrain (conceive, convex, inclined plane and other), the exposure or another characteristic that is considered crucial for site productivity determination. In a second step, inside these areas, easily measured or estimated parameters for the site classification, as in the present case, can be used for the estimation of site productivity, such as highest, lowest and mean slope, highest and lowest canopy density. The mean canopy density can be used in areas that are not strongly influenced by disturbances. Moreover, other parameters can be used for the estimation of site productivity; thickness or other characteristics of organic layer of forest floor are some of them (see Laamrani et al. 2014).
Some of the above – mentioned parameters can be easily measured using remote sensing data, but for others like canopy density, field observations are obligatory for their estimation. Pinno et al. (2009) refer that field measurements are needed in order to have precision in the prediction of site productivity within a forest management unit for Populus tremuloides in the Boreal Shield of Quebec.
In the case of mixed stands, either in groups or in a tree to tree basis site productivity, classification has to be conducted for each species and tree to tree mixture (Aertsen et al. 2012; Skovsgaard and Vanclay 2013). So, for each species or mixture, the above mentioned two-step process have to be applied.
The usage of boosting method for creating a collective classifier for site qualities in the studied forest can be characterized as fully successful. The application of this method using altitude, slope, age and canopy density as input, do not need background information regarding the tree age and (or) other information that is difficult to access. Moreover, in a quite high degree, this site classification is not influenced by disturbances. The boosting method for creating a collective classifier for site qualities, obviously will give far more accurate classifications of site productivity, if a more sophisticated scheme of data collection is used.
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