# A Study of Landfast Ice with Sentinel-1 Repeat-Pass Interferometry over the Baltic Sea
## 5 Conclusions  
This study is the first one that uses Sentinel-1 synthetic aperture radar interferometry for studying the landfast ice mechanics with the long temporal baseline (12 days) over the Baltic Sea. One case from February 2015 is examined in detail. An area nearly 400 km\({}^{2}\) was found with well-defined fringes and total change in the LOS of 40 cm. A small part of displacements was possibly produced by sea level tilt, currents, and thermal expansion, but the main factor was compression of the drift ice driven by the southwest winds on the boundary of landfast ice.  
To maintain a high coherence over the landfast ice, a short temporal baseline is needed. On the other hand, we need high coherence results by long temporal baseline for separating the fast ice from the drift ice. Detecting long-term trends in a fast ice displacement map is another advantage of long temporal baseline. In this study, for the first time, we detected these long-term trends on the Baltic fast ice. Lines with low coherence and backscattering were found over the fast ice that could fracture due to the landfast ice displacement or ice routes.  
Small scale fast ice changes was probably affected by weather parameters and other phenomena such as snowfall and rainfall, changing air temperature, and ice growth/melting. This indicates that better ground truth data are needed for future studies of the InSAR over the fast ice.  
Sentinel-1 satellite has some advantages compared to previous missions, including data accessibility and geographical coverage. Additional benefit is given by free software such as SNAP for easy data processing. Sentinel-1 uses TOPSAR mode. This technique has a uniform SNR and distributed target ambiguity ratio (DTAR) in comparison with other previous satellites. Previous missions used that Scans SAR mode for capturing data [15].  
InSAR displacement maps can be used to gain more knowledge about the processes of fast ice development and deformation. This information is useful in making risk maps for cracking and the opening of leads, needed by the local communities. To better understand the fast ice mechanisms, interferograms from both ascending and descending orbits would be needed to solve two movement components [24]. Another exciting possibility is investigating six-day interferometric data using both Sentinel-1A and Sentinel-1B acquisitions to better understand the potential of Copernicus data in sea ice monitoring applications.  
The authors would like to thank Copernicus program for Sentinel data and ESA for SNAP software. We are also grateful to Mr. [PERSON] for help with the surface truth data and Mr. [PERSON] who was helpful and offered invaluable assistance and guidance.  
[PERSON] and [PERSON] designed the study. [PERSON] was primarily responsible for the experimental analysis. [PERSON], [PERSON], [PERSON] and [PERSON] contributed to the results interpretation and discussion. [PERSON] and [PERSON] wrote the manuscript with contributions and revisions from all authors.  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} ALOS & Japanese Advanced Land Observing Satellite \\ DEM & Digital Elevation Model \\ DTAR & Distributed Target Ambiguity Ratio \\ EET & Eastern European Time \\ ESA & European Space Agency \\ EW & Extra Wide Swath \\ FIS & Finnish Ice Service \\ InSAR & Interferometric Synthetic Aperture Radar \\ IW & Interferometric Wide \\ LOS & Line Of Sight \\ NESZ & Maximum Noise Equivalent Sigma Zero \\ QGIS & Quantum Geographic Information System \\ SAR & Synthetic Aperture Radar \\ SM & Stripmap \\ SLC & Single Look Complex \\ SNAP & SeNtinel's Application Platform \\ SNAPHU & Statistical-cost Network-flow Algorithm for PHase Unwrapping \\ SNR & Signal to noise Ratio \\ TOPSAR & Terrain Observation with Progressive Scans SAR \\ WV & Wave \\ \end{tabular}