scholarly journals Post-mission misalignment angle calibration for airborne laser scanners

2021 ◽  
Author(s):  
Wendy Anne Dillane
Keyword(s):  
Laser Pulse ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Laser Pulses ◽  
Angular Misalignment ◽  
Data Set ◽  
Point Matching ◽  
Airborne Laser ◽  
Laser Scanners ◽  
Least Squares Adjustment

An Airborne Laser Scanning (ALS) system operates by locating returned laser pulses independently from all others. Locating the returned laser pulses requires knowing precisely for each laser pulse, the aircraft position (e.g. GPS), the attitude of the aircraft (e.g. IMU), the scanner angle when the laser pulse left the sensor, and the slant range to the terrain surface for that pulse. One of the most critical errors in ALS systems is the angular misalignment between the scanner and the IMU, which is called the misalignment or boresight error. This error must be addressed before an ALS system can accurately produce data. The purpose of this thesis was to develop and test a method of estimating the small misalignment angles between the laser scanner and the combined GPS/IMU solution for position and attitude. This method is semi-automated, requires no ground control and does not re-sample the ALS data in order to match the overlapping strips of data. A computer program called Misalignment Estimator was developed to estimate the misalignment angles using a least squares adjustment. The method was tested using a data set located at the Oshawa airport and provided by Optech. The misalignment angles were estimated to be -0.0178 degrees, -0.0829 degrees and 0.0320 degrees, for roll, pitch and heading respectively. The estimation of the misalignment angles was considered to be successful. Further research into automated point matching is recommended.

scholarly journals Post-mission misalignment angle calibration for airborne laser scanners

2021 ◽  
Author(s):  
Wendy Anne Dillane
Keyword(s):  
Laser Pulse ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Laser Pulses ◽  
Angular Misalignment ◽  
Data Set ◽  
Point Matching ◽  
Airborne Laser ◽  
Laser Scanners ◽  
Least Squares Adjustment

An Airborne Laser Scanning (ALS) system operates by locating returned laser pulses independently from all others. Locating the returned laser pulses requires knowing precisely for each laser pulse, the aircraft position (e.g. GPS), the attitude of the aircraft (e.g. IMU), the scanner angle when the laser pulse left the sensor, and the slant range to the terrain surface for that pulse. One of the most critical errors in ALS systems is the angular misalignment between the scanner and the IMU, which is called the misalignment or boresight error. This error must be addressed before an ALS system can accurately produce data. The purpose of this thesis was to develop and test a method of estimating the small misalignment angles between the laser scanner and the combined GPS/IMU solution for position and attitude. This method is semi-automated, requires no ground control and does not re-sample the ALS data in order to match the overlapping strips of data. A computer program called Misalignment Estimator was developed to estimate the misalignment angles using a least squares adjustment. The method was tested using a data set located at the Oshawa airport and provided by Optech. The misalignment angles were estimated to be -0.0178 degrees, -0.0829 degrees and 0.0320 degrees, for roll, pitch and heading respectively. The estimation of the misalignment angles was considered to be successful. Further research into automated point matching is recommended.

scholarly journals FINE REGISTRATION OF KILO-STATION NETWORKS - A MODERN PROCEDURE FOR TERRESTRIAL LASER SCANNING DATA SETS

2016 ◽  
Vol XLI-B5 ◽  
pp. 485-492
Author(s):  
J.-F. Hullo
Keyword(s):  
Laser Scanning ◽  
Laser Scanner ◽  
Data Sets ◽  
Data Set ◽  
Information Models ◽  
3D Network ◽  
Laser Scanners ◽  
Building Information ◽  
Set Up ◽  
Fine Registration

