# Mapping Surface Flow Velocity of Glaciers at Regional Scale Using a Multiple Sensors Approach
## 1 Introduction  
The shrinking of glaciers and the ice-sheet observed in recent decades result from the current climate change, which is enhanced by anthropogenic sources. These changes have significant impacts in terms of sea level rise (SLR), natural hazards and socio-economic issues related to water resources [1]. Estimates for SLR in recent decades suggest that glacier mass loss (outside the ice-sheets) has accounted for nearly 30% of the total sea level rise between 1993 and 2010 [2]. Furthermore, the disintegration of mountain glaciers in remote areas threatens local populations by limiting the year-round availability of drinkable water but also by increasing the risk of glacial lake outburst floods [3]. Thus, as reported by the International Panel for Climate Change (IPCC), monitoring glacier change has become a major challenge of the 21 st century. It is therefore essential to improve techniques to establish the current state, quantify ongoing changes as well as to project future glacier evolution. The mass balance of a glacier is controlled by the mass gain (i.e., accumulation) and the mass losses (i.e., ablation, calving processes). Ice is transported through the system by glacial flow, which canbe directly affected by changes in climatic conditions (e.g., changes in melt, snowfall, temperature...) making it a powerful indicator of glaciers' response to climate change [4]. In a context of global climate change, it is therefore of general importance to accurately document changes in surface flow velocity of glaciers worldwide. In addition, estimation of ice thickness distribution of mountain glaciers around the globe is essential to provide accurate estimate of water resources and to evaluate the future contribution of glaciers to sea level rise. However, measurements of ice thickness are sparse, timely and expensive: the global Glacier Thickness Database [5] contains direct measurements for only about 4700 of the 215,000 inventoried glaciers [6]. As part of the Ice Thickness Models Intercomparison eXperiment (ITMIX), several modeling methods were tested to map ice thickness distribution of mountain glaciers. This experiment and the related studies have shown that the accuracy of the estimates depends strongly on the quality of the input data, typically the surface flow velocity [7; 8; 9; 10]. Hence, large scale, comprehensive and frequent (e.g., sub-seasonal) mappings of the glacier surface velocity would be needed to accurately estimate ice thickness, but also to understand the variability in glacier dynamics. Nowadays, these speed maps are spatially and temporally scarce and at coarse resolution, which has hampered our understanding of glacier evolution in mountain regions [11; 12]. Specifically, the recent studies at regional scales using the growing archive of optical and radar data have focused on the largest glacier-covered regions [13; 14; 15; 16] with a spatial resolution excluding a large proportion of glaciers that have an area smaller than 5 km\({}^{2}\) and limiting the application of the developed methodologies to regions containing smaller glaciers (e.g., the European Alps or the tropical Andes). In the last few years, we entered a new era of spaceborne land surface observations with the launch of ESA's Sentinel-2 A/B satellites that systematically acquire data with a high temporal frequency (5-day cycle) and almost worldwide. In addition, the higher spatial resolution of Sentinel-2 compared to Landsat 7/8 (10 m versus 15 m) is expected to capture more small glaciers, resulting in more detailed mapping of their surface speed. With this amount of data, we now have the ability to address two important questions: (1) obtain comprehensive coverage of glacierized regions at the mountain range scale; and (2) have a temporal frequency of acquisition dense enough to quantify the changes in glacier dynamics happening on short time scale (weekly to annually).