Integrative approach of RS and GIS in characterization of land suitability for agriculture: a case study of Darna catchment

Abstract

Land elements like slope, soil depth, land use/land cover, water holding capacity, soil texture, soil erosion, elevation, potential of hydrogen, etc. determine the suitability for agriculture. Land suitability analysis is a one of the methods of assessment of detecting inherent capacities, potential and suitability levels of the lands for agriculture, and was utilized with the same land elements in this study. A multi-criterion decision making approach using IRS P6 LISS-IV satellite dataset within a GIS environment was used to identify suitable areas for agriculture in the Darna catchment. Experts’ opinions, literature review, and correlation technique were used to decide influencing criteria, assign scores to sub-criteria, and judgment formation in pairwise comparison matrix. All thematic layers of criteria were integrated with each other in GIS using the weighted overlay technique and generated agriculture suitability map into four classes according to FAO. About 23% of the area is under agriculture in the study region. This area can extend up to 69% under agriculture converting fallow land, scrub land, and sparse forest according to soil qualities with suitability levels, i.e., highly suitable (19%), moderately suitable (16%), and marginally suitable (34%). About 31% (19,219 ha) of reviewed area are classified in the class permanently “not suitable” for agriculture. Moderately and marginally suitable land requires the irrigation facility for efficient agriculture. This study emphasizes that about 46% area has potential as agriculture land and it will help improve the financial condition of the farmers.