We propose a complete methodology for the fine registration and referencing of kilo-station networks of terrestrial laser scanner data currently used for many valuable purposes such as 3D as-built reconstruction of Building Information Models (BIM) or industrial asbuilt mock-ups. This comprehensive target-based process aims to achieve the global tolerance below a few centimetres across a 3D network including more than 1,000 laser stations spread over 10 floors. This procedure is particularly valuable for 3D networks of indoor congested environments. In situ, the use of terrestrial laser scanners, the layout of the targets and the set-up of a topographic control network should comply with the expert methods specific to surveyors. Using parametric and reduced Gauss-Helmert models, the network is expressed as a set of functional constraints with a related stochastic model. During the post-processing phase inspired by geodesy methods, a robust cost function is minimised. At the scale of such a data set, the complexity of the 3D network is beyond comprehension. The surveyor, even an expert, must be supported, in his analysis, by digital and visual indicators. In addition to the standard indicators used for the adjustment methods, including Baarda’s reliability, we introduce spectral analysis tools of graph theory for identifying different types of errors or a lack of robustness of the system as well as <i>in fine</i> documenting the quality of the registration.

scholarly journals FINE REGISTRATION OF KILO-STATION NETWORKS - A MODERN PROCEDURE FOR TERRESTRIAL LASER SCANNING DATA SETS

2016 ◽  
Vol XLI-B5 ◽  
pp. 485-492
Author(s):  
J.-F. Hullo
Keyword(s):  
Laser Scanning ◽  
Laser Scanner ◽  
Data Sets ◽  
Data Set ◽  
Information Models ◽  
3D Network ◽  
Laser Scanners ◽  
Building Information ◽  
Set Up ◽  
Fine Registration

We propose a complete methodology for the fine registration and referencing of kilo-station networks of terrestrial laser scanner data currently used for many valuable purposes such as 3D as-built reconstruction of Building Information Models (BIM) or industrial asbuilt mock-ups. This comprehensive target-based process aims to achieve the global tolerance below a few centimetres across a 3D network including more than 1,000 laser stations spread over 10 floors. This procedure is particularly valuable for 3D networks of indoor congested environments. In situ, the use of terrestrial laser scanners, the layout of the targets and the set-up of a topographic control network should comply with the expert methods specific to surveyors. Using parametric and reduced Gauss-Helmert models, the network is expressed as a set of functional constraints with a related stochastic model. During the post-processing phase inspired by geodesy methods, a robust cost function is minimised. At the scale of such a data set, the complexity of the 3D network is beyond comprehension. The surveyor, even an expert, must be supported, in his analysis, by digital and visual indicators. In addition to the standard indicators used for the adjustment methods, including Baarda’s reliability, we introduce spectral analysis tools of graph theory for identifying different types of errors or a lack of robustness of the system as well as &lt;i&gt;in fine&lt;/i&gt; documenting the quality of the registration.

scholarly journals Boresight calibration of a terrestrial LiDAR scanning system

2021 ◽  
Author(s):  
Shahrzad Parandeh
Keyword(s):  
Mathematical Model ◽  
Laser Pulse ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Simulated Data ◽  
Laser Pulses ◽  
Three Dimensions ◽  
Measurement Unit ◽  
Scanning System ◽  
Terrestrial Lidar

Laser mapping has become quite popular in recent days due to its capability of providing information directly in three dimensions. A Terrestrial Laser Scanning (TLS) system operates by emitting and locating returned laser pulses. Locating the returned pulses requires knowing precisely for each laser pulse, the vehicle position (e.g. GPS), the attitude of the vehicle using Inertial Measurement Unit (lMU), the scanner angle when the laser pulse left the sensor, and the slant range to the surface for that pulse. One of the most critical sources of error in TLS or any other laser scanning system is the angular misalignment between the scanner and the IMU, which is called misalignment or boresight error. This error must be addressed before a TLS system can accurately produce data. The purpose of this research is to develop a method and identify the requirements for calculating the small misalignment angles between the laser scanner and the combined GPS/lMU solution for position and attitude. A mathematical model is developed in order to acquire the misalignment angles, using simulated data which consists of coordinates of target points, position of the scanner, rotation matrix of the IMU, and the product matrix (i. e. [LU., l1y, I1z]T) derived from the range and the MATLAB program which initially solves for the Projection Matrix using preset boresight angles (Rb). The equation is then rearranged to solve for the Rb as the goal is to obtain the same prearranged values that are initially used in the first part of the analysis. The calculation of the misalignment angles is considered to be successful as the prearranged Roll, Pitch, and Heading values are obtained after a few iteration, verifying that the mathematical model is sufficient for the purpose of calibrating the Terrestrial Laser Scanner.

