# Comprehensive Annual Ice Sheet Velocity Mapping Using Landsat-8, Sentinel-1, and RADARSAT-2 Data
## 4 Discussion  
### Potential of Landsat-8 for Large Scale Ice Velocity Mapping Compared with Current SAR Missions  
Since 2013, RADARSAT-2, Sentinel-1a and Landsat-8 have acquired large datasets over Greenland and Antarctica. We have processed both types of data sets and generated comparable maps of ice motion. The comparison of radar and optical ice velocity maps show that (i) the individual ice velocity measurements are equivalentbetween Landsat-8 and Sentinel-1; (ii) the precision is comparable for identical repeat cycle; (iii) area-coverage per scene where ice speed is mapped is roughly equivalent; and (iv) the annual mosaic products are similar within the error associated with both sensors.  
As in the case of radar sensors, optical sensors have limitations. We note that a calibration of the Landsat-8 offsets is necessary to ensure accurate ice velocity measurement (Figure 1). Small inaccuracy in the geolocation of the Landsat-8 (\(\pm\)6 m) images [28] can generate errors in speed up to 137 m/year for 16-day cycle. As the geolocation improves, this problem might be alleviated, especially if more accurate DEMs of Greenland and Antarctica become available and are used for geocoding. In that regard, it would be important to archive the level 0 image data, i.e., without geocoding, so the image geolocation and ortho-rectification can be improved in the future.  
Figure 8: Distribution of the difference between the ice velocity from ENVEO’s ice velocity [19] and the mosaics (this study) made from Landsat (**Left**) and Sentinel-1 (**Right**) for year 2014–2015 (**Top**) and year 2015–2016 (**Bottom**).  
Solar illumination is another limitation for optical data compared to SAR data. Figure 5b shows that, in polar regions, acquisitions limited to the summer season make it impossible to track the entire seasonal cycle in speed of Greenland glaciers. In Antarctica, we find that the mean correlation for a single Landsat scene is about 33%, mostly due to cloud cover, whereas SAR shows a correlation of 42%. We note that SAR decorrelation is often located in the same geographic region, i.e., caused by surface climate, whereas Landsat-8 decorrelation is mostly due to clouds and hence varies spatially. Given the same revisit time, SAR C-band velocity tracking is more precise than optical (Figure 7).  
One advantage of Landsat-8 comes from the large amount data acquired during the past years. It is reasonable to expect that SAR sensors would provide comparable if not superior quality data with the same rate of acquisition. It was also surprising to find out that Landsat-8 correlates even with 1-year time separation [21]. We have less experience doing this with SAR because it requires a good orbit control (small baselines) [40] over a long time and most SAR sensors have not tried to do so, but given proper baseline control the same success could be achieved with SAR sensors.  
These results demonstrate that the quality of the products generated from optical satellite sensors is comparable to that obtained with SAR sensors (Figures 2-4). Cloud cover that limits spatial coverage with optical sensors is no longer a limiting factor for annual mapping due to the dense temporal coverage. In addition, optical images are simpler and faster to process.