Nonparametric Regression for Estimation of Spatiotemporal Mountain Glacier Retreat From Satellite Images

Historical variations in the extent of mountain glaciers give insight into natural and forced changes of these bellwethers of the climate. Because of the limited number of ground observations relative to the number of glaciers, it is useful to develop techniques that permit for the monitoring of glacier systems using satellite imagery. Here, we propose a new approach for identifying the glacier terminus over time from Landsat images. The proposed method permits for detecting inflection points in multispectral satellite imagery taken along a glacier´s flow path in order to identify candidate terminus locations. A gated tracking algorithm is then applied to identify the best candidate for the glacier terminus location through time. Finally, the long-term trend of the terminus position is estimated with uncertainty bounds. This is achieved by applying nonparametric regression to the temporal sequence of estimated terminus locations. The method is shown to give results consistent with ground-based observations for the Franz Josef and Gorner glaciers and is further applied to estimate the retreat of Viedma, a glacier with no available ground measurements.