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The creative industry is developing today as a global phenomenon. The creative economy has vast potential for development and is one of the sectors with the fastest growing global economy. Creativity becomes the engine of social and economic change, turning into a new source of competitive advantage, as it is about how content creates creativity and helps create jobs. The study aims to analyze the spatial dynamics of creative economies at the level of Bucharest-Ilfov Development Region. A database was created, at the level of the administrative-territorial unit, with 2 economic indicators -the number of employees and the turnover considered relevant for this study, according to the NACE classification (Classification of National Economy Activities) for the period 2000-2016 on the basis of which has been made distribution maps of the creative economies for the Bucharest-Ilfov Development Region. Also, in order to quantify spatial dynamics of turnover and number of employees, in the study were tested: Sholl analysis (which quantifies the dynamics of the branching phenomenon), Mass Dimension (which measures the degree of "centrality"), Entropy (showing the degree of disorder), Pyramid Dimension (which shows the degree of complexity of the turnover relationship and the number of employees), Higuchi 2D (which shows the degree of complexity of the turnover relationship and the number of employees), Kolmogorov Complexity (which shows the degree of complexity of the phenomenon analyzed), FFI (indicating the dynamics of fragmentation / compaction of wealth or poverty). The obtained results show the specificity of the development of creative economies in the emerging spaces structured by highly complex urban systems.

ContextDeforestation remains one of the most pressing threats to biodiversity. Characterizing the resulting forest loss and fragmentation efficiently from remotely sensed data therefore has strong practical implications. Data are often separately analyzed for spatial fragmentation and disorder, but no existing metric simultaneously quantifies the shapes and arrangement of fragments. ObjectivesWe present a Fractal Fragmentation and Disorder Index (FFDI), which advances a previously developed fractal index by merging it with the Rényi information dimension. The FFDI is designed to work across spatial scales, and efficiently reports the fragmentation of images and spatial disorder of those fragments. MethodsWe validate the FFDI with four sets of synthetic Hierarchically Structured Random Map (HRM) multiscale images, characterized by increasing fragmentation and disorder but decreasing average size over multiple scales. We then apply the FFDI to the Global Land Analysis & Discovery Global Forest Change database satellite imagery of forest cover for 10 distinct regions of the Romanian Carpathian Mountains from 2000-2014. ResultsThe FFDI outperformed the individual use of its two components in resolving spatial patterns of disorder and fragmentation among HRM classes. It offers a clear advantage when compared to the individual use of Fractal Fragmentation Index and the Rényi information dimension, and works in an application to real data.ConclusionsThis work improves on previous characterizations of landscape patterns. With the FFDI, scientists will be able to better monitor and understand forest fragmentation from satellite imagery. The FFDI will have broad applicability to biological fields where image analysis is used.