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

Abstract

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.

Country and regional carbon stock in forest cover – estimates based on the first cycle of the Czech National Forest Inventory data (2001–2004)

“…between individual regions within one country (Andronache et al 2017). The variability in forest cover among countries and administrative regions results from different political settings, socioeconomic conditions, ownership structure and management practices in the past and present (Cvitanovic et al 2016, Andronache et al 2017. At a global level, Keenan et al (2015) revealed that forest cover increases with the increasing income of the region or the country, while Crespo Cuaresma et al (2017) revealed a U-shaped relationship between the income per capita and the forest cover of countries.…”

“…In general, large differences in forest cover as well as in hectare stock exist not only between individual countries but also at intracountry level, i.e. between individual regions within one country (Andronache et al 2017). The variability in forest cover among countries and administrative regions results from different political settings, socioeconomic conditions, ownership structure and management practices in the past and present (Cvitanovic et al 2016, Andronache et al 2017.…”

Using Multitemporal Landsat ETM+ Imagery to Determine a Sustainable Exploitation Patterns of the Forest Resources in the Moldo-Transylvanian Carpathians - Romania

“…In the analyses, we used images classified into forested areas (annually 2000-2014), for deforested areas (annually 2001-2014) and the reforested areas only a single synthetic image from 2001 to 2014 (a single image containing all the regeneration from 2001-2014) [37]. We have processed these TIFF encoded time series of Landsat images (Table 1) to extract deforested and reforested areas as described in more details in [34]. Subsequently, images were transformed into binary images using default binary function from ImageJ 1.51 software [38] and analyzed using a macro for calculating the area and the percentage of forest pixels ( Figure S1 in Supplementary Materials).…”

“…Because the shapes of forest areas are morphologically complex, fragmented, uneven and because standard descriptors depend on the scale of observation [32], we propose an invariant scale analysis as fractal analysis. The utility of fractal analysis in forest research was demonstrated previously by our research team [31,33,34]. Fractal analysis is a powerful tool both for describing irregular objects in nature because they cannot be defined by classical Euclidean geometry [35] and for measuring seemingly random or too complex patterns.…”

“…Fractal analysis is a powerful tool both for describing irregular objects in nature because they cannot be defined by classical Euclidean geometry [35] and for measuring seemingly random or too complex patterns. Previously studies by our research team [31,33,34] focused on the spatiotemporal dynamics of fragmentation and heterogeneity forests, by fractal analysis.…”