Spatial Pattern and Influencing Factors of Rural Settlements in Qinba Mountains, Shaanxi Province, China

Abstract

Spatial patterns and the influencing determinants of rural settlements are the most important indicators for understanding the constituent structure of rural regional systems. However, there is little knowledge addressing the characteristics from the settlement perspective by realizing the spatial reconstruction and sustainable development of rural settlements. Therefore, in this study, we analyzed the geographical, size, and morphological properties of rural settlement patterns in the Qinba Mountains in southern Shaanxi Province, China, using rural settlement and remote sensing data through spatial measurement index, gradient transects, demographic-economic index, and geodetector analysis. The results show the following: (1) Overall, rural settlements have spatial characteristics of “high-density multi-core clusters (0.8–1.6/km2) and low-density broadly scattered (<0.08/km2)”. There is a significant positive correlation between the scale of rural settlement density and the characteristics of high-value agglomeration. (2) The spatial disparities of morphological traits of settlement shapes are significant. Furthermore, 1840 NP/piece of plain basin landform types provide high-value areas for each settlement feature value, and locations with moderate slopes are best for settlement dispersal. Moreover, rivers, roads, and distance from township centers are all examples of beneficial directivity. There is consistency between the spatial differentiation of rural settlement areas per capita and the distribution of settlement scale. Conversely, the settlement density is inconsistent with the agricultural production value density’s spatial distribution features. (3) The impact of geographical factors on the diversification of settlement characteristics has significant spatial differences. Moreover, natural ecological characteristics such as elevation and landform and the distribution of cultivated land strongly influence the spatial pattern of the study region. Finally, the study findings can be beneficial for land and space planning and rural governments to develop sustainable rural settlements.