Airborne lidar system with variable-field-of-view receiver for water optical properties measurement

2003 ◽  
Author(s):  
Viktor I. Feygels ◽  
Yuri I. Kopilevich ◽  
Alexey I. Surkov ◽  
James K. Yungel ◽  
Michael J. Behrenfeld
Keyword(s):  
Optical Properties ◽  
Airborne Lidar ◽  
Field Of View ◽  
Lidar System ◽  
Variable Field

A study to measure optical properties of waters by oceanographic lidar with variable field-of-view

2014 ◽  
Author(s):  
Xiao-long Li ◽  
Chaofang Zhao ◽  
Zhi-shen Liu ◽  
Yong-hua Chen ◽  
Jin-jia Guo
Keyword(s):  
Optical Properties ◽  
Field Of View ◽  
Variable Field

scholarly journals Design of the Ship-Borne Multi-Wavelength Polarization Ocean Lidar System and Measurement of Seawater Optical Properties

2020 ◽  
Vol 237 ◽  
pp. 07007
Author(s):  
Qi Liu ◽  
Bingyi Liu ◽  
Songhua Wu ◽  
Jintao Liu ◽  
Kailin Zhang ◽  
...  
Keyword(s):  
Optical Properties ◽  
Attenuation Coefficient ◽  
Jiaozhou Bay ◽  
Field Of View ◽  
Optical Parameters ◽  
Ocean Optics ◽  
Lidar System ◽  
Sea Trial ◽  
Vertical Distributions ◽  
Multi Wavelength

A ship-borne multi-wavelength polarization ocean lidar system LOOP (Lidar for Ocean Optics Profiler) is introduced in detail, aiming to obtain high-precision vertical profiles of seawater optical characteristics. Based on Monte-Carlo simulation, the receiving telescope is designed with a variable field of view, producing system attenuation coefficient (Klidar) approximating the optical parameters of seawater under a different field of view and water body conditions. At first, a sea trial was conducted in Jiaozhou Bay, and the measured diffuse attenuation coefficient (Kd) of seawater was 0.3m−1, being in good agreement compared with the results measured by field instrument TriOS. Then a field campaign was organized in the South China Sea. The measurement of the seawater diffuse attenuation (Kd) was 0.035m−1. These results support the prospects that lidar, as an effective tool supplement to traditional passive ocean color remote sensing, can provide the vertical distributions of optical properties in the upper ocean.

Boresight Calibration of Airborne LiDAR System Without Ground Control Points

2012 ◽  
Vol 9 (1) ◽  
pp. 85-89 ◽  
Author(s):  
Chen Siying ◽  
Ma Hongchao ◽  
Zhang Yinchao ◽  
Zhong Liang ◽  
Xu Jixian ◽  
...  
Keyword(s):  
Airborne Lidar ◽  
Ground Control ◽  
Control Points ◽  
Lidar System ◽  
Ground Control Points

scholarly journals LIDAR BATHYMETRIC EVALUATION BASED ON SCATTERING CLASSIFICATION ALGORITHM

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 97-103
Author(s):  
J. Gao ◽  
G. Q. Zhou ◽  
H. Y. Wang ◽  
X. Zhou ◽  
Y. X. Mu ◽  
...  
Keyword(s):  
Attenuation Coefficient ◽  
Classification Algorithm ◽  
Airborne Lidar ◽  
Discrimination Factor ◽  
Actual Situation ◽  
Particle Scattering ◽  
Lidar System ◽  
Scattering Intensity ◽  
Diffuse Attenuation Coefficient ◽  
532 Nm

Abstract. The evaluation of the bathymetric capability of traditional airborne lidar system is mostly based on the formula of bathymetric capability by evaluating the diffuse attenuation coefficient (Kd). This method is derived form the assumption that the reflectance of sediment is fixed. In this study ,however,the reflectance of sediment is not fixed. Therefore, this study improves the ability of bathymetric formula, and proposes a particle scattering classification algorithm to obtain the transmissivity value. The algorithm filters the scattering modes of particles by scattering discrimination factor (q), and obtains the transmissivity values by using the scattering intensity formulas. Experiments show that, when the transmissivity is in the range of 0–1 and the average values of Kd(532 nm) are 0.1150 m−1, 0.0894 m−1 and 0.0903 m−1 in January, June and October respectively, accordingly, the bathymetric capabilities are 0–44 m, 0–61.5 m and 0–52.5 m, respectively. Compared with the original bathymetric method, these results show that the maximum bathymetric value has measured by the improved bathymetric capability formula and scattering classification algorithm has decreased under the influence of the change of sediment reflectance, and the result is more consistent with the actual situation and more accurate.

