Topography is one of the important factors influencing the distribution of rural settlements, as the natural environment in plateau-mountain areas is more complicated and harsher and the forces of various natural influences are more obvious. Analyzing the correlation between settlement distribution and topography would help understand the influence of topography on human activities. This paper takes rural settlements in Yunnan Province as the research object, introduces the concept of the distribution index, and integrates the methods of GIS spatial analysis and mathematical statistics to analyze the correlation between them. The results show that (1) the distribution pattern of rural settlements in Yunnan Province is dense in the northeast, sparse in the northwest, dense in the middle, and sparse in the south; the overall pattern shows low density, fragmentation, and a dotted distribution of high-value areas, showing three typical core areas with very obvious spatial differentiation. (2) The distribution of rural settlements is influenced by three key topographic factors: Relief amplitude, incision depth, and surface roughness. The dispersion index of rural settlements drastically declines as the value rises. (3) Each topographic factor influences the natural resources and climatic characteristics of the region, and by coupling them with the production and life of the rural settlements and the psychological needs of the inhabitants, they form an intrinsic mechanism that influences the distribution of rural settlements. (4) Topography is an important factor when developing and constructing in plateau-mountain areas. The environmental protection and construction of human settlements should be in accordance with nature and adapted to the terrain, which can reduce the damage to the natural environment. The study provides effective data support for quantifying the relationship between the distribution of rural settlements and topography in the plateau-mountain area and optimizing the layout of rural settlements.

The historical authenticity of historic urban areas has been compromised, and community cohesion has declined, necessitating comprehensive methods to systematically identify spatial textures and socio-cultural transformation characteristics. This study investigates the Jianxi Historic Urban Area in Luoyang from a Historic Urban Landscape perspective, integrating GIS, sDNA tools, and semi-structured interviews to analyze material spatial evolution and socio-cultural shifts. The findings reveal stable street network structures enhanced by road expansions, functional intensification marked by rising residential density and tertiary sector growth, and high replacement rates of 1950s–1960s buildings that improved the area’s physical quality but disrupted historical continuity and heritage integrity. Material transformations fragmented collective memory and reshaped residents’ sense of place identity. This research proposes sustainable renewal strategies, emphasizing refined gradient control models, community identity revitalization, and participatory decision-making, offering actionable insights for regenerating historic urban areas.

Traditional villages in Northwest Yunnan represent complex socio-ecological systems navigating the dual challenges of ecological fragility and rapid socio-economic transformation. This study examines how vulnerability patterns shape the spatial distribution of 248 traditional villages through an integrated assessment framework. We developed a Sensitivity-Resilience (S-R) model where sensitivity captures environmental constraints including topographic factors (elevation, slope, terrain roughness) and climatic variables (temperature, precipitation), while resilience encompasses ecological buffers (vegetation coverage, water network density) and socio-economic adaptive capacity (road network density, population density, GDP, nighttime lights)-combining 11 indicators from remote sensing data (DEM, MODIS climate products), national census records, and geographic databases (2000-2020). The geographic detector method, a spatial statistical technique that quantifies factor contributions without assuming linear relationships, revealed both individual and interactive effects on village distribution. Results show 81% of villages concentrate in low-to-moderate vulnerability zones, forming linear clusters along river valleys and lake peripheries. Natural factors impose primary spatial constraints (slope q = 0.72, elevation q = 0.69), while socio-economic factors exhibit stronger influence overall (GDP q = 0.89, road density q = 0.66). Critically, all factor interactions show enhanced effects, especially GDP interactions with road density and nightlight that reveal how economic development, accessibility, and urbanization jointly determine village vulnerability patterns. These findings directly inform differentiated conservation strategies for regional planners and heritage policymakers. High-vulnerability villages (17.7%) require adaptive infrastructure and hazard mitigation; moderate-vulnerability clusters (70.2%) can serve as development nodes with controlled tourism; low-vulnerability settlements (10.9%) need protection from urbanization pressure. The vulnerability framework provides transferable methods for understanding how traditional villages persist within, rather than despite, ecological constraints in fragile mountain regions globally.

Rapid population aging in developing countries has intensified demand for accessible nursing home services, yet spatial disparities in service distribution remain insufficiently examined in secondary cities. This study investigates spatial distribution and multi-dimensional accessibility of nursing homes in Kunming, China, using comprehensive spatial analytical methods to inform sustainable urban development. We analyzed 205 nursing homes with 47,600 beds, evaluating spatial distribution patterns, economic accessibility, and spatial accessibility across different transportation modes. Our analysis reveals a pronounced monocentric pattern with nursing resources concentrated within central urban districts, creating a “primary core-multiple satellite” structure and spatial mismatch between service supply and older adult population needs. A distinct institutional dichotomy exists between publicly and privately operated facilities, establishing a dual-track system with different accessibility implications for social equity. Economic accessibility analysis demonstrates significant barriers in central urban and tourism-oriented districts dominated by higher-priced private facilities, where minimum prices frequently exceed average monthly pension. Spatial accessibility remains inadequate across all transportation modes, with only 24.3% of communities achieving normal or higher accessibility via private car, 21.5% via public bus, and merely 13.9% via walking. These limitations primarily stem from insufficient service capacity (34 beds per 1000 older adults) relative to demographic needs rather than transportation constraints. We recommend three sustainable interventions: implementing demand-based planning mechanisms, establishing progressive pricing policies, and developing older adult-friendly transportation networks. This framework supports sustainable urbanization by promoting spatial equity and efficient resource allocation, providing valuable insights for secondary cities pursuing sustainable development goals.

Achieving carbon emission reductions in the residential building sector while maintaining economic growth represents a global challenge, particularly in rapidly developing regions with internal disparities. This study examines Jiangsu Province in eastern China—a economic hub with north-south development gradients—to develop an integrated framework for differentiated carbon reduction pathways. The methodology combines spatial autocorrelation analysis, logarithmic mean Divisia index (LMDI) decomposition, system dynamics modeling, and Tapio decoupling analysis to examine urban residential building emissions across three regions from 2016–2022. Results reveal significant spatial clustering of emissions (Moran’s I peaking at 0.735), with energy consumption per unit area as the dominant driver across all regions (contributing 147.61%, 131.60%, and 147.51% respectively). Scenario analysis demonstrates that energy efficiency policies can reduce emissions by 10.1% while maintaining 99.2% of economic performance, enabling carbon peak achievement by 2030. However, less developed northern regions emerge as binding constraints, requiring technology investments. Decoupling analysis identifies region-specific optimal pathways: conventional development for advanced regions, balanced approaches for transitional areas, and subsidies for lagging regions. These findings challenge assumptions about environment-economy trade-offs and provide a replicable framework for designing differentiated climate policies in heterogeneous territories, offering insights for similar regions worldwide navigating the transition to sustainable development.