Geospatial and common methods for the assessment of land suitability for wheat production in Iran

Wheat is considered the most important crop in Iran; however, not all of the land in Iran is equally suitable for growing wheat. This study aimed to apply a spatial model for land suitability assessment integrated with geographic information system (GIS) techniques for the wheat crop. Climate and Soil parameters were recognized as factors affecting land suitability for wheat crop in the study area. Three indices were used in assessing land suitability, soil fertility, chemical and physical quality indices. The results of the proposed model (LSI) were compared with the square root and Storie methods. The results showed that most of the units fall within the Moderate suitable class (S2) and the Marginally suitable class (S3) which together represent 88.66% of the total area. About 7.08% of the study area was High suitable and About 2.37% of the study area was unsuitable for wheat crops and those areas correspond to the adverse physical and chemical properties of the soil. The comparison of the results of the three approaches used showed that the present model has a Moderate level of agreement with the square root method (0.516) and showed that the present model has a low level of agreement with the Storie method (0.243). Comparing the results showed that the story model has a high agreement with the square root method (0.884). In the current model, the use of different indicators allows for obtaining results that seem to be more consistent with the current conditions of the region.

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Publication Details

Journal
Ecological Questions
Published
2024-08-20
DOI
https://doi.org/10.12775/eq.2024.052
Primary Topic
Soil and Land Suitability Analysis
Type
article
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article

Geospatial and common methods for the assessment of land suitability for wheat production in Iran

Lingxiao Sun, Jing He, Mahmood Rostaminia, Behnam Asghari Beirami et al.
Ecological Questions
Soil and Land Suitability Analysis
article

Geospatial and common methods for the assessment of land suitability for wheat production in Iran

Lingxiao Sun, Jing He, Mahmood Rostaminia, Behnam Asghari Beirami, Chunlan Li, Hamid Reza Matinfar, Seyed Omid Reza Shobairi, Qirghizbek Ayombekov, Hai-Yan Zhang, Maria Kohani
article en

Abstract

Wheat is considered the most important crop in Iran; however, not all of the land in Iran is equally suitable for growing wheat. This study aimed to apply a spatial model for land suitability assessment integrated with geographic information system (GIS) techniques for the wheat crop. Climate and Soil parameters were recognized as factors affecting land suitability for wheat crop in the study area. Three indices were used in assessing land suitability, soil fertility, chemical and physical quality indices. The results of the proposed model (LSI) were compared with the square root and Storie methods. The results showed that most of the units fall within the Moderate suitable class (S2) and the Marginally suitable class (S3) which together represent 88.66% of the total area. About 7.08% of the study area was High suitable and About 2.37% of the study area was unsuitable for wheat crops and those areas correspond to the adverse physical and chemical properties of the soil. The comparison of the results of the three approaches used showed that the present model has a Moderate level of agreement with the square root method (0.516) and showed that the present model has a low level of agreement with the Storie method (0.243). Comparing the results showed that the story model has a high agreement with the square root method (0.884). In the current model, the use of different indicators allows for obtaining results that seem to be more consistent with the current conditions of the region.

Ecological QuestionsVol. 35(4)
Chinese Academy of Sciences (CN), Lorestan University (IR), Xinjiang Institute of Ecology and Geography (CN), Ilam University (IR), University of Chinese Academy of Sciences (CN), K. N. Toosi University of Technology (IR)
Openalex Percentile: Top 80%
Soil and Land Suitability Analysis
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