期刊
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
卷 56, 期 3, 页码 1598-1614出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2017.2765601
关键词
Image correlation; iterative closest point (ICP); light detection and ranging (lidar); near-field deformation; structure from motion (SfM)
We present an investigation into different approaches for high-resolution mapping of near-field surface displacement for strike-slip earthquakes. Airborne laser scanning (ALS) and optical imagery are two common sources of earth observation data available to geoscientists for earthquake documentation and studies. Optical image correlation and point cloud differencing techniques are among the most widely used methods for retrieving displacement signals in the near field. We compare the performances of these techniques for estimating near-field deformation using pre and postevent high-resolution ALS and airborne imagery of the August 24, 2014 Mw 6.0 Napa, California earthquake. Estimates of deformation agree with field observations within a decimeter, at the expected accuracy level of the data. We show that the correlation of intensity images from ALS data can unveil the near-field deformation successfully and outperforms optical image correlation in vegetated areas as well as in the absence of geodetic markers (man-made structures). Furthermore, we illustrate that the point clouds generated with structure from motion perform comparably to ALS point clouds for retrieving the displacement signal in unvegetated areas. Overall, we conclude that ALS data are generally better than imagery for estimating near-field deformation regardless of the estimation methodology and that the iterative closest point algorithm was more effective at recovering the displacement signal.
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