Application of Surface Matching for Improved Measurements of Historic Glacier Volume Change in the Antarctic Peninsula

Climate records show that the Antarctic Peninsula is rapidly warming. Dramatic changes in ice shelf and glacier extent have been recorded over the last few decades. Mapping recent changes in the Antarctic Peninsula is relatively straightforward, as increased amounts of earth observation data become readily available for scientific purposes. However, long term measurements of volumetric changes within the region are rare and less is known of changes which have occurred over the second half of the 20th Century. Nonetheless, historical observations are available in the form of archival aerial stereo-photography. However, extracting information from historical data, i.e. to compare it to recent data, is not trivial, and to-date, this data source remains largely untapped, despite its rich potential. Often such imagery is stored in non-digital format and may have degraded over time. Other problems relate to insufficient metadata or ground control. Typically these difficulties result in poor registration of multi-temporal DEMs, which degrade subsequent measurements of surface change. This is one of the fundamental limitations of accessing archival datasets. In this research a least squares surface matching technique is introduced to overcome these challenges and achieve reliable registration of multi-temporal DEMs. Historical imagery acquired in the 1960s for two Antarctic Peninsula glaciers is processed to extract DEMs, which are subsequently compared to DEMs derived from modern ASTER satellite data and aerial photography. Through the surface matching approach, it is shown that the registration accuracy of the historical and modern-day datasets can be improved significantly. This enables precise quantification of glacier elevation changes on a multi-decadal time scale. Frontal glacier surface lowering of up to 50 m was observed over the last ~4 decades. Results of this study allow a better understanding of historical volumetric glacier changes of the Antarctic Peninsula and provide an efficient and automated method for improved DEM co-registration.