Optimal Land Use Structure for Sustainable Agricultural Development—A Case Study in Changsha County, South Central China

Abstract

Environmental and social problems caused by overfertilization, excessive pesticides, and encroachment on farmland are increasingly serious in agricultural settings, especially in suburban agricultural areas and highly intensive agricultural areas. Hence, modern agriculture not only pursues economic benefits, but it also pays more attention to ecological functions and social stability. This paper proposes a set of methods which are designed to realize optimal agricultural benefits and sustainable development by scientifically adjusting the land use structure. Taking Changsha County in South Central China as a case study, this paper first built an index system and adopted the information entropy-TOPSIS method to assess the economic, social, and ecological benefits of agricultural land use. Next, a coupled coordination model and an obstacle model were chosen to diagnose those factors that remained as obstacles to achieving the sustainable and coordinated development of the benefits of agricultural land use. Finally, based on the analysis of the changes in the benefits and obstacles over time, socio-economic and ecological constraints were established, and the multi-objective linear programming method (MOLP) was used to determine the comprehensive benefits and optimal land use structure. The results indicate that: (1) The agricultural benefits were stably increasing from 0.20 in 1996 to 0.79 in 2016. (2) The economic benefit index is no longer the main obstacle, while the social benefit index, which includes components such as the food security index, has become the principal influencing factor. (3) The optimal land use structure and comprehensive benefits were presented by taking into consideration the economic development, environmental protection, and social needs. This study emphasizes economic development, but it also seeks coordinated development with comprehensive benefits. The results of the study could provide scientific recommendations for optimizing the agricultural land use spatial patterns and sustainable land use.