scholarly journals Retrieval of Nearshore Bathymetry around Ganquan Island from LiDAR Waveform and QuickBird Image

2019 ◽  
Vol 9 (20) ◽  
pp. 4375
Author(s):  
Zhang ◽  
Zhang ◽  
Ma ◽  
Tian ◽  
Jiang
Keyword(s):  
Remote Sensing ◽  
Relative Error ◽  
Water Depth ◽  
Conflicts Of Interest ◽  
Gaussian Function ◽  
Measurement Data ◽  
Validation Data ◽  
Waveform Data ◽  
Depth Measurement ◽  
Lidar Waveform

Optical remote sensing is an effective means of water depth measurement, but the current approach of mainstream bathymetric retrieval requires a large amount of onsite measurement data. Such data are hard to obtain from places where underwater terrains are complicated and unsteady, and from sea areas affected by issues with rights and conflicts of interest. In recent years, the emergence of airborne light detection and ranging (LiDAR) provided a new technical means for field bathymetric survey. In this study, water depth inversion was carried out around an island far from the mainland by using remote sensing images and real LiDAR waveform data. Multi-Gaussian function fitting was proposed to extract water depth data from waveform data, and bathymetric values were used as control and validation data of the active and passive combination of water depth inversion. Results show that the relative error was 5.6% for the bathymetric retrieval from LiDAR waveform data, and the accuracy meets the requirements of ocean bathymetry. The average relative error of water depth inversion based on active and passive remote sensing was less than 9%. The method used in this study can also reduce the use of LiDAR data and the cost, thus providing a new idea for future coastal engineering application and construction.

scholarly journals Shallow Water Bathymetry Based on Inherent Optical Properties Using High Spatial Resolution Multispectral Imagery

2020 ◽  
Vol 12 (18) ◽  
pp. 3027 ◽  
Author(s):  
Xuechun Zhang ◽  
Yi Ma ◽  
Jingyu Zhang
Keyword(s):  
Remote Sensing ◽  
Shallow Water ◽  
Linear Model ◽  
Spatial Resolution ◽  
Water Depth ◽  
High Spatial Resolution ◽  
Optical Parameters ◽  
Optical Remote Sensing ◽  
Depth Measurement ◽  
Dongdao Island

Bathymetric surveys are of great importance for submarine topography mapping and coastal construction projects. They are also of great significance for terrain surveys of islands and coastal zones, maritime navigation and marine management planning. Traditional ship-borne water depth measurement methods are costly and time-consuming, therefore, in recent years, passive optical remote sensing technology has become an important means for shallow water depth measurements. In addition, multispectral water depth optical remote sensing has wide application values. Considering the relationship between water depth and the inherent optical characteristics of water column, an inherent optical parameters linear model (IOPLM) is developed to estimate shallow water bathymetry from high spatial resolution multispectral images. Experiments were carried out in the shallow waters (≤20 m) around Dongdao Island in China’s Paracel Islands and Saipan Island in the Northern Mariana Islands. Different accuracy evaluation indexes were used to verify the model. The comparisons with the traditional log-linear model and the Stumpf model show that in terms of overall accuracy and accuracy in different water depths, the IOPLM has slightly better results and stronger retrieval capabilities than the other models. The mean absolute error (MAE) of Dongdao Island and Saipan Island reached 1.17 m and 1.92 m, and the root mean square error (RMSE) was 1.49 m and 2.4 m, respectively.

scholarly journals Predicting specific impulse distributions for spherical explosives in the extreme near-field using a Gaussian function

2021 ◽  
pp. 204141962199349
Author(s):  
Jordan J Pannell ◽  
George Panoutsos ◽  
Sam B Cooke ◽  
Dan J Pope ◽  
Sam E Rigby
Keyword(s):  
Scaling Laws ◽  
Near Field ◽  
Specific Impulse ◽  
Gaussian Function ◽  
Data Driven ◽  
Blast Load ◽  
Structural Deformation ◽  
Load Prediction ◽  
Validation Data ◽  
Wide Range

