scholarly journals A Depth-Adaptive Waveform Decomposition Method for Airborne LiDAR Bathymetry

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5065 ◽  
Author(s):  
Xing ◽  
Wang ◽  
Xu ◽  
Lin ◽  
Li ◽  
...  
Keyword(s):  
Shallow Water ◽  
Deep Water ◽  
Water Surface ◽  
Decomposition Method ◽  
Trust Region ◽  
Airborne Lidar ◽  
High Signal ◽  
Bathymetric Range ◽  
Airborne Lidar Bathymetry ◽  
Water Bottom

Airborne LiDAR bathymetry (ALB) has shown great potential in shallow water and coastal mapping. However, due to the variability of the waveforms, it is hard to detect the signals from the received waveforms with a single algorithm. This study proposed a depth-adaptive waveform decomposition method to fit the waveforms of different depths with different models. In the proposed method, waveforms are divided into two categories based on the water depth, labeled as “shallow water (SW)” and “deep water (DW)”. An empirical waveform model (EW) based on the calibration waveform is constructed for SW waveform decomposition which is more suitable than classical models, and an exponential function with second-order polynomial model (EFSP) is proposed for DW waveform decomposition which performs better than the quadrilateral model. In solving the model’s parameters, a trust region algorithm is introduced to improve the probability of convergence. The proposed method is tested on two field datasets and two simulated datasets to assess the accuracy of the water surface detected in the shallow water and water bottom detected in the deep water. The experimental results show that, compared with the traditional methods, the proposed method performs best, with a high signal detection rate (99.11% in shallow water and 74.64% in deep water), low RMSE (0.09 m for water surface and 0.11 m for water bottom) and wide bathymetric range (0.22 m to 40.49 m).

scholarly journals Refined Geometric Modeling of Laser Pulse Propagation in Airborne LiDAR Bathymetry

2021 ◽  
Author(s):  
Katja Richter ◽  
David Mader ◽  
Patrick Westfeld ◽  
Hans-Gerd Maas
Keyword(s):  
Geometric Modeling ◽  
Water Surface ◽  
Pulse Propagation ◽  
Geometric Model ◽  
Airborne Lidar ◽  
Surface Geometry ◽  
Accurate Representation ◽  
Airborne Lidar Bathymetry ◽  
The Impact ◽  
Water Bottom

AbstractTo achieve a geometrically accurate representation of the water bottom, airborne LiDAR bathymetry (ALB) requires the correction of the raw 3D point coordinates due to refraction at the air–water interface, different signal velocity in air and water, and further propagation induced effects. The processing of bathymetric LiDAR data is based on a geometric model of the laser bathymetry pulse propagation describing the complex interactions of laser radiation with the water medium and the water bottom. The model comprises the geometric description of laser ray, water surface, refraction, scattering in the water column, and diffuse bottom reflection. Conventional geometric modeling approaches introduce certain simplifications concerning the water surface, the laser ray, and the bottom reflection. Usually, the local curvature of the water surface and the beam divergence are neglected and the travel path of the outgoing and the returned pulse is assumed to be identical. The deviations between the applied geometric model and the actual laser beam path cause a coordinate offset at the water bottom, which affects the accuracy potential of the measuring method. The paper presents enhanced approaches to geometric modeling which are based on a more accurate representation of water surface geometry and laser ray geometry and take into account the diffuse reflection at the water bottom. The refined geometric modeling results in an improved coordinate accuracy at the water bottom. The impact of the geometric modeling methods on the accuracy of the water bottom points is analyzed in a controlled manner using a laser bathymetry simulator. The findings will contribute to increase the accuracy potential of modern ALB systems.

scholarly journals Airborne Hyperspectral Imaging for Submerged Archaeological Mapping in Shallow Water Environments

2019 ◽  
Vol 11 (19) ◽  
pp. 2237 ◽  
Author(s):  
Alexandre Guyot ◽  
Marc Lennon ◽  
Nicolas Thomas ◽  
Simon Gueguen ◽  
Tristan Petit ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Shallow Water ◽  
Water Column ◽  
Sea Level ◽  
Hyperspectral Imagery ◽  
Airborne Lidar ◽  
Radiative Transfer Model ◽  
Invasive Technique ◽  
Transfer Model ◽  
Water Bottom

