Spatial indicators to evaluate urban fragmentation in basilicata region

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Abstract

The increase of artificial land use represents a relevant indicator in land management policies and practices. It is a useful tool in assessing the quality of settlement processes and the protection and enhancement policies in rural and natural areas. Over time land take processes have been caused by different phenomena: urban or industrial expansion, realization of infrastructures, the development or the productive exploitation of territorial areas characterized by the presence of specific resources (natural, mining, etc.). This phenomenon is no longer a direct consequence of a real need of new expansion areas throughout Italian national territory. In the past the phenomenon was mainly due to residential, productive or tertiary sector needs, and it was generated by demographic growth and the consequent urbanization process. In the last two decades land take is more and more related to a weak territorial governance, generally linked to an inefficiency of urban and territorial planning instruments and sometimes of speculative real estate initiatives. In this paper a spatial analysis procedure oriented to calculate indicators of urban fragmentation for Basilicata Region has been presented. Such indicators could drive to the identification of two phenomena: urban-sprawl and urban-sprinkling according to the literature classification proposed in several researches by Romano et al. The results represent a useful contribution in order to improve regional normative system concerning urban development. The research is part of a wider project on environmental and territorial indicators (INDICARE) promoted by FARBAS (Environmental Observatory Foundation of Basilicata Region) in collaboration with the University of Basilicata.

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Saganeiti, L., Pilogallo, A., Scorza, F., Mussuto, G., & Murgante, B. (2018). Spatial indicators to evaluate urban fragmentation in basilicata region. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10964 LNCS, pp. 100–112). Springer Verlag. https://doi.org/10.1007/978-3-319-95174-4_8

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