The surface water changes extremely since it could be possibly drought in summertime or flooding in the rainy seasons. Several kinds of satellites had been used in observing surface water since the 1970s. Nevertheless, the information lacking becomes controversial in capturing the dynamic changes in water coverage. To cope with this well-known issue in remote sensing, a method called image simulation was found. Image simulation becomes one of the solutions to unravel the shortage of remote sensing data by creating more images. Using the current improvements in remote sensing, more satellite images are available to grasp the connection between water height and the coverage of surface water. Hence, this study examines the recent remotely-sensed improvement that can observe the changes in surface water. We simulate an image at a particular water height by applying linear interpolation with the two closest water height images. This study proposes two approaches, which are A1 and A2. The A1 uses the estimated water height from the NAO.99b tide model. On the other hand, A2 applies the estimated water heights from AHI imageries. The evaluation in this study examines the proposed solution in three different cases, which are the low water height, the middle water height, and also the high water height case. A2 shows better performance for the three cases as the correlation number is more than 0.9. In summary, with the current technology in remote sensing, image simulation is possible to prevent the limitation of data. AHI imagery is able to capture the dynamic changes of water coverage within the intertidal area for generating the finer spatial remotely-sensed images.