Abstract
All programs and policies that stimulated and continue to promote the construction of renewable energy production plants, pose a growing challenge to regional planners and administrators: how to manage the transformation of the landscape to find an effective sustainable arrangement for renewable energy technologies? In fact, while RES plants contribute to solve the global problem of climate change and to reduce emissions, at the local level they imply significant impacts on several components such as: land use, land take, diminishing aesthetic values, deterioration of habitat quality. The intensity of these effects depends on the location of the plants, the distance between the plants, the extension of the ancillary infrastructures and the technical characteristics. It is questionable whether the intensity of the negative impacts at the local level is more related to the technical characteristics of each installations or their dislocation on the territory. The present work is part of this debate, discussing fragmentation index resulted from the assessment of the current regional settlement structure of RES plants.
In facts, the case study concerns the territory of Basilicata region (Italy), which over the last years has seen an abundant increase in installation of renewable energy plants. The evolution of the regional energy system has been strongly influenced both by incentive policies and by (weak) urban and territorial planning policies. This approach could be a valuable contribution both in identifying a fragmentation threshold beyond which the expected negative impacts outweigh the benefits, and in providing useful procedure for managing future installations.
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Acknowledgements
This research has been developed within the MEVCSU and INDICARE projects supported by the Environmental Observatory Foundation of Basilicata Region (FARBAS).
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Saganeiti, L., Pilogallo, A., Faruolo, G., Scorza, F., Murgante, B. (2019). Energy Landscape Fragmentation: Basilicata Region (Italy) Study Case. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11621. Springer, Cham. https://doi.org/10.1007/978-3-030-24302-9_50
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