Nearshore areas around the world contain a wide variety of archeological structures, including prehistoric remains submerged by sea level rise during the Holocene glacial retreat. While natural processes, such as erosion, rising sea level, and exceptional climatic events have always threatened the integrity of this submerged cultural heritage, the importance of protecting them is becoming increasingly critical with the expanding effects of global climate change and human activities. Aerial archaeology, as a non-invasive technique, contributes greatly to documentation of archaeological remains. In an underwater context, the difficulty of crossing the water column to reach the bottom and its potential archaeological information usually requires active remote-sensing technologies such as airborne LiDAR bathymetry or ship-borne acoustic soundings. More recently, airborne hyperspectral passive sensors have shown potential for accessing water-bottom information in shallow water environments. While hyperspectral imagery has been assessed in terrestrial continental archaeological contexts, this study brings new perspectives for documenting submerged archaeological structures using airborne hyperspectral remote sensing. Airborne hyperspectral data were recorded in the Visible Near Infra-Red (VNIR) spectral range (400–1000 nm) over the submerged megalithic site of Er Lannic (Morbihan, France). The method used to process these data included (i) visualization of submerged anomalous features using a minimum noise fraction transform, (ii) automatic detection of these features using Isolation Forest and the Reed–Xiaoli detector and (iii) morphological and spectral analysis of archaeological structures from water-depth and water-bottom reflectance derived from the inversion of a radiative transfer model of the water column. The results, compared to archaeological reference data collected from in-situ archaeological surveys, showed for the first time the potential of airborne hyperspectral imagery for archaeological mapping in complex shallow water environments.

Environmental Forces on Offshore LNG Terminals: The Complications of Shallow Water

2004 ◽  
Author(s):  
George Z. Forrsitall
Keyword(s):  
Shallow Water ◽  
Deep Water ◽  
Field Measurements ◽  
Review Of The Literature ◽  
Water Demands ◽  
Local Measurements ◽  
Wave Heights ◽  
Overall Reliability ◽  
Water Depths ◽  
Water Bottom

Construction of large and expensive facilities in relatively shallow water demands that additional effort be paid to the extreme environmental conditions expected there. A review of the literature on waves in shallow water shows that many processes must be considered there which are not important in deep water. Bottom friction under waves depends on the detailed bottom conditions and parameterizing it properly may require calibration to local measurements. The limits on wave heights over the nearly flat bottoms that are common in water depths of 10–30 m are poorly known. Additional laboratory and field measurements appear to be necessary before depth limited waves can be confidently specified. The structures often respond differently to wave from different directions, so directional criteria could be useful. Commonly used methods of specifying directional criteria are un-conservative, but it is possible to adjust them so that the overall reliability of the structure is preserved.

scholarly journals DETECTION AND EXTRACTION OF WATER BOTTOM TOPOGRAPHY FROM LASERBATHYMETRY DATA BY USING FULL-WAVEFORM-STACKING TECHNIQUES

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1053-1059 ◽  
Author(s):  
D. Mader ◽  
K. Richter ◽  
P. Westfeld ◽  
R. Weiß ◽  
H.-G. Maas
Keyword(s):  
Penetration Depth ◽  
High Reliability ◽  
Bottom Topography ◽  
Airborne Lidar ◽  
Water Bodies ◽  
Water Turbidity ◽  
Full Waveform ◽  
Reliable Detection ◽  
Airborne Lidar Bathymetry ◽  
Water Bottom

<p><strong>Abstract.</strong> Airborne LiDAR bathymetry allows an efficient and area-wide acquisition of water bottom points in shallow water areas. However, the measurement method is severely limited by water turbidity, impending a reliable detection of water bottom points at higher turbidity or in deeper water bodies. This leads to an incomplete acquisition of the water bottom topography. In this contribution, advanced processing methods are presented, which increase the penetration depth compared to the original processed data and enable a reliable extraction and detection of bottom points in deeper water bodies. The methodology is based on the analysis of correlated neighborhood information assuming a steady water bottom. The results confirm a significantly higher penetration depth with a high reliability of the additionally extracted water bottom points along with a larger coverage of the water bottom topography.</p>

scholarly journals FEASIBILITY INVESTIGATION ON SINGLE PHOTON LIDAR BASED WATER SURFACE MAPPING

