High-resolution debris cover mapping using UAV-derived thermal imagery: limits and opportunities

Abstract. Debris-covered glaciers are widespread in high mountain ranges on Earth. However, the dynamic evolution of debris-covered glacier surfaces is not well understood, in part due to difficulties of mapping debris cover thickness in high spatiotemporal resolution. In this study we present land surface temperatures (LST) and its diurnal variability measured from an unpiloted aerial vehicle (UAV) at high spatial resolution. We test two common approaches to derive debris thickness maps by (1) solving a surface energy balance model (SEBM) in conjunction with meteorological reanalysis data and (2) least squares regression of a rational curve using debris thickness field measurements. In addition, we take advantage of the measured diurnal temperature cycle and estimate the rate of change of heat storage within the debris cover. Both approaches resulted in debris thickness estimates with a RMSE of 6 to 8 cm between observed and modelled debris thicknesses, depending on the time of the day. The diurnal variability of the LST controls the relationship between LST and debris thickness and the non-linearity increases with increasing LST. During the warming phase of the debris cover, the LST depends strongly on the terrain aspect, rendering clear-sky morning flights that do not account for aspect-effects problematic. Our sensitivity analysis of various parameters in the SEBM highlights the relevance of the effective thermal conductivity when LST is high. Residual and variable bias of UAV-derived LSTs during a flight require calibration, which we achieve with bare ice surfaces. The model performance would benefit from more accurate LST measurements, which are difficult to achieve with uncooled sensors.