Spatial distribution characteristics of rural settlements under diversified rural production functions: A case of Taizhou, China

Abstract

Over the past forty years, rural China has undergone dramatic spatial restructuring, and its production functions have gradually become diversified. However, although several studies have examined factors affecting the distribution of rural settlements in recent years, few have focused on rural production functions. To fill this gap, this paper proposes an analytical framework to understand the impact of rural production functions on the spatial distribution of rural settlements and quantitatively analyzes the rural areas of Taizhou municipality by using the bivariate Moran's I method at the township level. In general, the results show that the spatial distribution of rural settlements has different correlations with each type of rural production functions. The distribution has the strongest correlation with agricultural production functions, followed by the industrial manufacturing and service supply functions, while the weakest correlation is with the ecological leisure function. Further, in the high-value areas of the agricultural production function and the ecological leisure function, the distribution of rural settlements is discrete, with low density, a large scale, and a long distance. In contrast, in the high-value areas of the industrial manufacturing function and the service supply function, the distribution of settlements is clustered, with high density, a small scale, and a short distance. Based on the correlations, this paper sketches four types of ideal town-villages construction pattern to guide the optimization of rural settlements layout, including the productivist-oriented evenness pattern, the transit-oriented axis pattern, the idyll-oriented corridor pattern, and the urbanization-oriented integration pattern. This research provides scientific guidance for developing countries in the spatial planning of rural territories and the optimization of rural settlements.