Abstract

High resolution satellite images with improved spatial and temporal resolution provide unprecedented opportunities to monitor Earth Surface changes in 2D and 3D due, for example, to earthquakes, sand dune migration, ice flow, or landslides. The volume of imagery available for such measurements is rapidly growing but the exploitation of these data is challenging due to the various sources of geometric distortions of the satellite imagery. Here we propose a new approach to extract high-quality surface displacement in 3D based on the correlation of multi-date and multi-platform high resolution optical imagery. We additionally show that when a large enough volume of data is available, it is possible to separate the deformation signal from the artifacts due to the satellite jitter and misalignment of the CCDs, which, together with topographic artifacts, are the main source of noise in the measurements. Our method makes use of a reference DEM, but the outcome is independent of the characteristics of the chosen DEM. We use the case-example of the ground deformation caused by the Ridgecrest earthquake sequence to assess the performance of our proposed approach. We show that it outperforms the more standard approach which combines 2-D correlation and DEM differencing. With our technique, we were able to generate high quality measurements of coseismic ground displacement with GSD of 2.4 m, and uncertainties at the 90% confidence level on the NS, EW and vertical displacement measurements of 0.6 m, 0.7 m, and 0.6 m respectively.

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