2018 ◽  
Vol IV-1 ◽  
pp. 109-116
Author(s):  
G. Mandlburger ◽  
B. Jutzi
Keyword(s):  
Shallow Water ◽  
Water Level ◽  
Water Surface ◽  
Single Photon ◽  
Ground Truth ◽  
Green Laser ◽  
Airborne Lidar ◽  
Large Area ◽  
Surface Mapping

<p><strong>Abstract.</strong> The recent advent of single photon sensitive airborne LiDAR (Light Detection And Ranging) sensors has enabled higher areal coverage performance at the price of an increased outlier rate and a lower ranging accuracy compared to conventional Multi-Photon LiDAR. Single Photon LiDAR, in particular, uses green laser light capable of penetrating clear shallow water. Although primarily designed for large area topographic mapping, the technique can also be used for mapping the water surface and shallow water bathymetry. In this contribution we investigate the capability of Single Photon LiDAR for large area mapping of water surface heights. While interface returns from conventional green-only bathymetric sensors generally suffer from water level underestimation due to the water penetration capabilities of green laser radiation, the specific questions are, if Single Photon LiDAR (i) is less affected by this well known effect due to the high receiver sensitivity and (ii) consequently delivers a higher number of water surface echoes. The topic is addressed empirically in a case study by comparing the water surface responses of Single Photon LiDAR (Navarra, Spain) and Multi-Photon Topo-Bathymetric LiDAR (Neubacher Au, Austria) for selected water bodies with a horizontal water surface (reservoirs, ponds). Although flown at different altitudes, both datasets are well comparable as they exhibit the same strip point density of ca. 14<span class="thinspace"></span>points/m<sup>2</sup>. The expected superiority of Single Photon LiDAR over conventional green-only bathymetric LiDAR for mapping water surfaces could not be verified in this investigation. While both datasets show good agreement compared to a reference water level when aggregating points into cells of 10<span class="thinspace"></span>&amp;times;<span class="thinspace"></span>10<span class="thinspace"></span>m<sup>2</sup> (mean deviations &amp;lt;<span class="thinspace"></span>5<span class="thinspace"></span>cm), higher resolution Single Photon LiDAR based water surface models (grid size 1&amp;ndash;5<span class="thinspace"></span>m) show a systematic water level underestimation of 5&amp;ndash;20<span class="thinspace"></span>cm. However, independently measured ground truth observations and simultaneous data acquisition of the same area with both techniques are necessary to verify the results.</p>

scholarly journals SEMANTIC CHANGE DETECTION OF RIVER GROUND POINTS IN AIRBORNE LIDAR BATHYMETRY DATA USING VOXEL OCCUPANCIES

2019 ◽  
Vol IV-2/W7 ◽  
pp. 9-15
Author(s):  
R. Boerner ◽  
L. Hoegner ◽  
U. Stilla
Keyword(s):  
Water Surface ◽  
Semantic Information ◽  
Reference Data ◽  
Ground Truth ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Semantic Change ◽  
Data Set ◽  
Airborne Lidar Bathymetry ◽  
Semantic Reference