Accurate quantification of the blast load arising from detonation of a high explosive has applications in transport security, infrastructure assessment and defence. In order to design efficient and safe protective systems in such aggressive environments, it is of critical importance to understand the magnitude and distribution of loading on a structural component located close to an explosive charge. In particular, peak specific impulse is the primary parameter that governs structural deformation under short-duration loading. Within this so-called extreme near-field region, existing semi-empirical methods are known to be inaccurate, and high-fidelity numerical schemes are generally hampered by a lack of available experimental validation data. As such, the blast protection community is not currently equipped with a satisfactory fast-running tool for load prediction in the near-field. In this article, a validated computational model is used to develop a suite of numerical near-field blast load distributions, which are shown to follow a similar normalised shape. This forms the basis of the data-driven predictive model developed herein: a Gaussian function is fit to the normalised loading distributions, and a power law is used to calculate the magnitude of the curve according to established scaling laws. The predictive method is rigorously assessed against the existing numerical dataset, and is validated against new test models and available experimental data. High levels of agreement are demonstrated throughout, with typical variations of <5% between experiment/model and prediction. The new approach presented in this article allows the analyst to rapidly compute the distribution of specific impulse across the loaded face of a wide range of target sizes and near-field scaled distances and provides a benchmark for data-driven modelling approaches to capture blast loading phenomena in more complex scenarios.

Sensitivity of Intersegmental Angles of the Spinal Column to Errors Due to Marker Misplacement

2015 ◽  
Vol 137 (7) ◽  
Author(s):  
Hossein Rouhani ◽  
Sara Mahallati ◽  
Richard Preuss ◽  
Kei Masani ◽  
Milos R. Popovic
Keyword(s):  
Relative Error ◽  
Sagittal Plane ◽  
Gaussian Function ◽  
Spinal Column ◽  
Transverse Plane ◽  
Lumbar Region ◽  
Experimental Errors ◽  
Rms Error ◽  
Lower Lumbar ◽  
Anterior Direction

The ranges of angular motion measured using multisegmented spinal column models are typically small, meaning that minor experimental errors can potentially affect the reliability of these measures. This study aimed to investigate the sensitivity of the 3D intersegmental angles, measured using a multisegmented spinal column model, to errors due to marker misplacement. Eleven healthy subjects performed trunk bending in five directions. Six cameras recorded the trajectory of 22 markers, representing seven spinal column segments. Misplacement error for each marker was modeled as a Gaussian function with a standard deviation of 6 mm, and constrained to a maximum value of 12 mm in each coordinate across the skin. The sensitivity of 3D intersegmental angles to these marker misplacement errors, added to the measured data, was evaluated. The errors in sagittal plane motions resulting from marker misplacement were small (RMS error less than 3.2 deg and relative error in the angular range less than 15%) during the five trunk bending direction. The errors in the frontal and transverse plane motions, induced by marker misplacement, however, were large (RMS error up to 10.2 deg and relative error in the range up to 58%), especially during trunk bending in anterior, anterior-left, and anterior-right directions, and were often comparable in size to the intersubject variability for those motions. The induced errors in the frontal and transverse plane motions tended to be the greatest at the intersegmental levels in the lower lumbar region. These observations questioned reliability of angle measures in the frontal and transverse planes particularly in the lower lumbar region during trunk bending in anterior direction, and thus did not recommend interpreting these measures for clinical evaluation and decision-making.

scholarly journals REFINED SIMULATION OF SATELLITE LASER ALTIMETER FULL ECHO WAVEFORM

2018 ◽  
Vol XLII-3 ◽  
pp. 1267-1273
Author(s):  
H. Men ◽  
Y. Xing ◽  
G. Li ◽  
X. Gao ◽  
Y. Zhao ◽  
...  
Keyword(s):  
Laser Energy ◽  
Vital Role ◽  
Data Simulation ◽  
Laser Altimeter ◽  
Validation Data ◽  
Simulation Accuracy ◽  
Waveform Data ◽  
Full Waveform ◽  
Ground Target ◽  
Echo Simulation

