In the face of increasingly complex urban challenges, a critical question arises: can urban ecosystems maintain resilience, vitality, and sustainability when confronted with external threats and pressures? Taking Kunming—a plateau-mountainous city in China—as a case study, this research constructs an urban ecosystem resilience (UER) assessment model based on the DPSIR (Driving forces, Pressures, States, Impacts, and Responses) framework. A total of 25 indicators were selected via questionnaire surveys, covering five dimensions: driving forces such as natural population growth, annual GDP growth, urbanization level, urban population density, and resident consumption price growth; pressures including per capita farmland, per capita urban construction land, land reclamation and cultivation rate, proportion of natural disaster-stricken areas, and unit GDP energy consumption; states measured by Evenness Index (EI), Shannon Diversity Index (SHDI), Aggregation Index (AI), Interspersion and Juxtaposition Index (IJI), Landscape Shape Index (LSI), and Normalized Vegetation Index (NDVI); impacts involving per capita GDP, economic density, per capita disposable income growth, per capita green space area, and per capita water resources; and responses including proportion of natural reserve areas, proportion of environmental protection investment to GDP, overall utilization of industrial solid waste, and afforestation area. Based on remote sensing and other data, indicator values were calculated for 2006, 2011, and 2016. The entire-array polygon indicator method was used to visualize indicator interactions and derive composite resilience index values, all of which remained below 0.25—indicating a persistent low-resilience state, marked by sustained economic growth, frequent natural disasters, and declining ecological self-recovery capacity. Forecasting results suggest that, under current development trajectories, Kunming’s UER will remain low over the next decade. This study is the first to integrate the DPSIR framework, entire-array polygon indicator method, and Grey System Forecasting Model into the evaluation and prediction of urban ecosystem resilience in plateau-mountainous cities. The findings highlight the ecosystem’s inherent capacities for self-organization, adaptation, learning, and innovation and reveal its nested, multi-scalar resilience structure. The DPSIR-based framework not only reflects the complex human–nature interactions in urban systems but also identifies key drivers and enables the prediction of future resilience patterns—providing valuable insights for sustainable urban development.

Rapid urbanization intensifies the overlap between natural hazards and persistent land-use disturbance in coastal agricultural landscapes, yet how these pressures jointly shape ecological risk remains unclear. In the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), we applied a hazard–vulnerability–ecological asset exposure (H–V–E) framework using 2000–2020 data and 5 km gridded assessment units, integrating rainstorm-induced flooding, tropical cyclones, human-induced landscape disturbance, and ecological–environmental and socioeconomic vulnerability. The framework uses ecosystem service value (ESV) as a proxy for ecological assets potentially exposed to loss and identifies eight H–V–E configurations to interpret risk patterns. Rainstorm-induced flooding formed localized hotspots along the central coast and western Pearl River Estuary, whereas tropical cyclone hazard showed a broader southern concentration. Mean landscape ecological risk changed little, but high-risk clusters intensified. ESV declined from CNY 279.12 billion to 262.72 billion over 2000–2020 and remained highest in peripheral forested and agricultural areas. Moderate-to-high integrated ecological risk covered 47.5% of the region. The low H–low V–high E configuration occupied the largest share (30.4%). These findings support differentiated management of cropland and surrounding ecological spaces through hazard mitigation, resilience enhancement, fragmentation control, and ecological asset protection.