To understand the performance of urban villages in terms of justice and inclusivity, an investigation from bottom-up was launched in current study. Through semantic differential (SD) method, subjective feelings of residents, workers and tourists were collected and evaluated; overall feeling was positive. Study indicated that urban villages in China, like in East Lake Village, with diverse life styles at all levels of society and registering positive overall evaluation, are sustainable. It concluded that development of adjacent formal space of the city, autonomous formalization of villagers and low rent of informal housing are essential conditions for a sustainable urban village. Suggested strategies for sustainable upgrading and reconstruction of urban villages should recognize and respect various types of groups, incorporating different demands and usage of space to protect diverse life styles. These strategies may entail cleaning, lighting and coloring which are effective ways to improve environmental quality.

Dynamic trade-offs and synergies among ecosystem services (ESs) are highly sensitive to land-use change, spatial scale, and future uncertainty. However, most ES-based zoning studies rely on static assessments that overlook temporal dynamics and scenario robustness. To address this limitation, we propose a novel intensity–trend–stability framework that integrates historical interaction strength, projected future trajectories, and cross-scenario consistency to assess and spatially zone ES interactions. The framework was applied to the Songnen Plain, China, using multi-scale analysis and four contrasting land-use scenarios for 2030. An XGBoost–SHAP model was further employed to identify key drivers and nonlinear effects underlying ES interaction dynamics. Results show that (1) land-use transitions exhibit strong scenario dependency under different development pathways. (2) Water yield consistently exhibits trade-offs with other ESs, whereas soil retention, carbon sequestration, and habitat quality maintain stable synergies, with interaction intensity generally weakening at coarser scales. (3) The proposed framework effectively identifies stable conflict zones, synergistic hotspots, and transitional areas, with HHH zones of water-related interactions accounting for 30.72–37.43% of the study area, while LLH zones of other ES pairs each occupy more than 39%. (4) Climatic and topographic factors primarily regulate water-related interactions, whereas vegetation conditions and landscape configuration dominate synergistic ES relationships, with pronounced nonlinear threshold effects. The proposed framework improves the detection of dynamic ES interaction patterns and supports scenario-based ecological zoning and sustainable land-use management.