Experimental evaluation of an airborne depth-sounding lidar

Steinvall, Ove; Koppari, Kurt R.; Karlsson, Ulf C. M.

doi:10.1117/12.138514

Cited by 3 publications

(2 citation statements)

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“…The value of the diffuse attenuation coefficient was given in the article as K = 0.1 m −1 , which indicates clear water. Steinvall et al [25] reported a dept bias for which they had no explanation, although they had made a correction to the depth bias as suggested by Guenther [2]. Fig.…”

Section: B Interpretation Of Depth Bias In Context Of Group Velocitymentioning

confidence: 99%

Depth Measurement Bias in Pulsed Airborne Laser Hydrography Induced by Chromatic Dispersion

Schwarz

Pfeifer

Pfennigbauer

et al. 2021

IEEE Geosci. Remote Sensing Lett.

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In contrast to topographic laser scanning, laser hydrography must take into account the presence of two media. A pulsed laser beam, which enters the water from the air at an oblique angle, is refracted at the air-water boundary in the direction of the plumb line. This change of direction described by Snellius' law is caused by a slower speed of the light wave in the water, the phase velocity. Light scattering caused by turbidity gives rise to further deviations from the straight path. Together, the slower speed and the turbidity induced path extension cause a longer pulse round trip time in water than in air. For an accurate measurement it is important to correct this propagation time extension. It is common practice to assume the phase velocity as the velocity for the laser pulses in water. In a dispersive medium, however, the phase velocity is only an approximation of the velocity of a pulse. In media with chromatic dispersion, the pulses propagate with a different velocity, the group velocity. In water, using the group velocity instead of the phase velocity reduces the range dependent bias of the depth measurement at a laser wavelength of 532 nm by more than 1.5%. We present an easy to perform experiment which shows that the group velocity differs so much from the phase velocity that this difference should be taken into account. We further discuss the use of group velocity to explain the depth bias using examples from the literature.

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Section: B Interpretation Of Depth Bias In Context Of Group Velocitymentioning

confidence: 99%

Depth Measurement Bias in Pulsed Airborne Laser Hydrography Induced by Chromatic Dispersion

Schwarz

Pfeifer

Pfennigbauer

et al. 2021

IEEE Geosci. Remote Sensing Lett.

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“…The waveform-calculated system attenuation coefficient K sys is related not only to K d but also to ALB parameters, such as field of view (FOV) [11,21,22]. If the receiver FOV is sufficient, then K sys approaches K d [22][23][24]. In our study, we assumed that the FOV of the Coastal Zone Mapping and Imaging LiDAR (CZMIL) was large enough to collect all the returning energy to the receiver unit, and K sys approached K d .…”

Section: Parameters Of the Volume Backscatter Returnmentioning

confidence: 99%

Remote Sensing of Suspended Sediment Concentrations Based on the Waveform Decomposition of Airborne LiDAR Bathymetry

Zhao

Zhang

et al. 2018

Remote Sensing

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Airborne LiDAR bathymetry (ALB) has been shown to have the ability to retrieve water turbidity using the waveform parameters (i.e., slopes and amplitudes) of volume backscatter returns. However, directly and accurately extracting the parameters of volume backscatter returns from raw green-pulse waveforms in shallow waters is difficult because of the short waveform. This study proposes a new accurate and efficient method for the remote sensing of suspended sediment concentrations (SSCs) in shallow waters based on the waveform decomposition of ALB. The proposed method approaches raw ALB green-pulse waveforms through a synthetic waveform model that comprises a Gaussian function (for fitting the air-water interface returns), triangle function (for fitting the volume backscatter returns), and Weibull function (for fitting the bottom returns). Moreover, the volume backscatter returns are separated from the raw green-pulse waveforms by the triangle function. The separated volume backscatter returns are used as bases to calculate the waveform parameters (i.e., slopes and amplitudes). These waveform parameters and the measured SSCs are used to build two power SSC models (i.e., SSC (C)-Slope (K) and SSC (C)-Amplitude (A) models) at the measured SSC stations. Thereafter, the combined model is formed by the two established C-K and C-A models to retrieve SSCs. SSCs in the modeling water area are retrieved using the combined model. A complete process for retrieving SSCs using the proposed method is provided. The proposed method was applied to retrieve SSCs from an actual ALB measurement performed using the Optech Coastal Zone Mapping and Imaging LiDAR in a shallow and turbid water area. A mean bias of 0.05 mg/L and standard deviation of 3.8 mg/L were obtained in the experimental area using the combined model.

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Current and future horizon of optics and photonics in environmental sustainability

Sridarshini

Chidambaram

Geerthana³

et al. 2022

Sustainable Computing: Informatics and Systems

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Experimental evaluation of an airborne depth-sounding lidar

Cited by 3 publications

References 0 publications

Depth Measurement Bias in Pulsed Airborne Laser Hydrography Induced by Chromatic Dispersion

Depth Measurement Bias in Pulsed Airborne Laser Hydrography Induced by Chromatic Dispersion

Remote Sensing of Suspended Sediment Concentrations Based on the Waveform Decomposition of Airborne LiDAR Bathymetry

Current and future horizon of optics and photonics in environmental sustainability

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