izvorni znanstveni rad
The management of forest resources is complicated due to the complete lack of maintenance and disorganization
of the land administration and survey that are decades old. Modern, unconventional monitoring systems are used
with the aim of improving the existing records systems and creating a clearer insight into the state of forest resources.
This study provides an example of the use of one such system, Sentinel-2. Using the R programming language,
the multispectral Sentinel-2 images were classified by the Random Forest classification algorithm. Following
the completion of the classifications, the accuracy of the classification was evaluated using the error matrix
and the Kappa value. An analysis of forest resources for one cadastral municipality was accomplished using classified
rasters and data from the Real Estate Cadastre Database. Based on the data analysis, major changes are visible
in terms of the abandonment of agricultural land and its conversion into a certain form of forest vegetation.
Furthermore, based on these data, the study demonstrates changes that can be monitored in shorter time intervals.
Sentinel-2 images can be used to determine forest expansion, based on the aforementioned analyses, resulting
in a clearer and better representation of existing forest resources that are unknown due to outdated and unreliable
land administration systems.
Sentinel-2, Real Estate Cadastre Database, Random Forest, forest
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