Import of kNN: Difference between revisions
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However, such mean values are not sufficient for the long-term prognoses and the advanced forest management simulations to be analysed by the system. Single tree-data is here needed, preferably as a sample of plots with trees (or seedlings or saplings). Instead of using the pixelwise mean values, the nearest neighbour is imputed, i.e. ''k'' = 1. This specific reference plot is identified in the NFI database (by "�?R-TRAKT-P�?LSLAG") where the actual inventory could have been performed years ago (hence, an outlier-reduction of the reference database is first done, excluding plots with assumed major changes in forest state). A suitable reference database is firstly defined by the same region- and county-code as the analysis area, possibly also a range in altitude (e.g. 100 - 300 meters a.s.l.). Moreover, instead of imputing a plot to each pixel of the current stand, the imputation could be performed in a sample of corresponding pixels (randomly or systematically sampled). A sample of, e.g., 10 pixels will imply the imputation of 10 plots per stand. | However, such mean values are not sufficient for the long-term prognoses and the advanced forest management simulations to be analysed by the system. Single tree-data is here needed, preferably as a sample of plots with trees (or seedlings or saplings). Instead of using the pixelwise mean values, the nearest neighbour is imputed, i.e. ''k'' = 1. This specific reference plot is identified in the NFI database (by "�?R-TRAKT-P�?LSLAG") where the actual inventory could have been performed years ago (hence, an outlier-reduction of the reference database is first done, excluding plots with assumed major changes in forest state). A suitable reference database is firstly defined by the same region- and county-code as the analysis area, possibly also a range in altitude (e.g. 100 - 300 meters a.s.l.). Moreover, instead of imputing a plot to each pixel of the current stand, the imputation could be performed in a sample of corresponding pixels (randomly or systematically sampled). A sample of, e.g., 10 pixels will imply the imputation of 10 plots per stand. | ||
By ''k''NN imputation the forest state of a stand is described by sample plots, seemingly field inventoried in the current stand. Some things give the hoax away though; the within-stand variation regarding volume, age, etc. might be | By ''k''NN imputation the forest state of a stand is described by sample plots, seemingly field inventoried in the current stand. Some things give the hoax away though; the within-stand variation regarding volume, age, etc. might be either unrealisticly low (if the imputation is done "with replacement", i.e. one reference plot can represent a stand more than once) or unrealisticly high (e.g., Maturity class K1 and S1 should not occur in the same stand, such stand should in real life be split into two stands). | ||