Fractal analysis for studying the evolution of forests

Andronache, Ion; Ahammer, Helmut; Jelinek, Herbert F.; Peptenatu, Daniel; Ciobotaru, Ana Maria; Drăghici, Cristian-Constantin; Pintilii, Radu-Daniel; Simion, Adrian-Gabriel; Teodorescu, Camelia

doi:10.1016/j.chaos.2016.06.013

Cited by 47 publications

(66 citation statements)

References 22 publications

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“…The box-counting method is generally used for the fractal analysis of the forested areas, to describe spatial patterns [26,34,40] and their dynamics in the deforestation process [27], or to describe root morphology [28]. Here we used fractal analyses to study the evolution of fragmentation related to the space occupied by forested areas and affected by deforestation, by means of the Fractal Fragmentation Index [34], using the Pyramid Dimension method, as well as the degree of heterogeneity and the dispersion of the deforested areas by Fixed Grid 2D Lacunarity [35]. In doing this, the Global Forest Change 2000-2014 database [29] was used, which is based on satellite remote sensing Landsat imagery.…”

Section: Discussionmentioning

confidence: 99%

“…The resulting binarized images were subject to fractal analysis using IQM 3.3 software [33]. The method used to determine the fractal dimension was the Fractal Fragmentation Index (to determine the fractal fragmentation of forest areas as a result of deforestation) [34] and Fixed Grid 2D Lacunarity (to determine how heterogeneous the area taken up by deforestation is) [35].…”

Section: Discussionmentioning

confidence: 99%

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Using Fractal Analysis in Modeling the Dynamics of Forest Areas and Economic Impact Assessment: Maramureș County, Romania, as a Case Study

Pintilii

Andronache

Diaconu

et al. 2017

Forests

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Abstract:This study uses fractal analysis to quantify the spatial changes of forest resources caused by an increase of deforested areas. The method introduced contributes to the evaluation of forest resources being under significant pressure from anthropogenic activities. The pressure on the forest resources has been analyzed for Maramures , County, one of the most deforested counties in Romania. In order to evaluate this, the deforested areas were calculated for the period of 2001-2014, by using the Global Forest Change 2000-2014 database. The Fractal Fragmentation Index (FFI) and Fixed Grid 2D Lacunarity (FG2DL) were used to quantify the degree of fragmentation and dispersion of the forested areas, and thereby the extent to which a forest area is affected by deforestation. The process of quantifying the pressure on forested areas included the creation of a database for the period of 2000-2014 containing economic activities (turnover) related to woody recourses, important indicators of forest exploitation. Taken together, the results obtained indicate a dramatic increase in deforested areas (over 19,122 ha in total for the period of analysis), in Maramures , County.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Using Fractal Analysis in Modeling the Dynamics of Forest Areas and Economic Impact Assessment: Maramureș County, Romania, as a Case Study

Pintilii

Andronache

Diaconu

et al. 2017

Forests

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“…The most intense deforestation has occurred in North-East and North-West Regions (deforestation rates of 4.8% and 3.9% respectively), followed by the Center Region (3.9%), South Region (2.5%), South-West Region (1.5%), West Region (1.4%), South-East Region (1.4%) and Bucharest-Ilfov Region (1.2%) [36].…”

Section: Study Areamentioning

confidence: 99%

“…This development is reflected by the economic changes during this period and is spawned by changes in legislation which encouraged deforestations [11,[36][37][38]. In a longer historical perspective, forest cover in Romania has been characterized by significant changes over the last 100 years, mostly due to socio-political factors that have had significant impact on the forest management [51].…”

Section: Forest Changes In Romaniamentioning

confidence: 99%

“…The fractal analysis provides a complementary approach to traditional per-pixel based assessment of deforestation and forest disturbance, by including a contextual dimension into the analysis. Fractal analysis in the form of the box-counting, pyramid dimension, Minkowski dimension, Tug-of-War dimension and Fractal Fragmentation Index (FFI) were recently used in the analysis of forests [36][37][38]. In this study, we used a different approach to fractal analysis in relation to textural differentiations of forest resources by analysis of the fractal object dilation effects on fragmentation and heterogeneity of the forest spatial evolution.…”

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confidence: 99%

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Assessment of Textural Differentiations in Forest Resources in Romania Using Fractal Analysis

Andronache

Fensholt

Ahammer

et al. 2017

Forests

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Deforestation and forest degradation have several negative effects on the environment including a loss of species habitats, disturbance of the water cycle and reduced ability to retain CO 2 , with consequences for global warming. We investigated the evolution of forest resources from development regions in Romania affected by both deforestation and reforestation using a non-Euclidean method based on fractal analysis. We calculated four fractal dimensions of forest areas: the fractal box-counting dimension of the forest areas, the fractal box-counting dimension of the dilated forest areas, the fractal dilation dimension and the box-counting dimension of the border of the dilated forest areas. Fractal analysis revealed morpho-structural and textural differentiations of forested, deforested and reforested areas in development regions with dominant mountain relief and high hills (more forested and compact organization) in comparison to the development regions dominated by plains or low hills (less forested, more fragmented with small and isolated clusters). Our analysis used the fractal analysis that has the advantage of analyzing the entire image, rather than studying local information, thereby enabling quantification of the uniformity, fragmentation, heterogeneity and homogeneity of forests.

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