Soybean ( Glycine max ) Cropland Suitability Analysis in Subtropical Desert Climate through GIS-Based Multicriteria Analysis and Sentinel-2 Multispectral Imaging

Noman Ahmad, Fazila Younas, Hamaad Raza Ahmad, Muhammad Sarfraz, Muhammad Ashar Ayub, Muhammad Aamer Maqsood, Fahd Rasul, Muhammad Fahad Sardar (), Tariq Mehmood, Jamaan S. Ajarem, Saleh n. Maoda, Xiang Li and Zhaojie Cui ()
Additional contact information
Noman Ahmad: Institute of Soil and Environmental Sciences, University of Agriculture Faisalabad, Faisalabad 38040, Pakistan
Fazila Younas: School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China
Hamaad Raza Ahmad: Institute of Soil and Environmental Sciences, University of Agriculture Faisalabad, Faisalabad 38040, Pakistan
Muhammad Sarfraz: Soil Salinity Research Institute, Pindi Bhattian, Hafizabad 52180, Pakistan
Muhammad Ashar Ayub: Institute of Agro-Industry and Environment, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan
Muhammad Aamer Maqsood: Institute of Soil and Environmental Sciences, University of Agriculture Faisalabad, Faisalabad 38040, Pakistan
Fahd Rasul: Department of Agronomy, University of Agriculture Faisalabad, Faisalabad 38040, Pakistan
Muhammad Fahad Sardar: Key Laboratory of Ecological Prewarning, Protection and Restoration of Bohai Sea, Ministry of Natural Resources, School of Life Sciences, Shandong University, Qingdao 266237, China
Tariq Mehmood: Helmholtz Centre for Environmental Research—UFZ, Department of Environmental Engineering, Permoserstr 15, D-04318 Leipzig, Germany
Jamaan S. Ajarem: Zoology Department, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
Saleh n. Maoda: Zoology Department, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
Xiang Li: College of Landscape Architecture and Art, Northwest A&F University, Yangling 712100, China
Zhaojie Cui: School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China

Land, 2023, vol. 12, issue 11, 1-28

Abstract: Soybean ( Glycine max ) is a protein-rich oilseed crop that is extensively used for cooking oil and poultry feed and faces significant challenges due to adverse global climatic conditions aggravated by the ongoing climate crisis. In response to this critical issue, this study was initiated to assess suitable zones for soybean cultivation, aiming to facilitate informed land use decisions within the semi-arid terrestrial ecosystem. Through the utilization of geostatistical interpolation, data layers encompassing soil, irrigation water, land use and land cover, topographic features, and climate information were generated and overlaid based on criterion weightage derived from the Analytic Hierarchy Process. The accuracy of land use and land cover was rigorously evaluated, yielding a 70% overall accuracy and a Kappa (K) value of 0.61, signifying an acceptable level of precision. Validation through the Receiver Operating Characteristic curve for soybean crop suitability demonstrated a highly satisfactory area under the curve of 0.738. The study estimates that out of 172,618.66 hectares, approximately 47.46% of the land is highly suitable (S1) for soybean production, followed by 21.36% moderately suitable (S2), 11.91% marginally suitable (S3), 7.00% currently not suitable (N1), and 12.28% permanently not suitable (N2). Conclusively, the findings suggest that the study area exhibits conducive climatic conditions, optimal soil health, and access to quality irrigation water, all of which have the potential to support soybean crops with improved agronomic practices. This investigation offers valuable insights to both farmers and policymakers concerning irrigation water quality, agricultural productivity, and soil degradation.

Keywords: soybean; land suitability; water quality; climatic conditions; weighted overlay analysis; analytical hierarchy process (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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