Integrated land planning approaches to sustainable olive cultivation and marginality contrast. Campania region case-study in Southern Italy

This repository contains figures and supporting data used in the analysis of spatial suitability and potential expansion areas for olive cultivation in the Campania region (Southern Italy). The materials accompany a study that integrates multiple spatial modelling approaches to identify environmentally suitable areas and evaluate opportunities for sustainable agricultural development. The research combines three complementary methodological frameworks: a deterministic GIS-based suitability model, a model-based species distribution approach using MaxEnt, and a probabilistic multi-criteria analysis based on Spatial Multi-Criteria Decision Analysis (S-MCDA). Together, these approaches enable the identification of territories that simultaneously exhibit favorable biophysical conditions, potential species distribution, and socio-economic characteristics associated with marginal agricultural land. The deterministic approach evaluates the physical suitability of the territory for olive cultivation by integrating environmental and geomorphological variables such as slope, soil characteristics, precipitation, and other pedoclimatic parameters. The model-based approach applies the MaxEnt species distribution model to estimate the potential distribution of Olea europaea L. based on environmental predictors. Model performance was evaluated using the ROC curve (AUC ≈ 0.8), while the relative contribution of environmental variables was assessed using the Jackknife test. The probabilistic approach uses a Spatial Multi-Criteria Decision Analysis framework to identify marginal lands that may represent opportunities for sustainable agricultural development. Twenty-five territorial factors were considered, including environmental, geomorphological, socio-economic, infrastructural, and ecosystem service indicators. In addition to modelling outputs, the repository includes a contingency matrix derived from the comparison between two land-use datasets (CORINE Land Cover 1990 and 2018). The matrix was produced using the Map Comparison Kit (MCK) and was used to evaluate land-use changes and persistence through the Kappa statistic, providing an assessment of spatial agreement between the two datasets and identifying transitions affecting olive-growing areas. Files included in this repository: • Deterministic Approach.jpg – spatial representation of the GIS-based physical suitability model for olive cultivation• Model-Based Approach.jpg – potential distribution map generated using the MaxEnt model• Probabilistic Approach.jpg – marginality-based suitability map derived from the S-MCDA framework• Probabilistic Approach_ALL FACTORS.jpg – representation of the factor layers used in the probabilistic model• REGION_ULIVI_MCK_Kappa.jpg – map output from the land-use comparison and Kappa analysis• LAND USE_KAPPA contingency matrix.xlsx – contingency matrix summarizing land-use transitions between CORINE Land Cover 1990 and 2018 used for Kappa statistic calculation This research was conducted as part of the study: 'Countering rural marginalization in the Mediterranean basin: a Multi-Dimensional Decision-Support framework for sustainable olive investments