Dynamics of Forest Fragmentation and Connectivity Using Particle and Fractal Analysis

Ion Andronache, Marian Marin, Rico Fischer, Helmut Ahammer, Marko Radulovic, Ana Maria Ciobotaru, Herbert F. Jelinek, Antonio Di Ieva, Radu Daniel Pintilii, Cristian Constantin Drăghici, Grigore Vasile Herman, Alexandru Sabin Nicula, Adrian Gabriel Simion, Ioan Vlad Loghin, Daniel Constantin Diaconu, Daniel Peptenatu

Research output: Contribution to journalArticlepeer-review

42 Scopus citations


The ever decreasing area of forests has lead to environmental and economical challenges and has brought with it a renewed interest in developing methodologies that quantify the extent of deforestation and reforestation. In this study we analyzed the deforested areas of the Apuseni Mountains, which has been under economic pressure in recent years and resulted in widespread deforestation as a means of income. Deforested surface dynamics modeling was based on images contained in the Global Forest Database, provided by the Department of Geographical Sciences at Maryland University between 2000 and 2014. The results of the image particle analysis and modelling were based on Total Area (ha), Count of patches and Average Size whereas deforested area distribution was based on the Local Connected Fractal Dimension, Fractal Fragmentation Index and Tug-of-War Lacunarity as indicators of forest fragmentation or heterogeneity. The major findings of the study indicated a reduction of the tree cover area by 3.8%, an increase in fragmentation of 17.7% and an increase in heterogeneity by 29%, while fractal connectivity decreased only by 0.1%. The fractal and particle analysis showed a clustering of forest loss areas with an average increase from 1.1 to 3.0 ha per loss site per year. In conclusion, the fractal and particle analysis provide a relevant methodological framework to further our understanding of the spatial effects of economic pressure on forestry.

Original languageBritish English
Article number12228
JournalScientific Reports
Issue number1
StatePublished - 1 Dec 2019


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