## 1 Introduction  
Tidal flats are extensive coastal ecosystems that form intertidal areas and are periodically imundated due to the ebb and flow of tides, which cover an area of 128 K km\({}^{2}\) of the Earth's surface [1, 2]. They play a vital role in removing inorganic and organic matter from the land, stabilizing the coastline, and providing protection against coastal flooding caused by hurricanes and storm surges [3, 4, 5]. Despite the geographical and ecological importance of tidal flats, the global area of tidal flats has decreased by 16% over the past 30 years [1, 6, 7]. In particular, the Korean coastal environment has been undergoing rapid changes due to coastal reclamation and development, thus the total area of tidal flats in Korea has decreased by 30-40% compared to the 1980s [8]. Tidal flats are constantly changed by waves, wind, and biological and anthropological effects. Therefore, when considering the physical, biological, geological, and morphological aspects of tidal flats, it is very important to accurately investigate extent and exposure of the tidal flats along with the tide level and the spatiotemporal change of the tidal flat topography [1, 9]. Ground-based point measurements provide information to improve our understanding of complex tidal flat environments on a local scale, despite involving expensive, labor intensive, and time consuming processes. Recently, the enhanced operational stability of unmanned aerial vehicle (UAV) platforms has increased the use of rapid and automated intertidal mapping. The high spatial resolution of UAV images can be very useful in detecting small changes in tidal flats. [PERSON] et al. [10] attempted topographic monitoring over tidal flats using a fixed-wing mapping drone combined with a digital camera and showed high accuracy in the result data. [PERSON] et al. [11] presented a method to detect detailed topographic changes in tidal flats with various ground control point configurations. However, this method requires on-site visits to obtain the data and the operating environment is readily affected by weather conditions, such as extreme wind, rain, and storms. Similar to in situ measurement, UAV platforms are challenging to use for the characterization of large scale tidal flat environments due to their limited flight time and coverage. Several studies have demonstrated that satellite-based remote sensing represents an effective tool for monitoring morphologic change and sedimentary facies distribution over wide tidal flats, on regional and continental scales [9; 12]. Specifically, the Normalized Difference Water Index (NDWI) from Landsat TM/ETM+ data was applied for the large scale intertidal classification and coastline extraction of East Asia [8] and Australia [13]. However, optical remote sensing imageries are always limited by weather conditions such as sunlight and cloud coverage. Synthetic aperture radar (SAR) images have also been applied to tidal flats with less cloud contamination [14], but SARs are readily affected by high speckle noise. The contrast between ocean and land is not always clear on a pixel-by-pixel basis in high resolution SAR images, which makes the waterline extraction of SAR images a challenging problem [15]. Thus, the integration of multitemporal and multiband SAR data can be very useful for the study of tidal flats. For example, [PERSON] et al. [16] used multiband SAR images, including C-band ENVISAT ASAR and L-band ALOS PALSAR, to analyze the characteristics of seasonal changes in reed marches and rice fields. [PERSON] et al. [17] showed that the frequent sampling of the Sentinel constellation helps to overcome the limitations induced by a shortage of images. The combined use of Sentinel-1 and -2 can provide an adequate number of images that covers the whole tidal cycle in a relatively short period. Intertidal topography has been generated through waterline extraction using multitemporal remote sensing data.