By Topic

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

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Yushin Ahn ; Byrd Polar Res. Center, Ohio State Univ., Columbus, OH, USA ; Howat, I.M.

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:

Geoscience and Remote Sensing, IEEE Transactions on  (Volume:49 ,  Issue: 8 )