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Showing 2 results for Moshtagh

N. Moshtagh, R. Jafari, S. Soltani , N. Ramezani,
Volume 19, Issue 73 (fall 2015)
Abstract

Spatial estimation of evapotranspiration (ET) rates is essential for agriculture and water resources management. This study aimed to estimate ET v an ET estimation algorithm called Surface Energy Balance Algorithms for Land (SEBAL) and also by using TM June 2009 satellite data in Damaneh region of Isfahan province. To calculate the ET, all the energy balance components and related parameters including net radiation, surface albedo, incoming and emitting shortwave and longwave radiation, surface emissivity, soil heat flux, sensible heat flux, NDVI vegetation index, Leaf Area Index(LAI),  and surface temperature were extracted from the geometrically and radiometrically corrected TM images. Results showed that ET rate was about 7.2 mm day-1 in agricultural areas, which was almost equal to 6.99 mm day-1 extracted from the FAO Penman-Monteith method in the synoptic weather station of Daran. Results here indicate that the extraction of ET rate which is almost equal to plant water requirements from remote sensing data can be used in selecting appropriate plants for agriculture and rehabilitation purposes in extensive arid and semi-arid regions of Isfahan province where severe droughts and water shortage are major problems.


Alireza Salehi, Ayatollah Karami, Zahra Moshtagh, Vida Aliyari,
Volume 30, Issue 3 (Fall 2026)
Abstract

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


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