JWSS - Journal of Water and Soil Science

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Salehi A, Karami A, Moshtagh Z, Aliyari V. Site Selection and Land Capability Evaluation for Pistachio Cultivation Development in Sistan and Baluchestan Province Using GIS and AHP. J Water Soil Sci. 2026; 30 (3) :159-178
URL: http://jstnar.iut.ac.ir/article-1-4564-en.html

This research was conducted with the aim of site selection and land capability evaluation for the development of pistachio cultivation in Sistan and Baluchestan province by integrating Geographic Information Systems (GIS), the Analytical Hierarchy Process (AHP), and remote sensing data (Landsat 8 satellite imagery within the Google Earth Engine platform). Eight criteria, including distance from water canals, roads, and population centers, land use, slope, elevation, slope aspect, and soil characteristics (salinity, texture, and pH), were weighted based on the opinions of 15 experts (inconsistency ratio = 0.03). The highest weights were assigned to distance from water canals (0.32), soil characteristics (0.25), and distance from roads (0.14). Information layers with a spatial resolution of 30 m were prepared in the GIS environment and integrated using the weighted overlay method. The final map showed that 13.8 percent of the province is in the highly suitable class, 23.0 percent in the moderately suitable class, 33.5 percent in the marginally suitable class, 27.5 percent in the unsuitable class, and 2.2 percent has absolute limitations. The findings indicated that 36.8 percent of the province has significant potential for the development of pistachio cultivation; however, the main limitation is access to water resources. 65.5 percent of the province is located in the unsuitable category in terms of distance from water canals. Therefore, the sustainable development of pistachio cultivation in the province requires precise planning with a focus on suitable areas and the sustainable management of water resources. The novelty of this research lies in applying Boolean masks to eliminate ecological errors and using cloud computing (GEE) for the temporal consistency of data. Furthermore, comparative analysis revealed that crop development in some areas (such as Zahedan) relies more on groundwater extraction than on inherent land potential; the model classifies these areas as "unsuitable," providing a preventive warning regarding long-term sustainability