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GEODETSKI VESTNIK
of iterations is selected (we chose 100 iterations). The share of the unit surfaces that can switch classes in the iteration is set to the value that corresponds to the area of the smallest investigated SU in relation to the total area concerned (in the classification of Slovenian municipalities it was set to 0.015%). Thus we allow for the smallest changes to occur and additionally impose no restrictions on the classification procedure. 5 TESTING THE SELECTED METHODS ON THE CASE OF SLOVENIA SU classification was done using ENVI (Harris, 2017). The proposed method was used to classify 210 Slovenian municipalities from 2011. Along with the use of eight normalised indicators (Table 2), the SUs at the level of municipalities were classified into 12 groups (Figure 7), which allows for a more detailed spatial division of Slovenia and, if appropriate, allows for the later aggregation of groups when identifying the typology of homogeneous SU groups. The initial values of the selected indicators by municipalities (Table 2) were calculated based on the data about the number of inhabitants per municipality from the Statistical Office of the RS and the data by the Ministry of Agriculture, Forestry and Food (MKGP). Population density relates to the information about the number of inhabitants per municipality in 2012, the share of urban population was calculated as the share of the inhabitants with permanent residence inside urban areas, determined according to Eurostat’s methodology of the degree of urbanisation and based on the raster of population density in Slovenia in 2012. The shares of actual land use are calculated from the layer of actual land use of the Ministry of Agriculture, Forestry and Food from 2012.
Figure 7: The results of unsupervised classification of Slovenian municipalities according to eight selected indicators, Slovenia, 2012.
The results of classifying all 210 Slovenian municipalities into 12 groups are also captured in a table, which gives the characteristic values of the created groups. Due to the size of the entire table, this paper shows the characteristic group values for only two, rather than eight indicators selected (GP and D30). The groups are numbered randomly according to the classification procedure (Table 3). | 556 |
Miha Konjar, Alma Zavodnik Lamovšek, Dejan Grigillo | Uporaba nenadzorovane klasifikacije za določanje tipologije pretežne rabe prostora | Use of unsupervised classification for the determination of prevailing land use tYpology | 541-581 |