Fanlin Yang

Variability of particle size distribution with respect to inherent optical properties in Poyang Lake, China

Suspended particulate matter plays a significant role in the studies of sediment fluxes, phytoplankton dynamics, and water optical properties. This study focuses on the relationships between particle size distribution (PSD), waters inherent optical properties (IOPs), and water constituents. We investigated the complex waters of Poyang Lake, the largest freshwater lake in China, in wet and dry seasons during 2008-2011. Because of the distinct temporal-spatial variation of Poyang Lake, these parameters and relationships also demonstrate seasonal and regional variability. The variation range of the concentration of suspended particulate matter is 0.32-69.08  mg/l, with a mean value of 22.21  mg/l. The median particle size in the dry season is much larger than that of the wet season. The Junge distribution fits the PSD of Poyang Lake very well in the scope of 6.21-331 μm. Furthermore, the slopes of the PSD range from 3.54 to 4.69, with a mean value of 4.11, with the steepest slopes (>4.5) occurring in the waters around Songmen Mountain Island and the northern waterway. A negative correlation was found between median particle size (Dv50) and the mass-specific absorption coefficient at 443 nm [apm(443)] for both wet and dry seasons. Identical to analogous waters, the spectral slopes of the PSD correlate well with the spectral slopes of the attenuation coefficient, but with different fitted formulas. In the dry season, the particle size can better explain the variability of the scattering coefficient, while the mass-specific scattering coefficient is better explained by the apparent density. However, no similar results were found for the wet season. In addition, the spectral slopes of the backscattering coefficient correlated well with the PSD slope, and the bulk refractive index calculated from the backscattering ratio and PSD slope can indicate the particle composition of Poyang Lake. Overall, the knowledge on the PSD and IOPs gained in this study broadens our understanding of water optics in highly turbid water columns.

The Waveform Model of Laser Altimeter System with Flattened Gaussian Laser

The current waveform model of a laser altimeter is based on a Gaussian laser beam of fundamental mode, while the flattened Gaussian beam has many advantages such as nearly constant energy distribution on the center of the cross-section. Following the theory of the flattened Gaussian beam and the waveform theory of the laser altimeter, some of the primary parameters of the received waveform were derived, and a laser altimetry waveform simulator and waveform processing software were programmed and improved under the circumstance of a flattened Gaussian beam. The result showed that the bias between theoretical and simulated waveforms was less than 3% for every order mode, the waveform width and range error would increase as target slope or order number rose. Under higher order mode, the shapes of the received waveforms were no longer Gaussian, and could be fitted more precisely as a generalized Gaussian function with power bigger than 2. The flattened beam got much better performance for a multi-surface target, especially when the small surface is far from the center of the laser footprint. This article provides the waveform theoretical basis for the use of a flattened Gaussian beam in a laser altimeter.

Comparison of two Bayesian-point-estimation methods in multiple-source localization

Environmental uncertainty represents the limiting factor in matched-field localization. Within a Bayesian framework, both the environmental parameters, and the source parameters are considered to be unknown variables. However, including environmental parameters in multiple-source localization greatly increases the complexity and computational demands of the inverse problem. In the paper, the closed-form maximumlikelihood expressions for source strengths and noise variance at each frequency allow these parameters to be sampled implicitly, substantially reducing the dimensionality and difficulty of the inversion. This paper compares two Bayesian-point-estimation methods: the maximum a posteriori (MAP) approach and the marginal posterior probability density (PPD) approach to source localization. The MAP approach determines the sources locations by maximizing the PPD over all source and environmental parameters. The marginal PPD approach integrates the PPD over the unknowns to obtain a sequence of marginal probability distribution over source range or depth. Monte Carlo analysis of the two approaches for a test case involving both geoacoustic and water-column uncertainties indicates that: (1) For sensitive parameters such as source range, water depth and water sound speed, the MAP solution is better than the marginal PPD solution. (2) For the less sensitive parameters, such as, bottom sound speed, bottom density, bottom attenuation and water sound speed, when the SNR is low, the marginal PPD solution can better smooth the noise, which leads to better performance than the MAP solution. Since the source range and depth are sensitive parameters, the research shows that the MAP approach provides a slightly more reliable method to locate multiple sources in an unknown environment.

Calibration method of rotation and displacement systematic errors for ship-borne mobile surveying systems

Rotation and displacement errors between sensors and the Inertial Navigation System have significant effects on the accuracy of measured point clouds. In ship-borne mobile surveying systems, over and underwater targets are measured by a laser scanner and multibeam echo sounder, respectively. A simple calibration method and a universal calibration field are urgently needed to address both rotation errors and displacement problems for over and underwater sensors. First, a systematic error analytic function is established through the path that the geolocation expression of measured data is derived and substituted into the expression of known calibration planes. Then, the calibration expression that can calibrate both rotation errors and displacement is derived based on the least-squares criteria using a designed calibration pool. The calibrating results showed that for both over and underwater sensors, the accuracies of rotation errors and displacement estimation are better than 0.015° and 1.2 mm, respectively. After this calibration, the geolocation accuracy of measured points is better than 5 cm within a range of 30 m. The method can effectively calibrate systematic errors and serve as guidance to address the calibration problem for mobile surveying systems.

