As the share of urban population increases globally each year, man-dominated systems tend to sprawl over the natural ones, substituting and fragmenting them. Urban sprawl is the main cause of many environmental issues, in tight connection with pollution and loss of biodiversity. One of the main consequences is a decrease of the ecosystem services provided by the urban green infrastructure. However, the extent of urban sprawl is spatially uneven due to the spatial structure of human settlements. Among the methods used to pinpoint sprawl, fractal analyses have a good potential for analyzing fragmentation, especially if used in conjunction with statistical methods. This study aimed to assess, in an exploratory perspective, the level of fragmentation in the Romanian cities covered by the Urban Atlas data, and determine its correlation with parameters related to their demographical and physical characteristics. In addition, taxonomical analyses were used to find whether cities or specific components of the green infrastructure can be grouped. The results did not reveal a general trend, although it seems that the green infrastructure consisted of agricultural/ semi-natural/ wetland areas, forests, green areas, sports and leisure facilities and water bodies in all of them, in different shares; with respect to their distribution, the numerical taxonomy analysis indicated that they form classes matching the types of ‘nature in the city’ previously described by ecologists, despite the particular historical evolution of each city and its particular influence on urban planning. The correlation analysis revealed that the population and its density and the share of the green infrastructure within the total area are significantly correlated with most fractal parameters. Similarly, the fractal dimension of the area, computed using Interactive Quantitative Morphology, seems to correlate with most morphological parameters. However, the taxonomical analysis of cities did not find very relevant groups due to the fact that many large Romanian cities lack Urban Atlas data. The results suggest that the degree of urban fragmentation is correlated especially with the population of cities and its density, reclaiming planning measures aimed at controlling the densification processes (sprawl, gentrification, location of specific activities etc.

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 Maramureș 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 Maramureș County.

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 CO₂, 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.

The study aims to develop a methodology for analyzing the trend of concentration of economic activities in the main core of national polycentric network A spatial projection has been realized in ArcGIS platform, for the period 2000-2012, containing the number of companies, number of employees, turnover and profit The original images were converted to images created 8-bit grayscale (using open-source software ImageJ) are then analyzed by Higuchi 1D Fractal Dimension algorithm using open-source software IQM Higuchi fractal dimension provided us very useful information about more or less chaotic disposed in space by the number of companies, the profit, the number of employees and the turnover From data analysis we observed a increase of Higuchi dimension with the growing economic influence of the main centers of development for all the four parameters We observed that Higuchi analysis could help in identifying of the increasing of the influence of the main centers on the neighbouring territories, in periods of economic development, or decreasing of influence in the periods of the economic crises For testing and confirmation of the veracity of Higuchi analysis the results obtained were confirmed by gray box-counting analysis using Fractal Analysis System and Fraclac/ImageJ Hence, the Higuchi's fractal dimension is a very good, fast and versatile method for modeling evolution of concentration trends in the national economy

The water quality of Rudrasagar Lake, the second-largest natural reservoir of Tripura is of great ecological and economic importance as it serves a diverse range of purposes, including fishing, irrigation, aquaculture, domestic use, and recreation activities. This study investigates the water quality of the study area, an esteemed Ramsar site in North Eastern India, using a combined application of multivariable statistical and geospatial techniques. In this study, 24 water samples were designed based on their use and collected along the periphery and the inner areas of the lake employing the Latin Square Matrix. This research also examines the spatial variations of water quality involving quartile-based water quality categorization of parameters, with Pearson’s Correlation analysis, Principal Component Analysis (PCA), and Hierarchy Cluster Analysis (HCA) applied for dimension reduction. The analysis involved quartile-based water quality categorization of parameters, with PCA and HCA applied for dimension reduction. Meanwhile, the Inverse distance weighted (IDW) approach was used to interpolate the spatial distribution of the quartile score using the ArcGIS platform. The Bureau of Indian Standards (BIS) was followed for water quality assessment. The results revealed significant spatial variation, providing valuable insights for future water management strategies. PCA indicates 57.26% of the variance in the dataset, whereas samples were classified into three subgroups and two groups in a dendrogram representing the result of the HCA. This study demonstrates the utility of PCA, HCA, and IDW interpolation in water quality assessment, highlighting the effect of human-induced activities in the lake’s vicinity.