The spatial morphology of traditional villages stems from prolonged interactions between socio-economic conditions and the regional natural environment under specific historical contexts. Over time, these settlements have acquired distinct spatial patterns through continuous adaptation to their surrounding ecosystems. Nevertheless, accelerated urbanization now exerts dual pressures—disrupting the spatial order and degrading natural ecosystems. In this context, an integrated analysis of the relationship between village spatial patterns and ecological conditions is essential for elucidating their formative mechanisms. The Xiangjiang River Basin is Hunan’s cultural core, and the spatial distribution of traditional villages is directly related to environmental variables. This study uses bivariate spatial autocorrelation and geographically weighted regression to investigate the relationship between the spatial distribution of traditional villages and ecological environmental appropriateness. The findings indicate the following: (1) The spatial distribution density of traditional villages in the Xiangjiang River Basin exhibits a negative correlation with the Ecological Environment Index (EEI), as evidenced by a Moran’s I value of −0.228. This suggests that traditional villages tend to be less concentrated in areas with a higher ecological suitability. (2) Among natural factors, the Relief Degree of Land Surface (RDLS), the Temperature Humidity Index (THI), and the Land Cover Index (LCI) display positive correlations with village density, with regression coefficients of 0.865, 0.003, and 11.599, respectively. In contrast, the Water Resource Index (WRI) shows a negative correlation, with a coefficient of −6.448, and (3) the impact of ecological suitability factors on village distribution is spatially heterogeneous: microtopographic variation is the primary driver in flat terrains, whereas the ecological carrying capacity exerts a greater influence in mountainous areas. These findings clarify the role of ecological suitability in shaping the spatial characteristics of traditional villages and provide a scientific basis for developing protection strategies that integrate ecological sustainability with cultural–heritage preservation.

This study explores the relationship and mechanism between traditional village distribution and human settlement suitability in Hunan Province. Based on village distribution data and a human settlement evaluation system, spatial analysis and the LISA model are used to analyze spatial correlation and influencing patterns. Results show that (1) Traditional village density is significantly negatively correlated with human settlement suitability. (2) L-H and H-L agglomerations dominate the region, with L-H clusters in central-northern plains and valleys and H-L clusters in western mountainous areas. (3) Human settlement factors show strong spatial heterogeneity, with natural factors varying regionally and human factors reflecting moderate adaptation. This study reveals the adaptive logic of traditional villages to natural and human environments, enriches relevant theories, and provides targeted guidance for classified protection of traditional villages and human settlement optimization.

High-quality growth of the construction industry and an improved human settlements environment are essential to sustainable urbanization. Existing studies have paid limited systematic attention to the spatial and temporal dynamics of the coordinated development between the construction industry and human settlements, as well as the underlying factors driving regional disparities. This gap restricts the formulation of precise, differentiated sustainable policies tailored to regions at different development stages and with varying resource endowments. Southern China, characterized by pronounced spatial heterogeneity and unique development trends, offers a natural laboratory for examining the spatio-temporal interaction between these two dimensions. Using panel data for 15 southern provinces (2013–2022), we applied the entropy method, coupling coordination model, Dagum Gini coefficient, spatial trend surface analysis, gravity model, and grey forecasting to evaluate current conditions and predict future trends. The main findings are as follows. (1) The coupling coordination degree rose steadily, forming a stepped spatial pattern from the southwest through the center to the southeast. (2) The coupling coordination degree appears obvious polarization effect, presenting a spatial linkage pattern with Jiangsu-Shanghai-Zhejiang, Hubei-Hunan-Jiangxi, and Sichuan-Chongqing as the core of the three major clusters. (3) The overall Dagum Gini coefficient declined, but intra-regional disparities persisted: values were highest in the southeast, moderate in the center, and lowest in the southwest; inter-regional differences dominated the total inequality. (4) Forecasts for 2023–2027 suggest further improvement in the coupling coordination degree, yet spatial divergence will widen, creating a configuration of “eastern leadership, central catch-up acceleration, and differentiated southwestern development.” This study provides an evidence base for policies that foster high-quality construction sector growth and enhance the living environment. The findings of this study indicate that policymaking should prioritize promoting synergistic regional development, enhancing the radiating and driving role of core regions, and establishing a multi-level coordinated governance mechanism to bridge regional disparities and foster more balanced and sustainable development.