<p><strong>Abstract.</strong> This paper proposes a method to get semantic information of changes in bathymetric point clouds. This method aims for assigning labels to river ground points which determine if either the point can be compared with a reference DEM, if there are no data in the reference or if there are no water points inside the new Data of wet areas of the reference data. This labels can be further used to specify areas where differences of DEMS can be calculated, the comparable areas. The Areas where no reference data is found specify areas where the reference DEM will have a higher variance due to interpolation which should be considered in the comparison. The areas where no water in the new data was found specify areas there no refraction correction in the new data can be done and which should be considered with a higher variance of the ground points or there the water surface should be tried to reconstruct. The proposed approach uses semantic reference data to specify water areas in the new scan. An occupancy analysis is used to specify if voxels of the new data exist in the reference or not. In case of occupancy, the labels of the reference are assigned to the new data and in case of no occupancy, the label of changed data is assigned. A histogram based method is used to separate ground and water points in wet areas and a second occupancy analysis is used to specify the semantic changes in wet areas. The proposed method is evaluated on a proposed data set of the Mangfall area where the ground truth is manually labelled.</p>

scholarly journals Potential of a Non-linear Full-Waveform Stacking Technique in Airborne LiDAR Bathymetry

2021 ◽  
Author(s):  
David Mader ◽  
Katja Richter ◽  
Patrick Westfeld ◽  
Hans-Gerd Maas
Keyword(s):  
Water Depth ◽  
High Reliability ◽  
Bottom Topography ◽  
Airborne Lidar ◽  
Majority Voting ◽  
Waveform Data ◽  
Full Waveform ◽  
Airborne Lidar Bathymetry ◽  
Water Bottom

AbstractAirborne LiDAR bathymetry is an efficient measurement method for area-wide acquisition of water bottom topography in shallow water areas. However, the method has a limited penetration depth into water bodies due to water turbidity. This affects the accuracy and reliability of the determination of water bottom points in waters with high turbidity or larger water depths. Furthermore, the coverage of the water bottom topography is also limited. In this contribution, advanced processing methods are presented with the goal of increasing the evaluable water depth, resulting in an improved coverage of the water bottom by measurement points. The methodology moves away from isolated evaluation of individual signals to a determination of water bottom echoes, taking into account information from closely adjacent measurements, assuming that these have similar or correlated characteristics. The basic idea of the new processing approach is the combination of closely adjacent full-waveform data using full-waveform stacking techniques. In contrast to established waveform stacking techniques, we do not apply averaging, which entails low-pass filtering effects, but a modified majority voting technique. This has the effect of amplification of repeating weak characteristics and an improvement of the signal-noise-ratio. As a consequence, it is possible to detect water bottom points that cannot be detected by standard methods. The results confirm an increased penetration water depth by about 27% with a high reliability of the additionally extracted water bottom points along with a larger coverage of the water bottom topography.

scholarly journals Comparison of Multichannel Signal Deconvolution Algorithms in Airborne LiDAR Bathymetry Based on Wavelet Transform

2021 ◽  
Author(s):  
Yue Song ◽  
Houpu Li ◽  
Guojun Zhai ◽  
Yan He ◽  
Shaofeng Bian ◽  
...  
Keyword(s):  
Shallow Water ◽  
Blind Deconvolution ◽  
Low Cost ◽  
Wavelet Denoising ◽  
Airborne Lidar ◽  
Orthogonal Polarization ◽  
Denoising Method ◽  
Airborne Lidar Bathymetry ◽  
Polarization Channel ◽  
Waveform Processing

Abstract Airborne LiDAR bathymetry offers low cost and high mobility, making it an ideal option for shallow-water measurements. However, due to differences in the measurement environment and the laser emission channel, the received waveform is difficult to extract using a single algorithm. The choice of a suitable waveform processing method is thus extremely important to guarantee the accuracy of the bathymetric retrieval. In this work, we use a wavelet-denoising method to denoise the received waveform and then test four algorithms for denoised-waveform processing: Richardson–Lucy deconvolution (RLD), blind deconvolution (BD), Wiener filter deconvolution (WFD), and constrained least-squares filter deconvolution (RFD). The simulation database and the measured multichannel database are used to evaluate the algorithms, with the focus on improving their performance after the data-denoising preprocessing and their capability of extracting water depth. The results show that applying wavelet denoising before deconvolution improves the extraction accuracy. The four algorithms perform better for the shallow water orthogonal polarization channel (PMT2) than the shallow horizontal row polarization channel (PMT1). Of the four algorithms, RLD provides the best signal-detection rate, and RFD is the most robust. BD has low computational efficiency, and WFD performs poorly in deep water (<25 m).

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