scholarly journals Airborne Waveform Lidar Simulator Using the Radiative Transfer of a Laser Pulse

2019 ◽  
Vol 9 (12) ◽  
pp. 2452 ◽  
Author(s):  
Minsu Kim
Keyword(s):  
Radiative Transfer ◽  
Laser Pulse ◽  
Accuracy Assessment ◽  
Three Dimensional ◽  
Finite Size ◽  
Airborne Lidar ◽  
Beam Divergence ◽  
System Response ◽  
Lidar System ◽  
Lidar Equation

An airborne lidar simulator creates a lidar point cloud from a simulated lidar system, flight parameters, and the terrain digital elevation model (DEM). At the basic level, the lidar simulator computes the range from a lidar system to the surface of a terrain using the geomatics lidar equation. The simple computation effectively assumes that the beam divergence is zero. If the beam spot is meaningfully large due to the large beam divergence combined with high sensor altitude, then the beam plane with a finite size interacts with a ground target in a realistic and complex manner. The irradiance distribution of a delta-pulse beam plane is defined based on laser pulse radiative transfer. The airborne lidar simulator in this research simulates the interaction between the delta-pulse and a three-dimensional (3D) object and results in a waveform. The waveform will be convoluted using a system response function. The lidar simulator also computes the total propagated uncertainty (TPU). All sources of the uncertainties associated with the position of the lidar point and the detailed geomatics equations to compute TPU are described. The boresighting error analysis and the 3D accuracy assessment are provided as examples of the application using the simulator.

scholarly journals Lidar Overlap Function Determination Using the Raman Lidar Signals

2020 ◽  
Vol 237 ◽  
pp. 07018
Author(s):  
Jaswant ◽  
Shishir Kumar Singh ◽  
Radhakrishnan S.R. ◽  
Devesh Shukla ◽  
Chhemendra Sharma
Keyword(s):  
Optical Properties ◽  
Simple Technique ◽  
Near Field ◽  
Lower Atmosphere ◽  
Raman Lidar ◽  
Lidar System ◽  
Field Range ◽  
The Mean ◽  
Overlap Factor

The determination of vertical distribution of optical properties of clouds and aerosols using the lidar system is affected by the incomplete overlap between the field of view of transmitter i.e. laser beam & the receiver in the near‐field range. Thus, the study of vertical profiles of aerosol optical properties in the lower atmosphere is erroneous without the correction of lidar overlap function. Here we have analysed the effect of overlap using a simple technique proposed by Ansmann and Wandinger to determine overlap function. We have determined the overlap factor for 5 different days of June 2016 and then calculated the mean overlap profile and determined the relative deviation of each day with respect to mean overlap factor. Results reveal that the complete overlap was achieved beyond 300 meters.

scholarly journals Direct Georeferencing for the Images in an Airborne LiDAR System by Automatic Boresight Misalignments Calibration

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5056
Author(s):  
Haichi Ma ◽  
Hongchao Ma ◽  
Ke Liu ◽  
Wenjun Luo ◽  
Liang Zhang
Keyword(s):  
Control Point ◽  
Digital Camera ◽  
Iteration Process ◽  
Airborne Lidar ◽  
Image Point ◽  
Test Field ◽  
Lidar System ◽  
Ground Control Points ◽  
Source Data ◽  
Point Set

Airborne Light Detection and Ranging (LiDAR) system and digital camera are usually integrated on a flight platform to obtain multi-source data. However, the photogrammetric system calibration is often independent of the LiDAR system and performed by the aerial triangulation method, which needs a test field with ground control points. In this paper, we present a method for the direct georeferencing of images collected by a digital camera integrated in an airborne LiDAR system by automatic boresight misalignments calibration with the auxiliary of point cloud. The method firstly uses an image matching to generate a tie point set. Space intersection is then performed to obtain the corresponding object coordinate values of the tie points, while the elevation calculated from the space intersection is replaced by the value from the LiDAR data, resulting in a new object point called Virtual Control Point (VCP). Because boresight misalignments exist, a distance between the tie point and the image point of VCP can be found by collinear equations in that image from which the tie point is selected. An iteration process is performed to minimize the distance with boresight corrections in each epoch, and it stops when the distance is smaller than a predefined threshold or the total number of epochs is reached. Two datasets from real projects were used to validate the proposed method and the experimental results show the effectiveness of the method by being evaluated both quantitatively and visually.

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