scholarly journals Boresight calibration of a terrestrial LiDAR scanning system

2021 ◽  
Author(s):  
Shahrzad Parandeh
Keyword(s):  
Mathematical Model ◽  
Laser Pulse ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Simulated Data ◽  
Laser Pulses ◽  
Three Dimensions ◽  
Measurement Unit ◽  
Scanning System ◽  
Terrestrial Lidar

Laser mapping has become quite popular in recent days due to its capability of providing information directly in three dimensions. A Terrestrial Laser Scanning (TLS) system operates by emitting and locating returned laser pulses. Locating the returned pulses requires knowing precisely for each laser pulse, the vehicle position (e.g. GPS), the attitude of the vehicle using Inertial Measurement Unit (lMU), the scanner angle when the laser pulse left the sensor, and the slant range to the surface for that pulse. One of the most critical sources of error in TLS or any other laser scanning system is the angular misalignment between the scanner and the IMU, which is called misalignment or boresight error. This error must be addressed before a TLS system can accurately produce data. The purpose of this research is to develop a method and identify the requirements for calculating the small misalignment angles between the laser scanner and the combined GPS/lMU solution for position and attitude. A mathematical model is developed in order to acquire the misalignment angles, using simulated data which consists of coordinates of target points, position of the scanner, rotation matrix of the IMU, and the product matrix (i. e. [LU., l1y, I1z]T) derived from the range and the MATLAB program which initially solves for the Projection Matrix using preset boresight angles (Rb). The equation is then rearranged to solve for the Rb as the goal is to obtain the same prearranged values that are initially used in the first part of the analysis. The calculation of the misalignment angles is considered to be successful as the prearranged Roll, Pitch, and Heading values are obtained after a few iteration, verifying that the mathematical model is sufficient for the purpose of calibrating the Terrestrial Laser Scanner.

scholarly journals Estimation of Vegetation-Induced Flow Resistance for Hydraulic Computations Using Airborne Laser Scanning Data

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1864
Author(s):  
Peter Mewis
Keyword(s):  
Laser Scanning ◽  
Flow Resistance ◽  
Laser Scanner ◽  
Airborne Laser Scanning ◽  
Density Parameter ◽  
Vegetation Density ◽  
Airborne Laser Scanner ◽  
Airborne Laser ◽  
Bed Roughness ◽  
Available Information

The effect of vegetation in hydraulic computations can be significant. This effect is important for flood computations. Today, the necessary terrain information for flood computations is obtained by airborne laser scanning techniques. The quality and density of the airborne laser scanning information allows for more extensive use of these data in flow computations. In this paper, known methods are improved and combined into a new simple and objective procedure to estimate the hydraulic resistance of vegetation on the flow in the field. State-of-the-art airborne laser scanner information is explored to estimate the vegetation density. The laser scanning information provides the base for the calculation of the vegetation density parameter ωp using the Beer–Lambert law. In a second step, the vegetation density is employed in a flow model to appropriately account for vegetation resistance. The use of this vegetation parameter is superior to the common method of accounting for the vegetation resistance in the bed resistance parameter for bed roughness. The proposed procedure utilizes newly available information and is demonstrated in an example. The obtained values fit very well with the values obtained in the literature. Moreover, the obtained information is very detailed. In the results, the effect of vegetation is estimated objectively without the assignment of typical values. Moreover, a more structured flow field is computed with the flood around denser vegetation, such as groups of bushes. A further thorough study based on observed flow resistance is needed.

