Abstract
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.
Highlights
Suspended sediments play a major role in erosion/deposition processes, biomass primary production, and the transport of nutrients, micropollutants, and heavy metals [1]
The proposed method overcomes the shortcoming of traditional methods and can extract the volume backscatter return from the raw pulse waveform to accurately retrieve suspended sediment concentrations (SSCs) in shallow waters
VTohleumeetbhaocdksaclasottecranretbuernasppinlietdheinfoduereprepwraetseernst.atIivnesiwtuatperosinotf mtheeasSuSrCemseanmtsploinfgSSsCtatsiohnosulwdebre bpelrofowrm0.e4d3 taoncdal1ib8r.8a,terethspeewctaivelfyo.rmThpraerearmetertieervsindgerSivSeCd mfroomdetlhs e(ir.ae.w, tphuelsCe-Kw,aCv-eAforamnds. cToomebnisnuerde mthoedaeclcsu)rwaceyreofbtuheiltpruospinogsetdhme ewthaovdef,otrhme dpeanrsaitmyeatnedrsreapnrdesmenetaastuivrendesSsSCofst.hSeDSsSCofsa4m.5,pl3i.n9g, astnadtio3n.8s mshgo/uLldwbeerecoonbstaidineeredduwsihnegntchoellCec-Kti,nCg-tAh,esaendfieclodmdbaitna.ed models, respectively, thereby showing that the combined model was best among the three models
Summary
Suspended sediments play a major role in erosion/deposition processes, biomass primary production, and the transport of nutrients, micropollutants, and heavy metals [1]. Through the C-K and the C-A models, SSCs at a pulse spot can be estimated by using K and A, respectively, of the corresponding volume backscatter return. Given the spatial distribution of the four SSC sampling stations, the slopes and amplitudes of (vao) luEmmepbiraiccaklsCca-Kttemr ordeteul rns and SSCs at stations 1, 3, and 4 are used to build the C-K, C-A and combinFeidgumreod6ealss.hows that the relationship between the slopes of volume backscatter returns and (a)meEamsuprierdicSaSl CCs-Kinmthoedeflour representative waters is monotonically increasing. This example shows the feasibility of establishing a retrieval model with Ks and As of the volume backscatter returns. Given that the combined model has higher Faicgcuurrea8c.yStlhopaenstahnedCa-mKpalintuddCes-Aobmtaoindeedlsu,stihneg SthSeCprreotproiesevdedmbeythothdes cinomthbeienxepdermimoednetalliswuatseerd as the final reasruelat.. (a) Slopes of the separated volume backscatter returns; (b) corresponding amplitudes
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