# Mapping Atmospheric Exposure of the Intertidal Zone with Sentinel-1 CSAR in Northern Norway
## 4 Discussion  
The method proposed here is similar to the \"water line\" method [28; 29; 30; 31; 50] to map topography in the ITZ. However, instead of mapping the topography by associating single satellite observations to tidal gauge height observations, we mapped the percentage of atmospheric exposure only on the basis of a statistical analysis of temporally consistent long time series of Sentinel-1 radar imagery. The topography is a function of atmospheric exposure parameterized by the tidal range at the specific location and can, therefore, be derived when the tidal range is known. Figure 6 shows that this relationship can be approximated with a linear relationship for atmospheric exposures between 5% and 95%. The advantage of mapping atmospheric exposure is that it is independent of the tidal range and can be mapped without access to tidal gauge measurements. In complex coastal systems with bays, fjords, islands, inlets, etc., the tidal range and phase can vary over short distances because of tidal current dynamics. The \"water line\" method would, therefore, need a dense network of tidal gauges or a tidal model to account for this in such areas. Tidal height errors also increase with the distance to tidal gauge positions due to the tidal wave curvature. The topography is, therefore, difficult to map in remote areas. Furthermore, atmospheric exposure is also a more relevant and essential environmental parameter for biodiversity and species living in the ITZ than the topography. The authors of [27] also used statistical analysis to map the ITZ area in southern China by extracting the highest and lowest water lines from the fifth and 95 th percentiles of S1  
Figure 16: Salmon farm detected as intertidal zone (**left**) and visible in aerial mosaics (© norgeibilder.no, Kartverket, Norge digitalt, Terratec AS). VV backscatter time series. Using the VH cross-polarization in addition to extracting other percentiles as we did in our study could further improve their results. This study showed that water-saturated tidal flats without stones and vegetation that have a smooth, wet surface can be difficult to detect with SAR, and some tidal flats might, therefore, be underestimated. This needs further investigation, and a combination with optical satellite observation, as presented in [49; 50], should improve the detection of the overall ITZ area. Underestimating mudflats seemed also to be the case in [27] compared to results based on optical satellites from [24; 25]. The use of only the VV polarization from S1 and less S1 acquisition in [27] might have further prevented the ITZ area detection. As optical satellite data acquisitions do not sample in a temporally consistent way because of cloud cover, mapping atmospheric exposure or topography with optical data alone would yet require tidal gauge observation or tidal models. In cloud-persistent areas such as Northern Norway, longer periods would also be needed to collect the necessary time series to sample the whole tidal range. On a continental and global scale, [24; 25] even used multi-decadal time series of Landsat data for this purpose. It is clear that our method needs a certain time period to collect enough satellite data to sample the complete tidal range and reduce the SAR-specific speckle noise. Using two 6 month ice-free summer periods, the Tromso Municipality was imaged 243 times, which gave us a solid statistical sampling data base. Test runs using only one June-November period (121 observations) showed nearly identical results at 20 m resolution and only slightly noisier results at 10 min resolution. A comparison with results based on S1 data of the whole year 2019, including winter months, showed only a major difference in fjords that are ice-covered during winter. A seasonality in atmospheric pressure, i.e., higher waters because of more low-pressure systems in Northern Norway during winter, did not have a noticeable impact on the results.