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Lookup NU author(s): Dr Francesco CarrerORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of Journal of Maps.This study applies a geographical-physical and statistical methodology to predict vineyard distribution in the Taurasi DOCG terroir, southern Italy. Integrating morpho-topographical, climatic, and pedological data through GIS-based logistic regression, it aims to refine vineyard site selection—traditionally guided by local expertise—via scientifically validated predictive tools. The Taurasi territory, marked by pronounced lithological and topographic heterogeneity and a viticulture-favorable climate, serves as an ideal case study. The model was developed using environmental variables, optimized through stepwise selection and Variance Inflation Factor (VIF) analysis, and validated using the Receiver Operating Characteristic (ROC) curve. The resulting suitability map identifies areas most conducive to viticulture, emphasizing the importance of altitude, slope, aspect, and temperature in shaping vineyard potential. Despite sensitivity to environmental data quality, the approach demonstrates the value of integrating geospatial and statistical methods for informed spatial planning. The study reinforces the role of data-driven strategies in optimizing and sustainably managing viticultural landscapes.
Author(s): Cusano A, Carrer F, Russo F
Publication type: Article
Publication status: Published
Journal: Journal of Maps
Year: 2025
Volume: 21
Issue: 1
Online publication date: 31/07/2025
Acceptance date: 13/06/2025
Date deposited: 11/08/2025
ISSN (electronic): 1744-5647
Publisher: Taylor and Francis Ltd.
URL: https://doi.org/10.1080/17445647.2025.2525922
DOI: 10.1080/17445647.2025.2525922
Data Access Statement: The data that support the findings of this study are available from the corresponding author, Angelo Cusano (angcusa-no@unisannio.it), upon reasonable request. The map was created using QGIS 3.36.1, an open-source Geographic Information System licensed under the GNU General Public License. QGIS is an official project of the Open Source Geospatial Foun-dation (OSGeo) and is public domain software. Data related to physical geography parameters were pro-cessed using QGIS 3.36.1 and the open-source statistical analysis software R 4.4.0, also licensed under the GNU General Public License. (https://www.r-project.org/; https://posit.co/download/rstudio-desktop/)
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