Assessing Coastal Landscape Vibrancy and Ecological Vulnerability with Multi-Source Big Data: A Framework for Sustainable Planning

The intensifying pressures of urbanization and climate change on coastal zones necessitate a holistic understanding of the interplay between human activity and ecological integrity for sustainable development. However, prevailing methods for assessing coastal vibrancy often overlook direct measures of human presence and fail to quantitatively capture its complex relationship with ecological vulnerability. To address these gaps, this study develops a novel multi-dimensional assessment framework for Coastal Landscape Vibrancy (CLV) and empirically examines its interaction with ecological vulnerability factors in Beihai, China. Moving beyond built-environment-centric approaches, our framework integrates the ‘Crowd’ dimension, directly quantified using Baidu Heat Index data, with the ‘Place’ dimension, characterized by urban features, natural attributes, and visual experience. Principal Component Analysis (PCA) was employed to objectively weight these indicators and construct a composite CLV index. We then applied multiple linear regression to analyze the influence of ecological factors constructed based on the Sensitivity-Resilience-Pressure (SRP) model. The results revealed that vibrancy was highly concentrated in urban cores and exhibited significant spatiotemporal variations. Regression analysis revealed that while ecological quality factors like green coverage (β = 0.236, p < 0.001) positively influenced vibrancy, anthropogenic stressors such as slope (β = −0.457, p < 0.001) and the impervious surface index (β = −0.092, p < 0.001) had significant negative impacts, highlighting a critical trade-off between human activity and ecological conditions. The findings provide a quantitative, evidence-based foundation for spatial planning, demonstrating that sustainable coastal vibrancy is achieved through a balanced integration of human activity and ecological conservation, rather than through unchecked development. This framework offers critical insights for formulating strategies that simultaneously enhance ecological resilience and optimize human service facilities.