Climate change is considered one of the main potential causes for socio-economic damages in viticulture in the future. The analysis of such systems has to be carried out adopting a methodology able to link different spatial and temporal variables, as well as evaluating the uncertainty related to climatic scenario. Thus, the Fuzzy Cognitive Map (FCM) approach was adopted to analyse potential viticulture trends under climate alteration in the Tuscany region (Italy). Best allocation of policy resources and incentives for mitigation of socio-economic impacts were tested through the application of nonlinear programming (NLP). Best policy scenario were depicted applying a multicriteria approach. Results highlighted the importance of regulation measures and the maintenance of quality brand.

Mitigation of socio-economic damage due to climate change: a fuzzy cognitive map optimisation for the Tuscan viticulture sector / Sacchelli, S; Alampi Sottini, V.. - In: AESTIMUM. - ISSN 1724-2118. - ELETTRONICO. - Proceedings:(2016), pp. 117-133. [10.13128/Aestimum-17888]

Mitigation of socio-economic damage due to climate change: a fuzzy cognitive map optimisation for the Tuscan viticulture sector

SACCHELLI, SANDRO
;
ALAMPI SOTTINI, VERONICA
2016

Abstract

Climate change is considered one of the main potential causes for socio-economic damages in viticulture in the future. The analysis of such systems has to be carried out adopting a methodology able to link different spatial and temporal variables, as well as evaluating the uncertainty related to climatic scenario. Thus, the Fuzzy Cognitive Map (FCM) approach was adopted to analyse potential viticulture trends under climate alteration in the Tuscany region (Italy). Best allocation of policy resources and incentives for mitigation of socio-economic impacts were tested through the application of nonlinear programming (NLP). Best policy scenario were depicted applying a multicriteria approach. Results highlighted the importance of regulation measures and the maintenance of quality brand.
2016
Proceedings
117
133
Sacchelli, S; Alampi Sottini, V.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1055677
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