Abstract
This study evaluates the performance of two fundamentally different approaches to achieve sub-pixel precision of normalised cross-correlation when measuring surface displacements on mass movements from repeat optical images. In the first approach, image intensities are interpolated to a desired sub-pixel resolution using a bi-cubic interpolation scheme prior to the actual displacement matching. In the second approach, the image pairs are correlated at the original image resolution and the peaks of the correlation coefficient surface are then located at the desired sub-pixel resolution using three techniques, namely bi-cubic interpolation, parabola fitting and Gaussian fitting. Both principal approaches are applied to three typical mass movement types: rockglacier creep, glacier flow and land sliding. In addition, the influence of pixel resolution on the accuracies of displacement measurement using image matching is evaluated using repeat images resampled to different spatial resolutions. Our results show that bi-cubic interpolation of image intensity performs best followed by bi-cubic interpolation of the correlation surface. Both Gaussian and parabolic peak locating turn out less accurate. By increasing the spatial resolution (i.e. reducing the ground pixel size) of the matched images by 2 to 16 times using intensity interpolation, 40% to 80% reduction in mean error in reference to the same resolution original image could be achieved. The study also quantifies how the mean error, the random error, the proportion of mismatches and the proportion of undetected movements increase with increasing pixel size (i.e. decreasing spatial resolution) for all of the three mass movement examples investigated.
Highlights
After filtering of the vectors based on the estimated overall image registration error of one pixel, after thresholding of the correlation coefficients (0.65 for the rockglacier, 0.6 for the glacier and 0.45 for the landslide) and after excluding upslope movements, only the remaining vectors presented in the Figs. are considered to be valid and useful as reference
The study contributes to better exploiting the large archives of repeat remotely sensed images that exist over actual or potential Earth surface mass movements, as well as to better meeting the increasing needs to quantify and monitor mass movements, in particular when they are accompanied by adverse effects
The study has in particular evaluated the performance of two different approaches to sub-pixel precision in normalized cross-correlation (NCC) for displacement measurement based on repeat images
Summary
The increasing number of available collections of multi-temporal space-borne, air-borne and terrestrial images, and the improvements in remote sensing and image processing in general significantly enhance the potential for applying matching techniques to detect and quantify Earth surface mass movements from repeat remotely sensed data. These needs and developments call for continued efforts to improve terrain displacement matching methods based on repeat images for a large number of applications in Earth sciences. The LSM has no limitation of precision as the location of the matches can theoretically be determined at any sub-pixel precision
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