# Antarctic Surface Ice Velocity Retrieval from MODIS-Based Mosaic of Antarctica (MOA)
Since the NASA Making Earth System Data Records for Use in Research Environments (MEASUREs) InSAR-Based Antarctica Ice Velocity Map revealed a complex flow pattern from the coastal region to the deep interior in the Antarctic for the first time [18; 19], ice surface velocity mapping at the regional to continental scale has progressed rapidly [20], not only in the Antarctic updated yearly [21], but also in Greenland Ice Sheet [22; 23], Central Asia [24], Cirucum-Arctic [25], Alaska [26], Canada [27], and Patagonia [28]. The improvements in contemporary remote sensing technology, either in optical or synthetic aperture radar (SAR), provided by new-launched earth observation satellites or constellations, such as Radarsat-2 [29], ALOS-PALSAR [27], TerraSAR-X and TanDEM-X [30], Landsat-8 [31; 32], Sentinel-1 [22], and Sentinel-2 [33], make these projects possible. Based on a quick re-visit of, and the high-quality imagery from, these integrated missions, some of them have already been systematized into near real-time operational retrieval and distribution portals to provide insights to both cryogenic research community and the public [34], taking Global Land Ice Velocity Extraction from Landsat-8 (GoLIVE-V1), for example. As an excellent data source commonly used in various cryospheric research fields, the Moderate Resolution Imaging Spectrophotometer (MODIS) demonstrates its capabilities in surface melting detection [35], water vapor estimation [36], digital elevation model calibration [37], etc. Perhaps as the result of the coarse spatial resolution, however, MODIS's potentiality to track ice sheet surface motion is seldom implemented. [PERSON] et al. investigated Larsen-C ice shelf's velocity from 2002 to 2009 via MODIS, and the difference from Landsat's retrieval was within 30 m\(\cdot\)a\({}^{-1}\)[38]. Coincidentally, the Larsen-C ice shelf was chosen to be the study area again by [PERSON] et al. [39], and it was found to have accelerated continually since 2000. In fact, [PERSON] et al. [40] and [PERSON] et al. [41] have exploited Declassified Intelligence Satellite Photography (DISP) images acquired during the Cold War period to trace back to earlier dynamic hints of the Larsen-C ice shelf. Most images that have been used to derive velocity in glaciology have been high or medium spatial resolution images, such as orthorectified airborne photos [42], SPOT [43], Landsat [44], ASTER [45], or Sentinel-2 [33]. In addition, the technology innovation makes commercial cubesat constellation [46] and unmanned aerial vehicles (UAVs) [47] as the efficient sensors to monitor glacier behavior. Low-resolution images cover large section in one scene, making them suitable for investigating the velocity of large areas such as Antarctic ice shelves [48]. Therefore, we speculate that MODIS might underperform in the glacier flow's velocity retrieval, since in most cases researchers have better choices. While MODIS enjoys a shorter re-visit time and a wider swath in the high latitude region, the probability of cloud-free scenes increases tremendously, which means a continental mosaic can be compiled in a relatively shorter time slot. [PERSON] et al. [49] has already tested MODIS-based Mosaic of Antarctic (MOA)'s performance in retrieving surface velocity of Ross Ice Shelves, the result of which provides external forcing for the long-term dynamic diffusion ice sheet model. However, regarding the basic tracking techniques, it inevitably yields gross errors in the primitive displacement field [50], especially where high variation dominates or surface melting and snow events transform former features. To enhance the primitive output but avoid laborious human sorting out, additional constraints are needed, such as a crude local statistics filter [51] or a physical assimilation mechanism [52].