The return waveform of satellite laser altimeter plays vital role in the satellite parameters designation, data processing and application. In this paper, a method of refined full waveform simulation is proposed based on the reflectivity of the ground target, the true emission waveform and the Laser Profile Array (LPA). The ICESat/GLAS data is used as the validation data. Finally, we evaluated the simulation accuracy with the correlation coefficient. It was found that the accuracy of echo simulation could be significantly improved by considering the reflectivity of the ground target and the emission waveform. However, the laser intensity distribution recorded by the LPA has little effect on the echo simulation accuracy when compared with the distribution of the simulated laser energy. At last, we proposed a refinement idea by analyzing the experimental results, in the hope of providing references for the waveform data simulation and processing of GF-7 satellite in the future.

scholarly journals Melt Pond Retrieval Based on the LinearPolar Algorithm Using Landsat Data

2021 ◽  
Vol 13 (22) ◽  
pp. 4674
Author(s):  
Yuqing Qin ◽  
Jie Su ◽  
Mingfeng Wang
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Relative Error ◽  
Large Scale ◽  
The Arctic ◽  
Landsat Data ◽  
Melt Pond ◽  
Melt Ponds ◽  
Very High ◽  
Sentinel 2

The formation and distribution of melt ponds have an important influence on the Arctic climate. Therefore, it is necessary to obtain more accurate information on melt ponds on Arctic sea ice by remote sensing. The present large-scale melt pond products, especially the melt pond fraction (MPF), still require verification, and using very high resolution optical satellite remote sensing data is a good way to verify the large-scale retrieval of MPF products. Unlike most MPF algorithms using very high resolution data, the LinearPolar algorithm using Sentinel-2 data considers the albedo of melt ponds unfixed. In this paper, by selecting the best band combination, we applied this algorithm to Landsat 8 (L8) data. Moreover, Sentinel-2 data, as well as support vector machine (SVM) and iterative self-organizing data analysis technique (ISODATA) algorithms, are used as the comparison and verification data. The results show that the recognition accuracy of the LinearPolar algorithm for melt ponds is higher than that of previous algorithms. The overall accuracy and kappa coefficient results achieved by using the LinearPolar algorithm with L8 and Sentinel-2A (S2), the SVM algorithm, and the ISODATA algorithm are 95.38% and 0.88, 94.73% and 0.86, and 92.40%and 0.80, respectively, which are much higher than those of principal component analysis (PCA) and Markus algorithms. The mean MPF (10.0%) obtained from 80 cases from L8 data based on the LinearPolar algorithm is much closer to Sentinel-2 (10.9%) than the Markus (5.0%) and PCA algorithms (4.2%), with a mean MPF difference of only 0.9%, and the correlation coefficients of the two MPFs are as high as 0.95. The overall relative error of the LinearPolar algorithm is 53.5% and 46.4% lower than that of the Markus and PCA algorithms, respectively, and the root mean square error (RMSE) is 30.9% and 27.4% lower than that of the Markus and PCA algorithms, respectively. In the cases without obvious melt ponds, the relative error is reduced more than that of those with obvious melt ponds because the LinearPolar algorithm can identify 100% of dark melt ponds and relatively small melt ponds, and the latter contributes more to the reduction in the relative error of MPF retrieval. With a wider range and longer time series, the MPF from Landsat data are more efficient than those from Sentinel-2 for verifying large-scale MPF products or obtaining long-term monitoring of a fixed area.

scholarly journals Technical Note: Using wavelet analyses on water depth time series to detect glacial influence in high-mountain hydrosystems

2013 ◽  
Vol 10 (4) ◽  
pp. 4369-4395 ◽  
Author(s):  
S. Cauvy-Fraunié ◽  
T. Condom ◽  
A. Rabatel ◽  
M. Villacis ◽  
D. Jacobsen ◽  
...  
Keyword(s):  
Time Series ◽  
Water Depth ◽  
Water Pressure ◽  
Methodological Approach ◽  
Technical Note ◽  
High Mountain ◽  
Tropical Andes ◽  
Glacial Meltwater ◽  
Depth Measurement ◽  
Wavelet Analyses

