Crop suitability analysis for the coastal region of India through fusion of remote sensing, geospatial analysis and multi-criteria decision making

Crop suitability analysis plays an important role in identifying and utilizing the areas suitable for better crop growth and higher yield without deteriorating the natural resources. The present study aimed to identify suitable areas for rice and coconut cultivation across the coastal region of India using the analytic hierarchy process (AHP) integrated with geographic information systems (GIS) and remote sensing. A total of nine parameters were selected for suitability analysis including elevation, slope, soil depth, drainage, texture, pH, soil organic carbon, rainfall, temperature and a land use land cover (LULC) constraint map. This study represents the first-ever application of an integrated approach combining AHP, GIS, and remote sensing for crop suitability analysis in entire coastal region of India. The weights for the parameters and subclasses were assigned using the AHP method based on experts' opinions. Subsequently, all the thematic maps were overlaid using the weighted overlay analysis to generate a land suitability map. Separately, the LULC crop mask map was used to extract suitable areas for rice and coconut cultivation to create crop-specific suitability maps. The final suitability maps were classified into four different classes: highly suitable, moderately suitable, marginally suitable, and not suitable for crop production. The findings revealed that approximately 13.68% of the study area was highly suitable, with around 19.26% and 18.35% being moderately and marginally suitable, respectively, and 13.76% was not suitable for rice cultivation. Similarly, for coconut cultivation, approximately 11% were highly suitable, with 27.40% and 18.34% being moderately and marginally suitable. However, about 35% of the total study region was deemed permanently unsuitable for any type of cultivation. The suitability maps were validated using area under receiver operating characteristic curve (AUROC). The AUROC values for rice and coconut were found to be 0.764 and 0.740 indicating high accuracy. By strategically cultivating rice and coconut in highly and moderately suitable locations identified in the current study, and utilizing marginally suitable areas for other crops, it is possible to achieve financial viability in agricultural production by increasing crop yield without causing harm to natural resources.