| Airborne LiDAR bathymetry(ALB)technology has shown great potential in shallow waters such as coastal zones and islands and reefs.However,there are still some deficiencies in data processing,which restricts the further development of ALB technology.Therefore,in view of the technical development and application requirements of ALB,the bathymetric errors are specifically analysed and evaluated from the device,environment,and target aspects.And the ALB total error model is established.In addition,the new methods for extracting effective parameters of echo,refraction correction,and eliminating system error between strips,which the ALB data were used to carry out the application of sediment classification in typical areas.The related work is carried out from three aspects:theoretical modeling,data processing and data application of ALB system.This dissertation conducts a detailed study from five key aspects(ALB echo signal processing and extraction method,ALB theoretical analysis model of measurement error caused by device,environment and target factors,refraction correction at the air-water interface,strips mosaicking,and coral reef information extraction).The main work and innovation points of the dissertation are as follows:1.To solve the problems that the shallow water echo signals of ALB are easily confused and difficult to be identified to extract water depth,an ALB waveform fitting algorithm based on layered heterogeneous model is proposed in this dissertation.According to the corresponding characteristics of different components of waveform,the ALB waveforms are fitted to a combination of three functions:a Gaussian function for the water surface contribution,a B-spline function for the water bottom contribution,and a Double-exponential function to fit the water column contribution.To get the best fitting effect of each part of echo signals,the corresponding decomposition parameters are optimized using Levenberg-Marquardt(LM)fitting algorithm.The performance of the proposed fitting model was verified by the measured data from the South China Sea.The proposed fitting model performed significantly better than the Double-Gaussian algorithm by reducing 65.11%,2.83%,1.01%and 86.61%of the average root mean square error(RMSE),average coefficient of determination(R2),average correlation coefficient(CORR)and average correlation coefficient standard deviation(STD),respectively.The proposed fitting model has the great robustness and can effectively meet the technical requirements of the scientific research and engineering application for ALB.2.Six different effects that influence the accuracy of ALB data are systematically analyzed and modeled for three aspects in this paper:the device aspect(laser pointing deflection),environmental aspect(atmospheric limitation,refraction on the sea surface,refraction in water,scattering in water)and target aspect(irregular bottom).For a water depth of 10 m,the ranging errors of the six different error models are 30 cm of the laser pointing error,less than 1 cm of the atmospheric limitation error,14 cm of the refraction error on the sea surface,5 cm of the refraction error in water,6 cm of the scattering errors in water and 2 cm of the irregular bottom error,respectively.The proposed error models can not only provide the reference measurement scheme for ALB data acquisition,but also to provide the effective error correction reference for ALB data post-processing.3.To reduce the refraction influence of blue-green laser at the air-water interface,a refraction correction method based on the instantaneous sea surface profile and ray tracing is proposed.First,the three-dimensional(3D)sea surface profile is fitted based on least squares criteria and the wave spectrum,using the laser point data reflected by the sea surface.Then,based on the sea surface slope,the geolocation biases of the laser points are corrected by tracing every laser transmission path at the air-water interface.The developed method is used to correct the ALB data collected in the South China Sea,and verified by the topography data captured by a ship-borne multi-beam echo sounder(MBES).For a water depth of 10 m,the bathymetric accuracy of ALB is improved by approximately 9.2 cm.The developed method can effectively improve the bathymetric accuracy of the ALB data.4.To reduce the 3D spatial offsets caused by residual error(mainly calibration residual error),a Monte Carlo matching algorithm based on a nonlinear least-squares adjustment model is proposed.First,the raw data of strip overlap areas were filtered according to their relative drift of depths.Second,a Monte Carlo model and nonlinear least-squares adjustment model were combined to obtain seven transformation parameters.Then,the multibeam bathymetric data were used to correct the initial strip during strip mosaicing.Finally,to evaluate the proposed method,the experimental results were compared with the results of the Iterative Closest Points(ICP)and three-dimensional Normal Distributions Transform(3D-NDT)algorithms.When the mean DRO error of the corresponding points on adjacent raw strips is greater than 1 m,the algorithm can still resolve strip mosaicking to an average distance of 7 cm,which realizes the ALB strip mosaicking with the high accuracy and strong robustness.5.Based on the high accuracy waveform data and terrain data obtained by ALB data processing,this dissertation proposes a methodology to detect coral reefs by combining ALB bottom waveform and topographic feature data.A feature vector was established by deriving bottom waveform variables(the peak amplitude,pulse width,area,skewness,kurtosis and backscatter cross-section)and topographic variables(the depth standard deviation,slope,bathymetric position index(BPI),Gaussian curvature,mean curvature and roughness).Using a support vector machine(SVM)classifier,coral reefs are detected by distinguishing two classes(coral reefs and others)on the seafloor.Compared with the existing methods,its overall accuracy and Kappa coefficient are improved by 2.65%and 0.06%,respectively.This mehod not only overcomes the difficulty of data collection in shallow water area,but also realizes the high precision extraction of coral reef information. |
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