The airborne lidar with two segmented field-of-view (FOV) receivers was used to detect the subsurface scattering layers. Significant differences were observed in the waveforms from one channel with small FOV of 6 mrad and the other channel with larger FOV of 40-6 mrad. The larger FOV of 40-6 mrad was to provide a larger dynamic range for the deep-water signal detection. A small-angle approximation based Lidar waveform simulation model was developed, and found that these differences are owing to the narrow beam divergence of laser pulse of only 0.3 mrad. Next, an algorithm, which incorporates a waveform-decomposition technique and a lowpass digital differentiator, was then used to detect the scattering layers from both small- and large- FOV channels. The observation of scattering layer along the coastal region of Sanya Bay of China shows that, more than three thin scattering layers can be found in the same water column close to the coasts, and the maximum depth of the scattering layer detected by the large FOV Channel can be up to 35m, and internal waves can be detected from spatial distributions of scattering layer. It can be found that the airborne bathymetry lidar with segmented field-of-view receivers can also be a great tool for the subsurface scattering layer detection.
In order to detect both precise peaks of the surface and the bottom, in this study, we separated the sea waveforms into three sub-types, such as extreme shallow-water, shallow-water, deep-water after the land and sea waveform classification. Then an algorithm based on FFT was devised and the results were tested on actual airborne LiDAR measurements from a case study.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.