Proposed algorithm for the identification of rural areas with regard to variability of soil quality

An Algorithm for Delimiting Rural Areas According to Soil Classes

“…The study area is a complex of 44 villages forming an administrative part of six communes (gminas) in the district (poviat) of Brzozów, situated in southeastern Poland, in the Subcarpathian voivodeship (Figure 1). Studies carried out in this area [31,32] allowed the authors to collect study material in the form of data from a real property register referring to types and classes of three major uses of land in terms of their share, i.e., arable land, meadows, and pastures. The overall value of the area of land (Wcag) was determined using three factors, i.e., total area of the village (ha), share of the respective type of land (separately for arable land, meadows, and pastures) in the overall area of the village (%), and the mean score for the respective type of land (pts.).…”

“…Those studies resulted in determining the production value of arable land and grassland according to soil-quality classes using a 100-point scale (Table 1). The methods of research comprised calculations for three factors, i.e., overall area of the village in hectares; percentage share (in relation to the overall area of the village) of arable land, meadows, and pastures and the mean score for the respective types of land; Studies carried out in this area [31,32] allowed the authors to collect study material in the form of data from a real property register referring to types and classes of three major uses of land in terms of their share, i.e., arable land, meadows, and pastures. The overall value of the area of land (Wcag) was determined using three factors, i.e., total area of the village (ha), share of the respective type of land (separately for arable land, meadows, and pastures) in the overall area of the village (%), and the mean score for the respective type of land (pts.).…”

“…The whole computational algorithm provided for clustering separately for arable land, meadows, pastures, and collectively for all agricultural land (arable land, meadows, pastures). Village clustering used the previously tested Ward's method [31,32] and the distance matrix was squared as Euclidean distances. It should be mentioned that Ward's method provided very good clustering results that in previous studies [31] were controlled using a different clustering method-the complete-linkage method-leading to 80% concurrence of the results.…”

“…The method employed in identifying useless agricultural land [31] proved satisfactory in terms of evaluating the actual level of defectiveness of land in the study area. High consistency between the results of each group of selected statistical methods guarantees the right decisions in the development strategy for the specific area.…”

“…In previous studies, among other authors, Wójcik-Le ń [31] designed a two-stage computational algorithm calculating-in the first place-a so-called land-quality measure of a specific village as a mean of the score for the class of land weighted by its percentage share in the surface area. Such a measure allowed a village to be placed in a hierarchy according to an adopted criterion.…”