Masked Correlation for Improvement of 2D Glacier Motion Estimation Based on Terrasar-x Imagery

Abstract. In this paper, the impacts of the non-glacier information in the template window used in cross-correlation calculation for 2D motion estimation of glaciers are discussed and illustrated by the example of the Taku glacier, which is the biggest glacier in the Juneau Icefield, Alaska. For this, the glacier motion maps are extracted by the traditional normalized cross-correlation technique and the masked cross-correlation method, which uses a manually generated binary mask to threshold the non-glacier pixels, based on geocoded high resolution TerraSAR-X images. Based on the comparison of the different results, it was found that without the disturbing information (e.g., mountain, water) the accuracy of the cross-correlation of sequential patches in masked cross-correlation method is improved and the estimation results are much more reasonable, which respect the law that glacier flows like a river with higher velocity in the middle and than that in the sides.