Abstract. Worldwide, the rapid shrinking of glaciers in response to ongoing climate change is currently modifying the glacial meltwater contribution to hydrosystems in glacierized catchments. Assessing the contribution of glacier run-off to stream discharge is therefore of critical importance to evaluate potential impact of glacier retreat on water quality and aquatic biota. This task has challenged both glacier hydrologists and ecologists over the last 20 yr due to both structural and functional complexity of the glacier-stream system interface. Here we propose a new methodological approach based on wavelet analyses on water depth time series to determine the glacial influence in glacierized catchments. We performed water depth measurement using water pressure loggers over ten months in 15 stream sites in two glacier-fed catchments in the Ecuadorian Andes (> 4000 m). We determined the global wavelet spectrum of each time series and defined the Wavelet Glacier Signal (WGS) as the ratio between the global wavelet power spectrum value at a 24 h-scale and its corresponding significance value. To test the relevance of the WGS we compared it with the percentage of the glacier cover in the catchments, a metric of glacier influence often used in the literature. We then tested whether one month data could be sufficient to reliably determine the glacial influence. As expected we found that the WGS of glacier-fed streams decreased downstream with the increasing of non-glacial tributaries. We also found that the WGS and the percentage of the glacier cover in the catchment were significantly positively correlated and that one month data was sufficient to identify and compare the glacial influence between two sites, provided that the water level time series were acquired over the same period. Furthermore, we found that our method permits to detect glacial signal in supposedly non-glacial sites, thereby evidencing glacial meltwater infiltrations. While we specifically focused on the tropical Andes in this paper, our approach to determine glacier influence would be applicable to temperate and arctic glacierized catchments. The WGS therefore appears as a powerful and cost effective tool to better understand the hydrological links between glaciers and hydrosystems and assess the consequences of rapid glacier melting.

Quantitative Retrieval of Tidal Flat Moisture Based on TM Images

2013 ◽  
Vol 448-453 ◽  
pp. 1066-1071
Author(s):  
Li Jun Yang ◽  
Ming Fei Wu ◽  
Yun Hong Zhu
Keyword(s):  
Remote Sensing ◽  
Relative Error ◽  
Tidal Flat ◽  
Spectral Characteristics ◽  
Atmospheric Correction ◽  
Maximum Error ◽  
Exponential Model ◽  
Wave Band ◽  
Gradient Distribution ◽  
Distribution Features

Based on spectrometry, the remote sensing inversion researches of the surface tidal flat moisture are conducted in combination with spectral values measured in the field and moisture measured in the laboratory. Firstly, the remote sensing images are preprocessed, including geometric correction, atmospheric correction and image enhancement. Then, the spectral characteristics of typical ground objects are analyzed to partition the whole image and separate the bare tidal flats. At last, TM5 wave band and exponential model are determined to be the best wave band and optimal model for the inversion of the bare tidal flat moisture. The experiment shows: (1)This method can help to improve the accuracy of the surface tidal flat moisture inversion, with the maximum error of moisture inversion is 3%, the relative error is 7.1% and the average relative error is 6.5%. (2)The surface tidal flat moisture is of evident gradient distribution features, which can be used as basis of tidal flat topographic survey.

scholarly journals Water depth retrieval models of East Dongting Lake, China, using GF-1 multi-spectral remote sensing images

2020 ◽  
Vol 22 ◽  
pp. e01004 ◽  
Author(s):  
Yang Nan ◽  
Li Jianhui ◽  
Mo Wenbo ◽  
Luo Wangjun ◽  
Wu Di ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Depth ◽  
Dongting Lake ◽  
Remote Sensing Images ◽  
Retrieval Models

Polarization lidar for shallow water depth measurement

2010 ◽  
Vol 49 (36) ◽  
pp. 6995 ◽  
Author(s):  
Steven Mitchell ◽  
Jeffrey P. Thayer ◽  
Matthew Hayman
Keyword(s):  
Shallow Water ◽  
Water Depth ◽  
Depth Measurement ◽  
Shallow Water Depth
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