Long-term mass-balance monitoring and evolution of ice in caves through structure from motion–multi-view stereo and ground-penetrating radar techniques

This study investigates the application of a terrestrial structure from motionmulti-view stereo (SfM-MVS) approach combined with ground-penetrating radar (GPR) surveys for monitoring the surface topographic change of two permanent ice deposits in caves located in the Julian Alps (south-eastern Europ...

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Veröffentlicht in:Progress in physical geography 2022-06, Vol.46 (3), p.422-440
Hauptverfasser: Securo, Andrea, Forte, Emanuele, Martinucci, Davide, Pillon, Simone, Colucci, Renato R
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Sprache:eng
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Zusammenfassung:This study investigates the application of a terrestrial structure from motionmulti-view stereo (SfM-MVS) approach combined with ground-penetrating radar (GPR) surveys for monitoring the surface topographic change of two permanent ice deposits in caves located in the Julian Alps (south-eastern European Alps). This method allows accurate calculation of both seasonal and annual mass balance, estimating the amount of ice inside caves. The ground-based SfM approach represents a low-cost workflow with very limited logistical problems of transportation and human resources and a fast acquisition time, all key factors in such extreme environments. Under optimal conditions, SfM-MVS allows sub-centimetric resolution results, comparable to more expensive and logistically demanding surveys such as terrestrial laser scanning (TLS). Fourteen SfM acquisitions were made between the 2017–2020 ablation seasons (i.e. July–October) while 2 GPR surveys were acquired in 2012. The obtained dense point clouds and digital terrain models (DTMs) made possible a reliable calculation of topographic changes and mass balance rates during the analysed period. The integration of SfM-MVS products with GPR surveys provided comprehensive imaging of the ice thickness and the total ice volume present in each of the caves, proving to be a reliable, low cost and multipurpose methodology ideal for long-term monitoring.
ISSN:0309-1333
1477-0296
DOI:10.1177/03091333211065123