In the context of marine sustainable development and resilient city construction, systematically conducting precise identification and evolution analysis of damaged space in urban coastal landscape has become an important topic in current coastal landscape protection and restoration practices. Based on Nature-based Solutions, this study constructs an analytical framework for clustering recognition and simulation application of damaged space in coastal landscapes, interpreting and analyzing the evolutionary trends and driving mechanisms of coastal landscape damage. An empirical study is conducted in the typical coastal zone of Yancheng City. Using landscape type and driving factor data from 2010 to 2020, a clustering recognition model is established by integrating the PLUS model with spatial autocorrelation analysis methods to simulate the evolutionary trends of damaged space in the coastal landscape. The Geographic Detector is further employed to reveal the impacts of driving factors and their interactions on the differentiation of damaged space. The results indicate that from 2010 to 2030, the damaged space of the coastal landscape exhibit a gradient evolution characteristic, shifting from coastal agglomeration to inland expansion (Moran’s I > 0.6). The clustering model identifies five types of damaged space, with high damage regions concentrated in coastal wet-lands, reclamation areas, and urban expansion belts. Vegetation scale, climatic temperature, regional economy, and land-use type adjustments are key variables influencing the evolution of landscape damage (q > 0.15). Corresponding restoration and renewal efforts need to be coordinated based on the mechanisms combining different levels of landscape damage zoning and key driving factors. The findings validate the effectiveness of this analytical framework in the dynamic characterization and mechanism analysis of coastal damaged space, providing methodological support and technical pathways for the zonal restoration and resilient management of coastal urban landscapes