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Automated Image Registration for Hydrologic Change Detection in the Lake-Rich Arctic

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3 Author(s)
Yongwei Sheng ; Dept. of Geogr., Univ. of California at Los Angeles, Los Angeles, CA ; Shah, C.A. ; Smith, L.C.

Multitemporal remote sensing provides a unique tool to track lake dynamics at the pan-Arctic scale but requires precise registration of thousands of satellite images. This is a challenging task owing to a dearth of stable features to be used as tie points [(TPs), i.e., control points] in the dynamic landscapes. This letter develops an automated method to precisely register images in the lake-rich Arctic. The core premise of the method is that the centers of lakes are generally stable even if their shorelines are not. The proposed procedures first extract lakes in multitemporal satellite images, derive lake centroids and match them between images, and then use the centroids of stable lakes as TPs for image registration. The results show that this approach can achieve subpixel registration accuracy, outcompeting the conventional manual methods in both efficiency and accuracy. The proposed method is fully automated and represents a feasible way to register images for lake change detection at the pan-Arctic scale.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:5 ,  Issue: 3 )