USING FRACTAL FRAGMENTATION AND COMPACTION INDEX IN ANALYSIS OF THE DEFORESTATION PROCESS IN BUCEGI MOUNTAINS GROUP, ROMANIA
Abstract
DOI: 10.26471/cjees/2019/014/092
In Romania, the spatial dynamics of the forests has fluctuated due to a complex of factors, an important role being given by economic pressure (yearly harvesting plan, pest control, forest fires, illegal cuts, etc.). The precise quantification of these actions on the tree cover area was addressed using new methods of analysis using fractal algorithms. The principle of their analysis consists in the imagistic discrimination of spaces with the same characteristics. Thus, a fractal method was used, to estimate geometrically, quantitatively, the tree cover loss areas in the period 2000-2014. It should be noted that the present study analyzes a natural forest area; therefore, the tree cover area is not compact or homogeneous in terms of tree distribution, of their size like height or crown surface. The researched area is part of the Romanian Carpathian mountain chain, which represents more than 50% of the total chain of the Carpathian Mountains. Within the analyzed area, during the mentioned period, an area of 2230.7 ha was loss, representing 2.9% of the tree cover area. The gain areas were only 1014.7 ha, that means about 1.32% of the tree cover areas. The method applied in the research of the phenomenon highlights the distribution and the size of the loss areas in this area of study. This makes a significant contribution in quantifying the dynamics of the fragmentation of the areas covered with forest vegetation, and offers the possibility of correlation with other quantitative parameters, in order to substantiate environmental policies, to reduce negative impacts: landslides, flood scale, training of debris, with economic repercussions and loss of life.
- forest
- deforestation
- fractal
- dimension
- economic
- pressure
- forest
- management
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© 2019 by the author(s). Licensee CJEES, Carpathian Association of Environment and Earth Sciences. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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