Mapping Surface Flow Velocity of Glaciers at Regional Scale Using a Multiple Sensors Approach

Abstract

We explore and compare the capabilities and limitations of different optical sensors (Sentinel-2/ESA, Landsat 7/8/USGS, Venµs/CNES-ISA, Pléiades/AirbusD&S and Planet Labs images) for mapping the surface speeds of mountain glaciers on a regional scale. We present here our automated workflow designed to download data from institutional or commercial servers, prepare images, launch the feature tracking algorithm, calibrate glacier surface speeds, and our post-processing treatment to obtain filtered and time-averaged velocity maps. We applied our methodology to three regions: (1) the European alps; (2) the Peruvian Cordillera Blanca; and (3) the Southern Alps of New Zealand for years 2017 and 2018 and quantified ice velocity for every possible repeat cycle from few days up to 400 days. For these regions, we demonstrate the ability of our processing chain to derive precise time-averaged ice flow maps. The statistical analysis of the results provided by each individual repeat cycles shows that velocity mapping from Sentinel-2 is about twice more precise than that from Landsat 7/8. If Sentinel-2 captures more details than Landsat, some of the smallest glaciers (<250 m wide) remain challenging. Given the estimated precision for Sentinel-2, we also conclude that velocity fluctuations of the order of 10 m/yr can only be captured with repeat cycles longer than 60 days. Comparing Sentinel-2 with Pléiades, Planet and Venµs imagery, we finally highlight the advantages of high-resolution sensors to map glacier surface speed with finer details in space and time.

Reversed Surface-Mass-Balance Gradients on Himalayan Debris-Covered Glaciers Inferred from Remote Sensing

“…Additionally, it is difficult to resolve accurately the SMB gradients of small glaciers <~10 km in length, due to poorer signal-noise relationships and a lack of sufficient data points to accurately predict SMB gradients. The coverage of high-altitude areas and smaller glaciers can be improved in the future with the improvement of optical-satellite-imagery resolution [53] and the enhancement of feature-tracking algorithms.…”

Greenland Ice Sheet solid ice discharge from 1986 through March 2020

“…The mass of the Greenland Ice Sheet is decreasing (e.g., Fettweis et al, 2017;van den Broeke et al, 2017;Wiese et al, 2016;Khan et al, 2016). Most ice sheet mass loss -as ice-berg discharge, submarine melting, and meltwater runoffenters the fjords and coastal seas, and therefore ice sheet mass loss directly contributes to sea-level rise (WCRP Global Sea Level Budget Group, 2018;Moon et al, 2018;Nerem et al, 2018;Chen et al, 2017). Greenland's total ice loss can be estimated through a variety of independent methods, for example direct mass change estimates from GRACE (Wiese et al, 2016), or by using satellite altimetry to estimate surface elevation change, which is then converted into mass change (using a firn model, e.g., Khan et al, 2016).…”

“…However, partitioning the mass loss between ice discharge (D) and surface mass balance (SMB) remains challenging (see Rignot et al, 2008;Enderlin et al, 2014). Correctly assessing mass loss, as well as the attribution of this loss (SMB or D), is critical to understanding the process-level response of the Greenland Ice Sheet to climate change and thus improving models of future ice sheet changes and associated sea-level rise (Moon et al, 2018).…”

review of Glacier Image Velocimetry

“…The temporal sampling is a bit counter intuitive, as this is an opposite direction to the workflow of [Millan et al 2019]. Where they found the time-span needs to be of sufficient size, in order to be of most use.…”