Clustering olive oil mills through a spatial and economic GIS-based approach

Abstract

Sicily ranks as the third-largest region in Italy for olive growing and olive oil production, holding the second position nationally regarding the number of active olive oil mills. This pioneering study integrates spatial and economic analyses to examine the geographical distribution of olive oil mills in Sicily and their relationship with the localization of olive groves. Using Local Indicators of Spatial Association (LISA), we conducted an advanced analysis of spatial patterns of olive oil mills, considering travel time on the road network. The adopted methodology addresses issues related to overestimation based on straight-line assumptions and the neglect of travel speed. Unlike traditional Euclidean distance approaches, our methodology provides a detailed understanding of the spatial relationships between olive oil mills and olive groves, revealing distinct patterns linked to elevation and proximity to olive groves. By linking profitability indicators with spatial clusters, we identify different thresholds of economic sustainability. Consequently, these findings contribute to a more comprehensive understanding of the olive oil industry, suggesting more environmentally sustainable practices. Policymakers, researchers, and industry stakeholders can leverage this knowledge to make informed decisions that foster the long-term sustainability of the olive oil sector.

Keywords

• Spatial pattern analysis of olive oil mills
• Olive oil mills service areas
• Local indicators of spatial association (LISA)
• Incremental spatial autocorrelation (ISA)
• Moran's I index and getis-ord local statistics
• Profitability