Land

Amid rapid global population aging, developing age-friendly urban spaces centered on the “15-minute community life circle” has become a priority in planning research. Taking Shenhe District of Shenyang City, a region undergoing deep aging, as a case study, this research constructs a facility weighting system reflecting the actual needs of the elderly. Integrating multi-source spatial data, the XGBoost model and SHAP framework were applied to analyze the non-linear effects of socio-economic, functional, and land-use factors on facility convenience. Results indicate that: (1) facility convenience exhibits a distinct “west-high, east-low” spatial pattern, characterized by high agglomeration in the western core and significant deficits in the eastern fringe; (2) convenience levels vary across categories, with medical and health facilities showing the highest accessibility, while cultural and leisure (CALFs), life service, and elderly care service facilities (ECSFs) remain the primary deficiencies; and (3) influencing variables demonstrate complex non-linear mechanisms, wherein functional density and distance from the city center are critical drivers with non-monotonic effects, while road network density displays threshold effects, inhibiting ECSFs and CALFs at high densities. These findings provide a refined, quantitative basis for optimizing facility layouts and formulating urban renewal strategies to build age-friendly communities.

Inequity in urban walking resources has been garnering increasing scholarly attention. However, there is still no widely accepted tool for assessing walkability, making results difficult to compare across studies. In addition, the ways in which walkability equity is typically defined and measured often overlook China’s local context. Therefore, this study develops a comprehensive walkability evaluation framework for Kunming’s main urban area using open-source data and census information, synthesizing 15 indicators across five dimensions (connectivity, accessibility, suitability, sociability, and aesthetics) analyzed through the Catastrophe Theory models (CT models). Furthermore, spatial autocorrelation, the Concentration Index (CI), and an interpretable machine learning framework (Random Forest-SHAP) are employed to examine the relationships between community walkability disparities and socio-economic factors for a spatial justice assessment. The results show the following: (1) Community walkability in the main urban area of Kunming exhibits a “core–periphery” spatial distribution pattern, where connectivity, accessibility, and sociability follow the general pattern, while suitability and aesthetics display heterogeneous spatial distributions. (2) The social differentiation characteristics of community walkability in Kunming’s main urban area correlate significantly with age structure, hukou registration, and social status, but show limited association with ethnicity and economic status. These findings challenge Western-centric social differentiation paradigms and underscore the context-specific nature of walkability equity in China, thus providing new perspectives for the understanding of built environment justice in the context of Chinese cities.

Ecological Security (ES) is an essential safeguard for regional sustainable development. Scientifically elucidating the multiscale evolution of ES patterns and their driving mechanisms is critical for ecological governance and conservation in Mountainous Urban Agglomerations (MUAs). Taking the central Yunnan Urban Agglomeration (CYUA) as a representative MUA, this study constructs a three-dimensional ES assessment framework integrating ecological health, ecological sensitivity, and ecological risk. By integrating ES slope-spectrum analysis with spatial autocorrelation, Geodetector, Multiscale Geographically Weighted Regression (MGWR), and machine learning, we analyze the spatiotemporal evolution of regional ES patterns and their driving mechanisms from a multiscale perspective. Results show that from 2000 to 2020, ES in the CYUA exhibited an overall improving trend with clear scale dependency. At the micro-scale, urban expansion intensified ecological fragmentation, whereas at the macro-scale, regional integration under policy guidance was evident. ES shows significant differentiation along slope gradients, forming a typical pattern of “low-slope–high-risk and high-slope–high-security,” with the 10–25° interval identified as a “conflict front” between ecological conservation and urban development, facing elevated degradation risks. Human Activity Intensity (HAI) is the dominant driver of ES spatial differentiation, with a critical pressure threshold of 0.29, and exhibits significant nonlinear interactive effects with slope and NDVI, with q-values exceeding 0.6. Overall, this study reveals complex human–environment interactions in MUAs and provides scientific evidence for balancing topographic constraints with urbanization, optimizing territorial spatial patterns, and promoting coordinated development of ecological conservation and high-quality urbanization.