Promoting Agricultural Sustainability in Semi-arid Regions: An Integrated GIS–AHP Assessment of Land Suitability for Encouraging Crop Diversification

Abstract

Informed decision regarding cultivating the right crop in the right land will guarantee maximum production, which is the need of the hour to meet the world’s burgeoning food demand and to ensure the sustainability of agriculture. The present study aimed to identify the land suitability for major crops in the semi-arid ecosystem of Palani block in Tamil Nadu by integrating the analytical hierarchy process (AHP) and geographic information system (GIS). Soil slope and various soil characteristics influencing crop growth such as soil depth, texture, drainage, gravelliness, pH and organic carbon were considered for assessing the land suitability. Weights and scores were assigned to the selected criteria and their respective sub-criteria based on their relative significance in influencing crop growth. It was found that soil drainage and texture were the most influencing factors for paddy cultivation, with weights of 0.49 and 0.27, respectively. For field beans, coconut, and guava, texture and depth were identified as the major influencing factors with high weightages ranging from 0.26 to 0.40. Results indicate that about 22% (8627 ha) of the study area was highly suitable for field beans, followed by paddy (18%). In contrast, paddy and coconut registered the largest land area under the marginally suitable class and were deemed unsuitable for about 19% and 21% of the land, respectively. For guava and field beans, respectively 37% and 44% of the land were found moderately suitable while 77% and 76.6% of the land were found suitable. Soil texture, soil depth, and drainage were identified as the major impediments to coconut and paddy suitability. An error matrix was generated by comparing the land suitability derived through the AHP–GIS method with the farmers’ opinions on land suitability for different crops. It indicated a high agreement between the suitability classes and farmers’ opinion for field beans, followed by coconut, guava and rice with kappa indices of 0.64, 0.51, 0.49 and 0.40 and overall accuracy of 75%, 65%, 62% and 60%, respectively. The present study not only helps in identifying suitable areas for crop cultivation, but also recommends land management strategies to each land parcel to improve land productivity and sustainability.