Landscape dynamics driven by socioeconomic factors of the coastal cities along the Yellow Sea and Bohai Sea over the last 40 years

• Construction land and aquaculture ponds expanded displacing dry land and tidal flats in YSBS region. • YSBS region exhibited progressive homogenization, intensified fragmentation, and amplified anthropogenic disturbances. • Landscape patterns are primarily driven by socioeconomic factors like road and population. • Patch density and other landscape metrics are advised to guide policies balancing conservation and development. Coastal regions along the Yellow Sea and Bohai Sea (YSBS) are critical globally for biodiversity conservation and ecological security. However, these ecosystems face increasing threats from synergistic pressures of population growth and economic development, which drive siginificant changes in landscape pattern. While existing studies have employed remote sensing and ecological spatial analysis to assess landscape patterns in key wetland areas, they predominantly focus on isolated coastal ecosystems or singular drivers rather than the complex human-environment interactions shaping these dynamics. Therefore, this study analyzed land use/land cover changes (1980–2020) to quantify spatiotemporal landscape dynamics and employed the Geodetector model to identify driving mechanisms of natural and socioeconomic factors. The results showed that construction land and reservoir pond expanded dramatically by 180.68% and 200.63% from 1980 to 2020, respectively, at the expense of dry land and tidal flats. Over four decades (1980–2020), the YSBS region exhibited spatiotemporal heterogeneity in landscape evolution, marked by progressive homogenization (46.47% Largest Patch Index, decline), intensified fragmentation (8.49% Patch Density, reduction), and amplified anthropogenic disturbances (108.78% Degree of Landscape Disturbance surge), with contrasting dynamics between industrialized hubs (e.g., Tianjin’s 36.69% Degree of Landscape Disturbance rise) and conserved wetlands (e.g., Dongying’s 4.14% Largest Patch Index growth). Geographical detector analysis revealed that socio-economic factors dominated landscape pattern variations. Road density (S6) exhibited the strongest explanatory power for fragmentation, diversity, and disturbance metrics. Synergistic interactions between fiscal revenue-expenditure ratio (E5) and tourism activity, population growth, and built-up land per capita amplified patch density explanatory power from 28.6% to 72.1%, highlighting multi-factor collaborative driving mechanisms. This study offers new insights for landscape spatial planning by using patch density as a critical metric with other ecological indicators (e.g., Largest Patch Index, Degree of Landscape Disturbance) and considering interactions between socioeconomic factors, to create policy synthesis balance landscapes ecology and sustainable economic development.