Insights into the dynamics of coastlines and tidal flats at fine spatial and temporal resolutions are essential for sustainable development. Previous studies were generally conducted at relatively coarse temporal intervals, which hardly captured detailed coastal dynamics, especially in rapidly developing islands. In this study, we developed a new method to map the monthly changes in coastlines and tidal flats in the Zhoushan Archipelago during 1985–2017 using the full time series of Landsat images based on the Google Earth Engine (GEE) platform. First, we built the full time series of the Modified Normalized Difference Water Index (MNDWI). Second, we derived temporal segments of MNDWI using a binary segmentation algorithm. Third, we classified the corresponding coastal cover types (i.e., water, tidal flats, and land) for each temporal segment based on the features of MNDWI and regional tidal heights. Finally, we identified the change information including conversion types, and turning years and months. Results indicate that the proposed method can well identify turning years with an overall accuracy of 90% and map coastal cover types with overall accuracies of 89–94% in 1985 and 87–92% in 2017. Significant coastline expansions and declines in tidal flats were found in the study area. The areas of water and tidal flats decreased by 6% and 10% during 1985–2017, respectively, while the land area increased by 18%. The land reclamation was accelerated in the recent decade, and mainly occurred on the medium-large islands, their surrounding small islands, and the islands close to the mainland. The proposed framework based on the GEE platform is transferable to investigate coastal dynamics in other areas. The derived information of changes in coastlines and tidal flats is of great use for sustainable management and ecological studies in coastal areas.