Assessment of Sustainable Development of Rural Settlements in Mountainous Areas: A Case Study of the Miaoling Mountains in Southwestern China

Abstract

As a model based on the harmonious development of society, economy, population, and resources, sustainable development is an essential driving force for a country’s social and economic development. The countryside is an important part of the country, and its sustainable development has been given attention, but existing research lacks a focus on the sustainable development of rural settlements in mountainous areas. In this paper, the rural settlements in the Miaoling Mountains of China are taken as the research object, a geographic detector is used to determine the weight of rural settlement sustainable development factors, a rural settlement sustainable development model is constructed, and a local spatial autocorrelation method is used to quantitatively analyse the level of sustainable development of the rural settlements and the influencing factors related to both the natural environment and socio-economic levels. The results show that (1) 78% of rural settlements in the Miaoling Mountains have a medium to low level of sustainable development and are weak in overall sustainability. (2) The spatial differentiation of the sustainable development levels of rural settlements in the Miaoling Mountains are apparent, and the high sustainable development level settlements are mainly distributed around the urban areas. In contrast, the low sustainable development level settlements are scattered. (3) The level of sustainable development is positively correlated spatially with gross domestic product (GDP), arable land, elevation, normalised difference vegetation index (NDVI), water systems, and roads, and negatively correlated spatially with slope. Of these, GDP, arable land, and elevation have a more substantial influence on the level of sustainability of rural settlements. According to the local autocorrelation analysis, the positively correlated settlement types are mainly clustered in distribution, while the negatively correlated settlement types are sporadic.