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An integrated approach land suitability for agroecological zoning based on fuzzy inference system and GIS

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Abstract

Land suitability assessment is integral to land planning and development. One of the crucial ways to know the different capabilities of lands is to use agroecological zoning. The result of this type of land zoning is quantitative and qualitative increases in crop yields due to climate, soil, and topographic adaptations. This study aimed to create agroecological zoning maps for irrigated and rain-fed chickpea cultivation in semiarid regions in the Khorasan provinces, Iran. Data was prepared in a geographic information system (GIS) environment and using a membership function defined in a fuzzy inference system. Then, by weighted linear combination method, the standardized layers were combined with their weight in GIS environment to reach the final maps. The results illustrated that the precipitation factor had the highest weight (0.9) for rain-fed chickpea farming. For irrigated chickpea cultivation, slope and soil capability had the highest weight (0.9). The agroecological zoning maps indicated that 154,625 ha (0.7%) and 178,412 ha (2.9%) of the study area were the most suitable lands, respectively, for rain-fed and irrigated chickpea cultivation. 9.5% (2,265,128 ha) and 9% (2,168,314 ha), 31% (7,398,457 ha) and 19.1% (4,565,217 ha), and 58.8% (14,010,097 ha) and 71% (16,916,364 ha) of the study area were moderately suitable, marginally suitable, and unsuitable for rain-fed and irrigated chickpea cultivation, respectively. The results also illustrated that climatic zoning and topographic zoning have a critical role in determining the suitable areas for chickpea production under rain-fed and irrigated conditions.

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Acknowledgements

The authors are grateful toward those who have contributed to and collaborated on the current research by providing commentary or some of the original research inputs. This research was funded by Ferdowsi University of Mashhad and by number 51095.

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  1. Jafar Nabati and Ehsan Neamatollahi have contributed equally to this work

Authors and Affiliations

  1. Legume Department, Research Center for Plant Sciences, Ferdowsi University of Mashhad, Mashhad, Iran

    Jafar Nabati & Ehsan Neamatollahi

  2. Department of Agronomy and Plant Breeding, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

    Ahmad Nezami

  3. Department of Desert Area Management, Faculty of Natural Resources and Environment, Ferdowsi University of Mashhad, Mashhad, Iran

    Morteza Akbari

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  1. Jafar Nabati
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Nabati, J., Nezami, A., Neamatollahi, E. et al. An integrated approach land suitability for agroecological zoning based on fuzzy inference system and GIS. Environ Dev Sustain 25, 2316–2338 (2023). https://doi.org/10.1007/s10668-022-02127-7

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