The dynamic coastal zones, marked by rich biodiversity and rapid transformations due to human activities, present a challenging environment for monitoring and management. Tidal flats, a key natural feature of these zones, are increasingly subjected to anthropogenic stress, rising sea levels, and various environmental pressures. This study addresses the critical need for a robust, large-scale remote sensing approach to monitor these changes over time, particularly under fluctuating tides and evolving coastal landscapes. Using the three decades of Landsat 5 and Landsat 8 data (1990-2020), we developed an innovative approach for the automatic acquisition of low-tide imagery. Our method, which incorporates knowledge-based of tidal flat extraction, achieved a classification accuracy of over 95%. This technique effectively mitigates the impact of clouds, fog, and waves on image analysis, enabling precise and rapid delineation of large-scale intertidal zones. As a result, we produced the most extensive dataset on tidal flat areas in China's coastal zone, updated at three-year intervals. The spatial analysis results showed the primary distribution of tidal flats in Liaoning, Shandong, Jiangsu, Zhejiang, and Guangxi, which collectively account for over 70% of China's tidal flat areas. We observed distinct patterns of tidal flat evolution, with rapid changes in regions like the Liaohe River Delta, Yellow River Delta, Yangtze River Delta, and the Jiangsu Coast. These changes are closely linked to increased reclamation activities and salt marsh vegetation expansion. In contrast, coastal areas like Tianjin and Zhejiang showed a swift expansion of intertidal zones initially, followed by a stabilization post-2010, constrained by limited development space. Our study's approach to rapid tidal flat extraction has shown promising applications in other global river deltas. The comprehensive tidal flat mapping and data generation presented here offer valuable insights and support for the monitoring, management, and sustainable development of coastal wetlands.@en