GIS-Based Approach for Modeling Vineyard and Apple Orchard Suitability in Mountainous Regions
Armand Casadó-Tortosa, 
Felicidad  de Herralde (), 
Robert Savé, 
Miquel Peris, 
Jaume Lordan, 
Antoni Sánchez-Ortiz, 
Elisenda Sánchez-Costa, 
Adrià Barbeta and 
Inmaculada Funes
Additional contact information 
Armand Casadó-Tortosa: Institute of Agrifood Research and Technology (IRTA), Torre Marimon, 08140 Caldes de Montbui, Spain
Felicidad  de Herralde: Institute of Agrifood Research and Technology (IRTA), Torre Marimon, 08140 Caldes de Montbui, Spain
Robert Savé: Institute of Agrifood Research and Technology (IRTA), Torre Marimon, 08140 Caldes de Montbui, Spain
Miquel Peris: Institute of Agrifood Research and Technology (IRTA), Torre Marimon, 08140 Caldes de Montbui, Spain
Jaume Lordan: Institute of Agrifood Research and Technology (IRTA), Torre Marimon, 08140 Caldes de Montbui, Spain
Antoni Sánchez-Ortiz: Faculty of Oenology, Rovira i Virgili University, Campus Sescelades, Marcel·lí Domingo, w/o No., 43007 Tarragona, Spain
Elisenda Sánchez-Costa: Institute of Agrifood Research and Technology (IRTA), Torre Marimon, 08140 Caldes de Montbui, Spain
Adrià Barbeta: Institute of Agrifood Research and Technology (IRTA), Torre Marimon, 08140 Caldes de Montbui, Spain
Inmaculada Funes: Institute of Agrifood Research and Technology (IRTA), Torre Marimon, 08140 Caldes de Montbui, Spain
Land, 2025, vol. 14, issue 11, 1-26
Abstract:
Climate change is expected to negatively impact agricultural production, leading to phenological and metabolic changes, increased water demands, diminished yields, and changed organoleptic characteristics, restricting the positive geographic productivity potential. As an adaptive strategy, agriculture in mountainous regions has gained prominence despite the fact that it entails new challenges. Indeed, mountain-specific conditions and limitations need to be considered, compared to the traditional productive regions. Consequently, there is a lack of information about the most suitable locations because the new conditions and limitations need to be accounted for. This study provides a crop suitability assessment approach to be used in mountainous regions where data about crop yield or development is scarce or nonexistent. Specifically, we evaluated the suitability of vineyards and apple orchards in the southern Pyrenees and Pre-Pyrenees. Using Geographical Information System (GIS) techniques, integrated with fuzzy logic and the Analytic Hierarchy Process (AHP), we combined traditional climatic, soil, and topographic indicators with factors relevant to mountainous regions. Our results indicated that the most suitable areas were primarily in lower basins and sunny hillsides, with smaller water needs. Vineyards would benefit from a very low risk of late spring frosts and elevated solar radiation, whereas apple orchards from a reduced risk of hailstorms, a very low risk of late spring frosts, and mild slopes. The fuzzy membership functions combined with the AHP facilitated the integration of indicators, effectively identifying areas with high potential for crop development. This approach contributes to landscape management and planning by offering a modifiable tool for assessing crop suitability in mountainous regions.
Keywords: GIS; fuzzy logic; AHP; mountainous regions; vineyard; apple orchard; crop suitability (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52  (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc 
Citations: 
Downloads: (external link)
https://www.mdpi.com/2073-445X/14/11/2135/pdf (application/pdf)
https://www.mdpi.com/2073-445X/14/11/2135/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX 
RIS (EndNote, ProCite, RefMan) 
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:14:y:2025:i:11:p:2135-:d:1780255
Access Statistics for this article
Land is currently edited by Ms. Carol Ma
More articles in Land  from  MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().