Abstract
Biofuels could be a possible solution to promote agricultural development in rural areas by increasing farm income. Different studies suggest that all problems linked to large-scale biofuel production can be overcome by promoting small-scale production, particularly of rapeseed straight vegetable oil (SVO) used as self-supply agricultural biofuel, specially if the rapeseed is cultivated in crop rotation systems with minimum tillage practices. However, an ex-ante analysis would be very important to explore the feasibility of rapeseed production, via the evaluation of land use suitability.
As land planning issues are complex problems with multiple decision makers and criteria, we propose a spatial multi-criteria analysis model for supporting decision makers in the site selection process for winter rapeseed production. The methodology applied is the Ordered Weighted Averaging (OWA) extended by means of fuzzy linguistic quantifiers. The results have shown as the proposed methodology is more flexible compared to the other MCA methods, in particular for the possibility to make the choice in qualitative rather than quantitative terms, enabling the decision-maker to explore different decision strategies or scenarios, thus facilitating a better understanding of alternative land use suitability models.
This research was carried out in the framework of the project ‘Smart Basilicata’ (Contract n. 6386 – 3, 20 July 2016).
Smart Basilicata was approved by the Italian Ministry of Education, University and Research (Notice MIUR n.84/Ric 2012, PON 2007–2013 of 2 March 2012) and was funded with the Cohesion Fund 2007–2013 of the Basilicata Regional authority.
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Viccaro, M., Cozzi, M., Vastola, A., Romano, S. (2018). Promoting Small-Scale Biofuel Production: A Qualitative GIS-OWA Methodology for Land Suitability Analysis of Winter Rapeseed. In: Berbel, J., Bournaris, T., Manos, B., Matsatsinis, N., Viaggi, D. (eds) Multicriteria Analysis in Agriculture. Multiple Criteria Decision Making. Springer, Cham. https://doi.org/10.1007/978-3-319-76929-5_6
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