Velocidades superficiales del glaciar Upsala, Andes Patagónicos Sur, mediante el uso de correlación cruzada en imágenes satelitales: periodo 2013-2014.

M. Gabriela Lenzano,Luis Lenzano,Silvana Moragues,Daniel Falaschi,Andrés Lo Vecchio

doi:10.5027/andgeov45n1-3034

Abstract

In this study we present surface velocities estimation for the Upsala glacier catchment, South Patagonian Ice Field (SPI) during the summer season of years 2013 (January-March) and 2014 (March-April), including the Bertacchi, Cono, and Murallón tributaries using satellite images from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). The Cross-Correlation method was applied by COSI-Corr technique with sub-pixel accuracy. In general, it should be noted that the SPI glaciers, and Upsala glacier in particular, are fast-flowing ice bodies, which makes the technique works properly. Results of surface velocities estimation ranged from 0.22 to 2.93 md-1 for January-March 2013 and 0.12 to 5.8 md-1 for March-April 2014. In summary, COSI-Corr can achieved accurate and reliable results for glacier displacements and surface velocities estimation, also contributing in the better knowledge of the velocities change processes in time, taking into account Upsala is one of the most dynamic temperate glaciers of the SPI.

Highlights

Glaciers worldwide stand out as one of the best climate change indicators, such as the fluctuations like a function of height (Oerlemans, 2005), and the calving glaciers are sensitive due to the loss of mass in the terminus (Badino and Romeo, 2005)
In this study we present surface velocities estimation for the Upsala glacier catchment, South Patagonian Ice Field (SPI) during the summer season of years 2013 (January-March) and 2014 (March-April), including the Bertacchi, Cono, and Murallón tributaries using satellite images from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)
Remote sensing techniques have offered in the last decades tools for glacier monitoring thanks to the availability, of satellite imagery relying in both optical (Kääb, 2002; Berthier et al, 2005; Quincey and Glasser, 2009) and Synthetic Aperture Radar (SAR) images (Rignot and Kanagaratnam, 2006; Luckman et al, 2007), amongst others

Summary

Introduction

Glaciers worldwide stand out as one of the best climate change indicators, such as the fluctuations like a function of height (Oerlemans, 2005), and the calving glaciers are sensitive due to the loss of mass in the terminus (Badino and Romeo, 2005). Remote sensing techniques have offered in the last decades tools for glacier monitoring thanks to the availability, of satellite imagery relying in both optical (Kääb, 2002; Berthier et al, 2005; Quincey and Glasser, 2009) and Synthetic Aperture Radar (SAR) images (Rignot and Kanagaratnam, 2006; Luckman et al, 2007), amongst others. Three methods are commonly employed to derive glacier-surface velocities: interferometry of SAR imagery, SAR tracking techniques, and cross correlation of optical satellite images (Scherler et al, 2008). Cross-correlation of satellite imagery has been largely utilized for mapping and monitoring glacier velocities in several mountain regions around the globe (Taylor et al, 2008; Heid and Kaab, 2011; Heid, 2011; Herman et al, 2011)

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Conclusion