An alternative photogrammetry approach, using annual ASTER image pairs for the period 2000-2013, has the potential to identify the temporal variability of dynamic processes relating to mass balance. The implementation of a single multi-temporal image block allows multi temporal image registration to be implemented through the use of a single bundle block adjustment using 32 Ground Control Points (GCP). It allows the simultaneous computing of all image geometric models and relates them all to one another. Additionally the resulting surface elevation models for each epoch will exhibit a better relative accuracy and a more consistency between years allow a stronger signal of elevation change to be interpreted. The relatively coarse spatial resolution at which ASTER images are acquired is limited and a desired spatial resolution for detecting change is achieved over such a short time period. Triangulation assessment revealed the sub-pixel accuracy of the resulting model with 1/6 pixel (2-3m) plainmetrically and 1/3 pixel (4-5m) in elevation and the independent assessment of GCPs using a leave one out cross validation produced similar results. These findings indicate this different approach to processing images is a useful technique for resolving the spatial resolution required to detect annual surface elevation changes.