Soybean (Glycine max) Cropland Suitability Analysis in Subtropical Desert Climate through GIS-Based Multicriteria Analysis and Sentinel-2 Multispectral Imaging
LAND(2023)
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.
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Key words
soybean,land suitability,water quality,climatic conditions,weighted overlay analysis,analytical hierarchy process
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