Historic cities face a dual challenge of preserving cultural authenticity and adapting to modern urbanization, yet existing studies often overlook the multidimensional coupling mechanisms critical for sustainable urban renewal. This research has proposed a replicable framework to balance heritage conservation, ecological restoration, and pedestrian mobility. Focusing on the historic city of Shenyang, this study evaluated spatial dynamics via the Walkability Index (WI), Green View Index (GVI), and Cultural Heritage Index (CHI), and quantified their coupling coordination patterns. Multisource datasets including OpenStreetMap road networks, POIs, and Baidu street-view imagery were integrated. A Coupling Coordination Degree (CCD) model was developed to assess system interactions. Results revealed moderate overall walkability (WI = 42.66) with stark regional disparities, critically low greening (GVI = 10.14%), and polarized heritage distribution (CHI = 18.73) in Shenyang historic city. Tri-system coupling was moderate (CCD = 0.409–0.608), constrained by green-heritage disconnects in key districts. This work could contribute to interdisciplinary discourse by bridging computational modeling with human-centric urban design, providing scalable insights for global historic cities.

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.

Urban green space (UGS) service mismatch is a key public space issue that needs to be addressed in the renewal of built-up urban areas. Existing studies have mostly evaluated UGS service levels from the perspective of green space supply or accessibility, but have paid insufficient attention to the mismatch among population demand, UGS supply, and UGS accessibility, as well as the built environment contexts associated with different mismatch types. Taking the urban core of Shenyang as a case study, this study constructs a UGS service mismatch typology and combines non-UGS built environment indicators, XGBoost, and SHAP to identify the spatial characteristics and nonlinear model-based associations of different mismatch types. The results indicate the following: (1) UGS service problems in the urban core of Shenyang can be divided into five types. Priority Improvement Area, Potential Activation Area, and Resource-rich Area together account for 56.05% of the study area, indicating that the mismatch among demand, resources, and accessibility has a high spatial coverage. (2) Different mismatch types correspond to differentiated built environment profiles. Priority Improvement Area co-occurs with service shortage, weak functional concentration, low development intensity, and weak transit support. Potential Activation Area has relatively good functional and transport foundations, but its UGS service transformation remains insufficient. (3) SHAP results show that public transit proximity, functional concentration, and building form are key indicators associated with model-based type differentiation. The contributions of mean building floor and POI density to Priority Improvement Area decline after exceeding their breakpoints, indicating that, within the model, this type is more likely to occur in areas with insufficient development intensity and functional concentration. By integrating the demand–supply–accessibility relationship, UGS service mismatch typology, and built environment characterization, this study provides a more spatially targeted analytical framework for UGS service diagnosis in built-up urban areas, and supports the shift from uniform green space provision to type-specific service optimization.