Detecting the equilibrium‐line altitudes of New Zealand glaciers using ASTER satellite images

Abstract

The glaciers of the Southern Alps of New Zealand play an important role in understanding regional and global patterns of climate change. They constitute the third largest ice mass in the Southern Hemisphere after Antarctica and South America, and present unique glaciological features in the region: high sensitivity, high input-output systems that represent the temperate, maritime end of glacier process-behaviour continuum. Since 1977 equilibrium-line altitudes (ELA) of 48 New Zealand index glaciers have been surveyed using oblique aerial photographs as a low-cost proxy for monitoring glacier mass balance. Although this method yields good results, it is location-specific. The use of synoptic high resolution satellite imagery can potentially maximise opportunities to get a wider picture of glacier response to climate variability throughout the New Zealand Southern Alps. Hence, our objective was to investigate how well ELAs detected from 15 m ASTER satellite imagery compare with reference ELAs obtained from aerial photographs taken approximately at the same time, and thus determine whether this imagery could in the future provide a more comprehensive view of glacier wellbeing and trends throughout the Southern Alps. End-of-summer ASTER images were selected and orthorectified. Glaciers were extracted, and ice and snow patterns were classified, using supervised classification of principal components. ELAs were digitised and projected over a digital elevation model. The comparison of ELAs gave a mean height departure of 61 ± 55 m, or 14.4 ± 13.4% expressed relative to the glacier elevation range. We conclude that ASTER data could extend ELAs estimated by G08007; Online publication date 20 August 2009 Received 25 February 2008 accepted 11 July 2009 the current snowline program across the whole Southern Alps. However, small and steep glaciers with complex shapes generate large errors (dominant in the New Zealand context), and thus we suggest that only the largest glaciers can be monitored reliably. ASTER imagery cannot easily replace the annual aerial surveys, mainly because of the difficulty in obtaining the appropriate imagery. The short temporal window, high percentage of cloud cover within the area, and the potential for early unseasonable snowfall are significant limitations to the use of ASTER imagery, without mentioning the recent deterioration of the shortwave infrared ASTER instrument.

Annual ice volume changes 1976–2008 for the New Zealand Southern Alps

“…The ELA measurement programme for New Zealand enables sampling of ELA proxies of a substantial mountain system at the cost of less than 2 days per year of aircraft flight time (Willsman et al, 2010). Alternatively, Mathieu et al (2009) show how the ELA of New Zealand glaciers can be detected using ASTER satellite images. Although considerable variations occur among glaciers in any given year, there is a high degree of reliability for estimating changes across the whole of the Southern Alps when the spatially average ELA i values are considered.…”

Changes in the southeast Vatnajökull ice cap, Iceland, between ~ 1890 and 2010

“…Satellite data have been used to estimate the ELA by this approximation in remote regions and where mass balance is not measured (e.g. Barcaza et al, 2009;Jiskoot et al, 2009;Mathieu et al, 2009;Mernild et al, 2013;Rabatel et al, 2013;Shea et al, 2013). Since limited mass balance measurements exist for the outlet glaciers of this study (Fig.…”

Decadal Scale Changes in Glacier Area in the Hohe Tauern National Park (Austria) Determined by Object-Based Image Analysis

“…Care needs to be taken when interpreting snowlines mapped from optical imagery and interpreting them as a proxy for ELA. The mapped snowline is highly affected by the image acquisition date, seasonal snowfalls and shadow [15,58]. It is therefore of great importance that the satellite acquisition occurs as close as possible to the end of the ablation season in order for multiple images to be comparable.…”

“…Band ratios and spectral indices that use the NIR and SWIR spectral bands, such as the Normalized Difference Snow Index (NDSI), are therefore well suited for semi-automatic mapping of clean ice, and have been used extensively in the European Alps [4,13,14]. Clean ice reflects 25%-35% less visible radiation than fresh snow, thereby allowing the end-of-season snowline or transient snowline (TSL) to be mapped [15]. also used for comparison.…”