SUITABILITY MAPS FOR PINOT NOIR - Based on the use of Geographic Information and Environmental Data in the Oltrepò Pavese Region

Viticulture represents one of the oldest agricultural practices and is closely linked to the environmental characteristics of the territory where vines are cultivated. Vine growth and grape quality are strongly influenced by a combination of climatic, topographic, and soil-related factors, including temperature, solar radiation, water availability, and soil properties. For sensitive grape varieties such as Pinot Noir, achieving optimal grape composition requires a careful balance among these factors, while inadequate conditions can negatively affect grape yield and wine quality. In the context of climate change, traditional viticultural areas are undergoing significant transformations, with shifts in temperature and rainfall patterns altering vineyard suitability. This has increased the need for spatially explicit, data-driven tools to support sustainable vineyard planning and adaptation strategies at the local scale. Geographic Information Systems (GIS), combined with advanced modelling techniques, provide an effective means of integrating heterogeneous environmental data and assessing viticultural suitability at high spatial resolution. The aim of this research is to produce high-resolution viticultural suitability maps for Pinot Noir in the Oltrepò Pavese area (Lombardy, Italy). The study involved the collection and processing of environmental data layers, with particular attention to thermal conditions through the computation of the Winkler Index. Vineyard suitability was subsequently assessed using two modelling techniques: (i) a GIS-based Multi-Criteria Decision Analysis (MCDA), and (ii) a Fuzzy Logic model implemented in MATLAB. Both approaches used the same set of topographic, pedological, climatic, and land-use criteria to identify areas classified as highly suitable, moderately suitable, marginally suitable, or unsuitable for Pinot Noir cultivation. The comparison between the GIS-MCDA and Fuzzy Logic outputs revealed both areas of agreement and disagreement in the resulting suitability patterns. The suitability maps were further compared with the spatial distribution of existing vineyards, obtained from available reference data, to assess the consistency of the model outputs with established viticultural practices. Overall, this research demonstrates the effectiveness of integrating GIS-based MCDA and Fuzzy Logic modelling for vineyard suitability assessment. The proposed methodology provides a valuable decision-support tool for land-use planning, precision viticulture, and sustainable vineyard management. It offers a reproducible framework that can be adapted to other grape varieties and regions facing climate-related challenges.