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The volume variation of a glacier is the actual indicator of long term and short term evolution of the glacier behaviour. In order to assess the volume evolution of the Austre Lovénbreen (79° N) over the last 47 years, we used multiple historical datasets, complemented with our high density GPS tracks acquired in 2007 and 2010. The improved altitude resolution of recent measurement techniques, including phase corrected GPS and LiDAR, reduces the time interval between datasets used for volume subtraction in order to compute the mass balance. We estimate the sub-metre elevation accuracy of most recent measurement techniques to be sufficient to record ice thickness evolutions occurring over a 3 year duration at polar latitudes. The systematic discrepancy between ablation stake measurements and DEM analysis, widely reported in the literature as well as in the current study, yields new questions concerning the similarity and relationship between these two measurement methods. The use of Digital Elevation Model (DEM) has been an attractive alternative measurement technique to estimate glacier area and volume evolution over time with respect to the classical in situ measurement techniques based on ablation stakes. With the availability of historical datasets, whether from ground based maps, aerial photography or satellite data acquisition, such a glacier volume estimate strategy allows for the extension of the analysis duration beyond the current research programmes. Furthermore, these methods do provide a continuous spatial coverage defined by its cell size whereas interpolations based on a limited number of stakes display large spatial uncertainties. In this document, we focus on estimating the altitude accuracy of various datasets acquired between 1962 and 2010, using various techniques ranging from topographic maps to dual frequency skidoo-tracked GPS receivers and the classical aerial and satellite photogrammetric techniques.

Due to poor weather conditions including common heavy cloud cover at polar latitudes, daily satellite imaging is not always accessible. Nevertheless, fast events including heavy rainfall inducing floods appear as significant in the ice and snow budget while being ignored by satellite based studies since the slower sampling rate is unable to observe such short phenomena. We complement satellite imagery with a set of ground based autonomous automated high resolution digital cameras. The recorded oblique views, acquired at a rate of 3 images per day, are processed for comparison with the spaceborne imagery. Delaunay triangulation based mapping using a dense set of reference points provides the means for an accurate projection by applying a rubber sheeting algorithm. The measurement strategy of identifying binary information of ice and snow cover is illustrated through the example of a particular flood event. We observe a snow cover evolution from 100% to 44.5% and back to 100% over a period of 2 weeks.

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