It is important to clarify the impact of livelihood vulnerability level on farmers’ willingness to cluster their homesteads in order to promote the intensive use of homesteads and rural revitalization. This paper constructs a framework for the influence of farmers’ livelihood vulnerability on their intention of homestead agglomeration, then assesses the livelihood vulnerability of farmers based on 211 questionnaire data points, and analyzes the influence of farmers’ livelihood vulnerability on their intention of homestead agglomeration through binary logistic regression. The results showed that the vulnerability of farmers’ livelihoods had a significant negative effect on the intention of homestead agglomeration, and the more vulnerable farmers’ livelihoods were, the more significant their tendency to gather residential land. In addition, from the three-dimensional perspective of “exposure-sensitivity-adaptability”, exposure and sensitivity have a negative effect on farmers’ intention to agglomerate, while adaptability has a significant positive effect. Therefore, this paper argues that the vulnerability of farmers’ livelihoods can be improved by reducing exposure and sensitivity and increasing adaptive capacity to enhance farmers’ willingness to cluster their homesteads, thus providing some theoretical support for the preliminary work of homestead layout optimization in rural spatial governance.

Scientific analysis of the spatial features and driving factors of homestead agglomeration in different landform types of mountainous and hilly areas in Southwest China is of great significance for the optimization of national spatial patterns and high-quality rural development. This paper selects 22 villages in 3 towns with different landform types in Chongqing and examines the spatial features and driving factors of homestead agglomeration in different landform types from the perspectives of terrain gradient, kernel density estimation, farmer household agglomeration status, and landscape index. We analyzed the agglomeration spatial features of different landform types and explored their driving factors and mechanisms. It was found that (1) the distribution of homesteads in mountainous and hilly areas has obvious terrain gradient characteristics, and the layout of platform area homesteads is not constrained by terrain conditions. (2) Chongqing homesteads show a spatially dispersed pattern, but the degree of homestead spatial agglomeration varies significantly among different landform types, with those in mountainous and hilly areas being mainly dispersed and those in platform areas being mainly clustered. (3) Homestead spatial agglomeration is characterized by a combination of factors inside and outside the rural system and farmers’ willingness. There are differences in the driving factors of homestead agglomeration in different landform types. Homestead agglomeration in mountainous and hilly areas is mainly driven externally, while homestead agglomeration in platform areas is mainly driven internally. In both situations, farmers’ willingness must be fully considered. The results of this study can provide a scientific basis for the spatial planning and optimal allocation of land resources in the southwestern hilly area.

The industrial land supply impacts regional high-quality development, with various impacts across sectors. Considering China’s Yangtze River Economic Belt (YREB), this paper uses entropy weighting, spatial analysis, and the spatial Durbin model for spatiotemporal and regional analysis of the high-quality development level (HDL) and its spatial correlation with the industrial land supply. (1) The annual average HDL in all cities of the YREB increases, the regional HDL is spatially unbalanced and decreases from downstream–midstream–upstream, and HDL overlaps with economic development spatiotemporally. (2) The increase in high-tech industrial land supply promotes local HDL, and the raw material industrial land supply promotes HDL more indirectly than directly. (3) The land supply of the industrial supporting service, processing, food and light textile, and raw material industries has significant indirect effects. Processing has the strongest positive spillover effect, and food and light textile has a significant negative spillover effect. The HDL equilibrium in the YREB increased from 2010 to 2019, and the clustering of the processing, industrial supporting service, and food and light textile industries aggravated the spatial imbalance. (4) The regional structure and layout of the industrial land supply should be optimized to promote the HDL of the YREB.