Modeling and Mapping Climate Risk for Olive Cultivation in Greece Using an AI-Assisted Geospatial Analysis System

Greek olive groves are subject to multiple thermal, water, biotic, and extreme-weather pressures, yet national-scale maps of their combined historical exposure remain limited. The present study quantified climate risk for olive cultivation across Greece using twenty agroclimatic indicators grouped into four thematic categories. Using hourly ERA5-Land data (1995–2024) and quality-controlled ESWD reports (2014–2024), each indicator recorded how often predefined adverse thresholds were met at the grid-cell level during the reference period. We integrated the resulting layers using a weighted multi-criteria decision analysis, with lethal frost applied as a separate constraint, to produce a composite spatial distribution of climate risk and district-level summaries linked to CORINE Land Cover 2018, olive grove class (2.2.3). Composite risk was spatially heterogeneous: cold and frost recurrence predominated in northern and upland areas, whereas water-related indicators occurred most persistently in southern and island districts, including eastern Crete. Most of the mapped olive grove area fell into intermediate composite classes rather than at the extremes of the score range. Comparison with a recent nationwide olive suitability assessment showed agreement in major western and southern producing districts, but also contrasting patterns where high suitability coincided with elevated recurrence-based risk. The resulting products provide a national historical baseline for climate-risk recurrence in Greek olive groves, offer a spatial basis for regionally targeted adaptation planning, and demonstrate the applicability of an AI-assisted geospatial framework for reproducible national-scale climate-risk assessment of perennial crops.