Some Geospatial Insights on Orange Grove Site Selection in a Portion of the Northern Citrus Belt of Mexico

Abstract

This study aimed to delineate the most suitable areas for sustainable citrus production by integrating multi-criteria decision analysis, time-series remote sensing, and principal component analysis in a portion of the northern citrus belt of Mexico, particularly in the Rioverde Valley. Fourteen specific factors were grouped into four main factors, i.e., topography, soil, climate, and proximity to water sources, to carry out a multi-criteria decision analysis for classifying production areas according to suitability levels. To explore the effect of precipitation on land suitability for citrus production, we analyzed the historical record of annual precipitation estimated by processing 20-year NDVI daily data. The multi-criteria model was run for every precipitation year. The final map of land suitability was obtained by using the first component after principal component analysis on annual land suitability maps. The results indicate that approximately 30% of the study area is suitable for growing orange groves, with specific areas designated as suitable based on both mean annual precipitation (MAP) and principal component analysis (PCA) criteria, resulting in 84,415.7 ha and 95,485.5 ha of suitable land, respectively. The study highlighted the importance of remotely sensed data-based time-series precipitation in predicting potential land suitability for growing orange groves in semiarid lands. Our results may support decision-making processes for the effective land management of orange groves in the Mexico’s Rioverde region.

Keywords

• geographic information systems
• land suitability mapping
• land use planning
• multi-criteria decision analysis
• MCD43A4