Monitoring water coverage in intertidal zones is challenging due to the lack of satellite sensors that simultaneously provide both high spatial and high temporal resolution. Landsat offers detailed spatial information but is limited by its 16-day revisit cycle, whereas Himawari-8 provides frequent observations but at coarse spatial scales. Existing multi-sensor fusion approaches, such as STARFM and ESTARFM, attempt to bridge this gap but rely on the assumption of linear or abrupt land cover changes, which is inadequate for capturing the gradual and non-linear dynamics of tidal environments. This study proposes a simulation-driven method to enhance water coverage monitoring by generating reference images that represent varying water height conditions. The approach integrates normalized Landsat OLI and Himawari-8 AHI imagery with digital elevation and tidal models to interpolate Modified Normalized Difference Water Index (mNDWI) values. Through linear interpolation, synthetic reference images are produced for low, medium, and high-water height scenarios, filling temporal gaps and providing additional input for fusion-based monitoring. Results from the Hsiang-Shan Wetland demonstrate that simulated reference images contribute more significantly to accurate water mapping than Himawari-8 data alone. The method improves temporal continuity, enhances the representation of tidal dynamics, and reduces discrepancies in fused outputs. Although the accuracy depends on DEM and tidal model quality, the findings highlight the potential of simulation-driven approaches to strengthen water monitoring frameworks. This method can be extended to support applications in flood mapping, wetland management, and coastal conservation.
Putri et al. (Sun,) studied this question.