Mosaicing of airborne LiDAR bathymetry strips based on Monte Carlo matching

This study proposes a new methodology for mosaicing airborne light detection and ranging (LiDAR) bathymetry (ALB) data based on Monte Carlo matching. Various errors occur in ALB data due to imperfect system integration and other interference factors. To account for these errors, 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. The results demonstrate that the algorithm proposed in this study is more robust and effective. When the quality of the raw data is poor, the Monte Carlo matching algorithm can still achieve centimeter-level accuracy for overlapping areas, which meets the accuracy of bathymetry required by IHO Standards for Hydrographic Surveys Special Publication No.44.

Shipborne Over- and Under-Water Integrated Mobile Mapping System and Its Seamless Integration of Point Clouds

ABSTRACT The rapid acquisition techniques of over- and under-water geoinformation is urgently needed. The Shipborne Over- and Under-water integrated Mobile Mapping System (SiOUMMS) applies plug-in and multi-process network technology to achieve integrated data acquisition and cooperative control of multi-sensors, such as Global Navigation Satellite System, Inertial Measurement Unit, laser scanner, and multi-beam echo sounder. The proposed system can meet the requirements of diverse application scenarios and sensors, allowing for flexibility and scalability. Meanwhile, coarse calibration based on a set of common points and fine calibration using the plane feature constraint are proposed for integratedly obtaining the exterior orientation elements of the laser scanner and the multi-beam echo sounder. Together, these methods provide theoretical support and technical help to the seamless integration of over- and under-water point clouds. Experiments are also described, proving that the root mean square error of over-water point clouds is 0.133 m, the average elevation clearance spacing between adjacent over- and under-water point clouds is less than 0.3 m, and the average horizontal clearance spacing is less than 0.2 m. At the same time, cases in this paper show that SiOUMMS has made important achievements in the integrated measurement of reefs, coastal zone, and inland waterways, and has broad prospects for future applications.

Morphological characterization of coral reefs by combining LiDAR and MBES data: A case study from Yuanzhi Island, South China Sea

The correlation between seafloor morphological features and biological complexity has been identified in numerous recent studies. This research focused on the potential for accurate characterization of coral reefs based on high-resolution bathymetry from multiple sources. A standard deviation (STD) based method for quantitatively characterizing terrain complexity was developed that includes robust estimation to correct for irregular bathymetry and a calibration for the depth-dependent variablity of measurement noise. Airborne LiDAR and shipborne sonar bathymetry measurements from Yuanzhi Island, South China Sea, were merged to generate seamless high-resolution coverage of coral bathymetry from the shoreline to deep water. The new algorithm was applied to the Yuanzhi Island surveys to generate maps of quantitive terrain complexity, which were then compared to in situ video observations of coral abundance. The terrain complexity parameter is significantly correlated with seafloor coral abundance, demonstrating the potential for accurately and efficiently mapping coral abundance through seafloor surveys, including combinations of surveys using different sensors.

Refraction Correction of Airborne LiDAR Bathymetry Based on Sea Surface Profile and Ray Tracing

Water depth can be measured using airborne LiDAR bathymetry (ALB). However, when the green laser beam passes through the air–water interface, the sea surface slope greatly affects the laser propagation path, significantly influencing the accuracy of the measured seafloor topography. To reduce its influence, a refraction correction method at the air–water interface based on the sea surface profile and ray tracing is proposed. First, the 3-D sea surface profile is fit based on the least-squares criteria and the wave spectrum, using the laser point data reflected by the sea surface. Then, on the basis of 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 multibeam echo sounder. Before the refraction correction, the mean absolute error (MAE) is 14.2 cm, and the root-mean-square error (RMSE) is 17.5 cm. After the refraction correction, the MAE and RMSE decrease to 7.2 and 8.3 cm, respectively. The developed method can effectively improve the bathymetric accuracy of the ALB data.

A New Wind Speed Retrieval Method for an Ocean Surface Using the Waveform Width of a Laser Altimeter

ABSTRACT The current retrieval method of sea wind speeds using a space-borne laser device is based on the received energies, which are significantly influenced by the absorption and scatter effect in the atmosphere. A new method is derived to retrieve the wind speed by the path of waveform width—root mean square (RMS) surface height—wind speed, which differs from the classical path of received energy—mean sea slope—wind speed. First, by deriving a more rigorous expression of the waveform model of an ocean surface for a laser altimeter, the theoretical relationship between the surface height RMS and waveform width is established. Second, the surface height RMS is fitted to a new empirical formula that is related to the wind speed using the geoscience laser altimeter system (GLAS) waveform data and the National Centers for Environmental Prediction wind speeds. Then, the JONSWAP spectra with swell effect and the waveform simulator are used to generate sea surface profiles and echo waveforms to verify the new retrieval method. Finally, in a Pacific region by using GLAS waveform data, the retrieval results indicate that the bias was approximately 0.2 m/s, the RMSE was approximately 1.2 m/s, and the ratio of valid data exceeded 20%.