| dc.description.abstract |
Coastal digital elevation model (DEM) is important to map the spatial distribution of marine organisms, monitor changes of seafloor morphology, and produce accurate orthorectified images. There are different approaches for
bathymetry mapping. For example, sonar and airborne bathymetric Lidar have high accuracy, but both face difficulties on monitoring inaccessible and controversial area. On the other hand, satellite imagery does not have this limitation. The spectral information in satellite imagery can be helpful for retrieving coastal DEM. However, this approach requires a good quality of
training data. Therefore, digital photogrammetry approaches are more preferable as they can measure accurate bathymetry without the training data requirement.
This research first uses an initial DEM to generate two orthorectified images for image matching. If the DEM is accurate, these two orthorectified images should be very similar. However, if parallaxes happen between the orthorectified images, we assume they are caused by the incorrectness of the DEM. As the traditional approaches often use the exterior orientation parameters (EOPs) of images to estimate elevation corrections, EOPs may not be available for every satellite images nowadays. Hence, this research estimates the elevation corrections from parallaxes by using the convergence angle, bisector angle, and asymmetry angle of the stereo-pair.
In general, the proposed method comprises four main steps: (1)pre-processing, (2) elevation correction, (3) DEM reconstruction, and (4) refraction correction. First of all, an initial DEM is applied to produce orthorectified images. In order to increase the performance for image matching, we only match the features extracted from the master image. After calculating parallaxes, we can estimate the elevation corrections and iterate the process using image pyramids. Finally, because of the refraction effect, the refraction correction is necessary to produce the final bathymetry DEM.
We have examined the proposed solution on the Dongsha Atoll in the South China Sea. By comparing with a DEM derived from Lidar, we have the following observations: (1) For the accuracy of matched points, pan-sharpened image has better performance on the shallow water region, which is about 0.52 meters. (2) For the accuracy of DEM, green bend images can achieve more match points on the deeper water region, which result in a more accurate (i.e., 1.15 meters) DEM. (3) Since underwater features are less obvious, small target window size (i.e., less than 31 × 31) would result in wrong matches. (4) In terms of the correlation coefficient threshold, as the Green band has good water penetration performance, there were no significant difference when using different thresholds (i.e., 0.6, 0.7, 0.8). | en_US |