Abstract:To effectively evaluate disaster resilience in mountainous urban areas, the study focused onthe central urban area of Chongqing, a typical mountainous city in China influenced by the flood-landslidedisaster chain. Based on the concept and mechanisms of urban disaster resilience and combinedwith the causal logic of the Pressure-State-Response (PSR) model, a resilience evaluation index systemfor floods and landslides was constructed through the collection and analysis of multi-source data.Landslide pressure resilience was evaluated using machine learning techniques, and the flood pressureand state-response resilience were assessed through a combination of subjective and objective weightinganalyses with the VIKOR method. The rank-sum ratio comprehensive evaluation method was em ployed to construct an overall resilience assessment model, measure urban disaster resilience levels,classify resilience grades, and analyze the assessment results. The findings indicated that: (1) High landslide pressure resilience was observed in the western and northwestern regions of the study area,moderate resilience in the central area, and low resilience in the southern and northeastern regions.(2) Flood pressure resilience was lower in the central region of the study area, while the eastern andwestern regions generally displayed higher resilience, with the outer regions being more resilient thanthe inner regions. Nanchuan District in the southeastern region of the study area had the highest floodpressure resilience. (3) Yuzhong District, the core urban area of Chongqing, showed the highest stateresponseresilience, with the spatial distribution of state-response resilience exhibiting an evident decreasingtrend from center to periphery. (4) The spatial distribution of comprehensive resilience did notshow distinct patterns, but it was common for an administrative region within the study area to exhibitvarying resilience levels, reflecting the uneven development of resilience across different stages.
