LAND SUITABILITY ASSESSMENT FOR SOYBEAN (GLYCINE MAX) IN BARDAGHAT MUNICIPALITY USING GIS TECHNIQUES
Birendra Tiwar, Amrit Dumre and Mahesh Jaishi
DOI: 10.26480/bda.02.2024.152.158
ABSTRACT
The Bardaghat Municipality, situated in the Nawalparasi West district, grapples with reduced agricultural productivity owing to inadequate land management practices and the absence of thorough land assessments for crops, notably soybean (Glycine max). This has resulted in meager soybean yields and constrained opportunities for small-scale farmers to diversify into more lucrative crops. The central aim of this research is to assess land suitability for soybean cultivation within the study area, with the overarching objective of boosting crop productivity and refining land use planning strategies. The research employed a comprehensive methodology, combining Pair-wise Comparison Matrix (PWCM) and Weighted Multi-Criteria Analysis via Analytical Hierarchy Process (AHP) to consider various biophysical criteria. Thematic maps were generated using Remote Sensing, Geostatistics, and Geographic Information Systems (GIS). Expert input guided the assessment of three primary criteria and eleven sub-criterion parameters, with weighted assigned through PWCM and integrated into a weighted overlay tool for thorough analysis. The research findings underscored the critical importance of Climatological factors (58.115%), Topographical features (30.9%), and Edaphological conditions (10.94%) in determining the suitability of land for soybean production. The resulting land suitability map revealed that the entire study area, accounting for 100% (162.05 km2), was highly suitable for soybean cultivation, with no land deemed unsuitable. Notably, built-up regions such as rivers and road networks were excluded from the research scope. The research seeks to advance sustainable agriculture by guiding land planning and empowering local small- scale farmers through optimized soybean cultivation, ultimately bolstering agricultural productivity in Bardaghat Municipality and fostering regional sustainability.
KEYWORDS
Analytical Hierarchy Process, Geographic Information System, Land Suitability, Pair-Wise Comparisons Matrix, Soybean.