Efficient Automated Glacier Surface Velocity Measurement From Repeat Images Using Multi-Image/Multichip and Null Exclusion Feature Tracking | IEEE Journals & Magazine | IEEE Xplore

Efficient Automated Glacier Surface Velocity Measurement From Repeat Images Using Multi-Image/Multichip and Null Exclusion Feature Tracking


Abstract:

Observations of ice motion are critical for constraining ice sheet mass balance and contribution to sea level rise, as well as predicting future changes. A wealth of imag...Show More

Abstract:

Observations of ice motion are critical for constraining ice sheet mass balance and contribution to sea level rise, as well as predicting future changes. A wealth of imagery now exists for measuring ice motion from space, but existing repeat-image feature-tracking (RIFT) algorithms require the selection of several location- and data-specific parameters and manual data editing and are therefore not efficient for processing large numbers of image pairs for differing regions. Here, we present the multiple-image/multiple-chip RIFT algorithm which does not involve any user-defined local/empirical parameters and has a higher matching success rate than conventional single-image single-chip correlation matching. We also present an efficient method for applying RIFT to null-value striped data, such as the Landsat-7 Enhanced Thematic Mapper Plus. This method offers the potential for fully automated processing of large data sets.
Published in: IEEE Transactions on Geoscience and Remote Sensing ( Volume: 49, Issue: 8, August 2011)
Page(s): 2838 - 2846
Date of Publication: 24 March 2011

ISSN Information:


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