Scientific Association of Waste Management Human Ecology 3041-9255 4 13 2026 01 21 Ecological Zoning of Southern Khorasan lands for Ferula assafoetida production using geographical Information system (Case study:Nehbandan) Ecological Zoning of Southern Khorasan lands for Ferula assafoetida production using geographical Information system (Case study:Nehbandan) 1805 1822 236275 10.22034/he.2025.551761.1160 FA Gholamreza Doraki Department of Plant Production and Genetics, Faculty of Agriculture, University of Birjand, Birjand, Iran. 0009-0000-7728-6754 Mohammad Ali Behdani Department of Plant Production and Genetics, Faculty of Agriculture, University of Birjand, Birjand, Iran. 0000-0001-6182-700X Morteza Esmaelnejad Department of Geography, Faculty of Literature and Humanities, University of Birjand, Birjand ,Iran. 0000-0001-5398-4267 Mohammad Hassan Sayyari Zahan Department of Plant Production and Genetics, Faculty of Agriculture, University of Birjand, Birjand, Iran. 0000-0001-7417-2049 Journal Article Ferula assa-foetida L. is a key medicinal-industrial species in Iran, and its cultivation development can simultaneously help protect natural habitats, provide local employment, and reduce raw sales. This study aimed to assess the ecological suitability of the location for the establishment and development of Ferula assa-foetida in Nehbandan County and provide an "action plan" for executive decision-making. Materials and Methods: Topographic data from DEM with a resolution of 30 meters, 15-year climate (precipitation, temperature, and humidity), and topsoil data (0–30 cm: texture, pH, EC, organic matter, nitrogen, phosphorus, potassium, lime, gypsum, and saturated moisture) were collected and assimilated to a 30-meter grid. Layer normalization was performed with appropriate fuzzy functions (fuzzy large/small/medium/optimum). The criteria were weighted using the AHP based on the judgments of 15 experts, and the results were analyzed in Expert Choice software (CR=0.05<0.1). The final overlap was obtained using the gamma operator in ArcGIS Pro 3.4 (γ = 0.8) and the Jenks classification. “Rainfall” with a relative weight of 0.219 was the most effective factor, followed by “altitude” (0.146) and “temperature/LST” (0.120). The soil texture package had an intermediate share (sand 0.073, silt 0.040, clay 0.022), and the modifier indices, including saturated moisture (0.066) and slope direction (0.061), moderated the classes. In soil chemistry, pH (0.059) and salinity (EC=0.045) identified local limiting factors; the nutrients nitrogen (0.034), potassium (0.019), and phosphorus (0.010), as well as lime (0.011) and gypsum (0.007), played a secondary and manageable role. The final map showed “very suitable/suitable” cores mainly in the northern foothill belts and central-eastern outcrops; in contrast, the southern and southwestern plains were assigned to the “moderate to poor” classes due to low rainfall, high LST, and, in some places, ultra-sandy/salinity textures. The spatial skeleton of the suitability of Anghozeh in Nehbandan is built with the three pillars of “precipitation-altitude-temperature” and is trimmed with “texture-soil chemistry-slope direction”. Accordingly, it is recommended to focus investment and promotion on the "very suitable/suitable" islands of the north and east, and to improve border areas with targeted interventions commensurate with the "limiting factor" (reducing salinity/alkalinity, optimizing soil texture and moisture, selecting sunny directions). In addition to reducing pressure on harvesting from natural habitats, this study's output provides a basis for locating processing rings and reducing raw sales, and offers a generalizable model for provinces with the same climate. Ferula assa-foetida L. is a key medicinal-industrial species in Iran, and its cultivation development can simultaneously help protect natural habitats, provide local employment, and reduce raw sales. This study aimed to assess the ecological suitability of the location for the establishment and development of Ferula assa-foetida in Nehbandan County and provide an "action plan" for executive decision-making. Materials and Methods: Topographic data from DEM with a resolution of 30 meters, 15-year climate (precipitation, temperature, and humidity), and topsoil data (0–30 cm: texture, pH, EC, organic matter, nitrogen, phosphorus, potassium, lime, gypsum, and saturated moisture) were collected and assimilated to a 30-meter grid. Layer normalization was performed with appropriate fuzzy functions (fuzzy large/small/medium/optimum). The criteria were weighted using the AHP based on the judgments of 15 experts, and the results were analyzed in Expert Choice software (CR=0.05<0.1). The final overlap was obtained using the gamma operator in ArcGIS Pro 3.4 (γ = 0.8) and the Jenks classification. “Rainfall” with a relative weight of 0.219 was the most effective factor, followed by “altitude” (0.146) and “temperature/LST” (0.120). The soil texture package had an intermediate share (sand 0.073, silt 0.040, clay 0.022), and the modifier indices, including saturated moisture (0.066) and slope direction (0.061), moderated the classes. In soil chemistry, pH (0.059) and salinity (EC=0.045) identified local limiting factors; the nutrients nitrogen (0.034), potassium (0.019), and phosphorus (0.010), as well as lime (0.011) and gypsum (0.007), played a secondary and manageable role. The final map showed “very suitable/suitable” cores mainly in the northern foothill belts and central-eastern outcrops; in contrast, the southern and southwestern plains were assigned to the “moderate to poor” classes due to low rainfall, high LST, and, in some places, ultra-sandy/salinity textures. The spatial skeleton of the suitability of Anghozeh in Nehbandan is built with the three pillars of “precipitation-altitude-temperature” and is trimmed with “texture-soil chemistry-slope direction”. Accordingly, it is recommended to focus investment and promotion on the "very suitable/suitable" islands of the north and east, and to improve border areas with targeted interventions commensurate with the "limiting factor" (reducing salinity/alkalinity, optimizing soil texture and moisture, selecting sunny directions). In addition to reducing pressure on harvesting from natural habitats, this study's output provides a basis for locating processing rings and reducing raw sales, and offers a generalizable model for provinces with the same climate. https://www.landscapeecologyjournals.ir/article_236275_103d53d9071cd9d744299b5b489ea5e3.pdf