scholarly journals Segmentation and Multi-Scale Convolutional Neural Network-Based Classification of Airborne Laser Scanner Data

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3347 ◽  
Author(s):  
Zhishuang Yang ◽  
Bo Tan ◽  
Huikun Pei ◽  
Wanshou Jiang
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Region Growing ◽  
Point Clouds ◽  
Classification Method ◽  
Multi Scale ◽  
Airborne Laser

The classification of point clouds is a basic task in airborne laser scanning (ALS) point cloud processing. It is quite a challenge when facing complex observed scenes and irregular point distributions. In order to reduce the computational burden of the point-based classification method and improve the classification accuracy, we present a segmentation and multi-scale convolutional neural network-based classification method. Firstly, a three-step region-growing segmentation method was proposed to reduce both under-segmentation and over-segmentation. Then, a feature image generation method was used to transform the 3D neighborhood features of a point into a 2D image. Finally, feature images were treated as the input of a multi-scale convolutional neural network for training and testing tasks. In order to obtain performance comparisons with existing approaches, we evaluated our framework using the International Society for Photogrammetry and Remote Sensing Working Groups II/4 (ISPRS WG II/4) 3D labeling benchmark tests. The experiment result, which achieved 84.9% overall accuracy and 69.2% of average F1 scores, has a satisfactory performance over all participating approaches analyzed.

scholarly journals 3D MODELS OF OBJECTS IN PROCESS OF RECONSTRUCTION

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Jovana Radović
Keyword(s):  
Laser Scanning ◽  
Laser System ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Terrestrial Laser Scanning ◽  
3D Models ◽  
Terrestrial Laser Scanner ◽  
Accurate Data ◽  
Final Model ◽  
Airborne Laser

Within the last years terrestrial and airborne laser scanning has become a powerful technique for fast and efficient three-dimensional data acquisition of different kinds of objects. Airborne laser system (LiDAR) collects accurate georeferenced data of extremely large areas very quickly while the terrestrial laser scanner produces dense and geometrically accurate data. The combination of these two segments of laser scanning provides different areas of application. One of the applications is in the process of reconstruction of objects. Objects recorded with laser scanning technology and transferred into the final model represent the basis for building an object as it was original. In this paper, there will be shown two case studies based on usage of airborne and terrestrial laser scanning and processing of the data collected by them.

scholarly journals Investigations on intra-annual elevation changes using multi-temporal airborne laser scanning data: case study Engabreen, Norway

2005 ◽  
Vol 42 ◽  
pp. 195-201 ◽  
Author(s):  
Thomas Geist ◽  
Hallgeir Elvehøy ◽  
Miriam Jackson ◽  
Johann Stötter
Keyword(s):  
Mass Balance ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Remote Sensing Data ◽  
Control Area ◽  
Airborne Laser Scanning ◽  
Time Interval ◽  
Scanner Data ◽  
Glacier Surface ◽  
Airborne Laser

AbstractKey issues of glacier monitoring are changes in glacier geometry and glacier mass. As accurate direct measurements are costly and time-consuming, the use of various remote-sensing data for glacier monitoring is explored. One technology used and described here is airborne laser scanning. The method enables the derivation of high-quality digital elevation models (DEMs) with a vertical and horizontal accuracy in the sub-metre range. Between September 2001 and August 2002, three laser scanner data acquisition flights were carried out, covering the whole area of Engabreen, Norway, and corresponding well to the measurement dates for the mass-balance year 2001/02. The data quality of the DEMs is assessed (e.g. by comparing the values with a control area which has been surveyed independently or GPS ground profiles measured during the flights). For the whole glacier, surface elevation change and consequently volume change is calculated, quantified and compared with traditional mass-balance data for the same time interval. For the winter term, emergence/submergence velocity is determined from laser scanner data and snow-depth data and is compared with velocity measurements at stakes. The investigations reveal the high potential of airborne laser scanning for measuring the extent and the topography of glaciers as well as changes in geometry (Δarea, Δvolume).

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