Keypoint-based deformation monitoring using a terrestrial laser scanner from a single station: Case study of a bridge pier

[EN] Terrestrial laser scanners (TLSs) offer a possibility for more automated and efficient deformation monitoring of civil engineering structures with higher spatial resolution than standard methods, as well as without the necessity of permanently installing the monitoring equipment. In such applications, scanners are usually placed so that the lines of sight are roughly aligned with the main directions of the expected deformations, and the deformations are estimated from point cloud differences between multiple epochs. This allows high sensitivity in the direction of the surface normal, but deformations along the surface are often undetected or hard to precisely quantify. In this work, we propose an algorithm based on the detection and matching of keypoints identified within TLS intensity images. This enables precise quantification of deformations along the scanned surfaces. We also present the application of the algorithm for monitoring a bridge pier of the Hochmoselbrücke in Germany, as a case study. Deformations up to about 4 cm due to thermal expansion and bending of the pier were successfully detected from scans taken throughout the day from a single location, up to 180 m from the monitored surfaces. The results agreed within a few millimeters to independent monitoring using state-of-the-art processing of TLS point clouds obtained from a different location and using a different type/brand of instrument. The newly proposed algorithm can either be used to complement existing TLS-based deformation analysis methods by adding sensitivity in certain directions, or it can be valuable as a standalone solution.Medic, T.; Ruttner, P.; Holst, C.; Wieser, A. (2023). Keypoint-based deformation monitoring using a terrestrial laser scanner from a single station: Case study of a bridge pier. En 5th Joint International Symposium on Deformation Monitoring (JISDM 2022). Editorial Universitat Politècnica de València. 167-175. https://doi.org/10.4995/JISDM2022.2022.1381216717

Estimating Dry Matter and Total Soluble Content in Apples Using a Commercial Portable Hyperspectral Imaging System

The quest for rapid, non-destructive, and precise technologies for fruit quality estimation is motivated by the needs across the whole food production chain. One of the emerging technologies fulfilling these requirements is spectral imaging. However, despite documented successes, the technology is yet to become established in commercial applications. The best results reported in the literature rely on fixed, non-portable dedicated setups, and controlled light conditions, which limits the potential use cases along the food production chain. In our study, we investigate the possibility of estimating dry matter content (DMC) and total soluble content (TSC) of store-bought apples in non-regulated indoor conditions using a commercial, portable, hand-held imaging system featuring a hyperspectral camera. The acquired images are transformed into per-fruit representative spectral profiles, pre-processed, and analyzed using partial least squares (PLS), the established method in the chemometrics community. We achieved the R2 of 0.93 for TSC and 0.91 for DMC on the test dataset, with a mean absolute error of 0.71 °Brix for TSC and 0.7% for DMC, which is comparable to the state-of-the-art results presented in the literature. These results indicate that recent instrumental developments enable the deployment of spectral imaging systems in a wider range of tasks in food production, requiring portability and allowing for less stringent control of environmental conditions.ISSN:1682-1750ISSN:2194-9034ISSN:1682-177

Towards Assessing Sandstone Surface Moisture and Degradation Level from Radiometrically Corrected TLS Intensity Data

Water is a prevalent deterioration agent for historic masonry works, especially those made of clay-bearing sandstones. To preserve cultural heritage made of sandstone, it is important to monitor, and then detect the regions with water retention or stone deterioration. To that aim, we investigate the prospects of terrestrial laser scanner (TLS) intensities for quantifying moisture in sandstone. Through a series of experiments following the drying processes of sandstone samples, we verify that TLS intensities can serve as moisture proxies for remote-sensing water retention. We identify the theoretically most suitable wavelengths, systematic effects requiring mitigation, and promising mitigation strategies. However, we also observe that the intensities are significantly affected by the type of sandstone and its level of degradation. Our results indicate that it is possible to distinguish different sandstones and levels of artificial degradation by observing and analyzing TLS-intensity time series during the drying process.ISSN:2194-9042ISSN:2194-905

Challenges and Recommendations for 3D Plant Phenotyping in Agriculture Using Terrestrial Laser Scanners

Active sensing with LiDAR, and terrestrial laser scanners (TLS) in particular, are increasingly being used in plant phenotyping for assessing structural or 3D geometrical plant traits. Although these technologies provide the unprecedented possibility for remote, non-destructive, automatable, and efficient estimation of plant geometry, their deployment does not come without challenges. In this publication, we present a systematic overview of all challenges impacting TLS-based 3D plant phenotyping. We provide actionable recommendations for the end users of the technology, as well as the research questions and possible directions that can contribute the most to resolving these challenges. We specifically focus on TLSs, as we detected a lack in the existing literature dedicated to this sensing system providing a unique compromise between data quality and resolution vs. measurement efficiency and covered volume. The presented discussions are based on the literature review and our own experience in estimating the structural traits of sugar beet and wheat in plant phenotyping experiments.ISSN:2194-9042ISSN:2194-905

Towards Wheat Yield Estimation in Plant Breeding from Inhomogeneous Lidar Point Clouds Using Stochastic Features

The world relies heavily on wheat, corn, and rice for nutrition, with global challenges such as population growth and climate change threatening food security. To tackle this, plant breeding, supported by digital technologies, focuses on improving food quality and quantity. Currently, crop yield estimation uses indirect observations through hyperspectral data and spectral indices, such as NDVI, which suffer from low sensitivity in breeding scenarios. Terrestrial laser scanners (TLS) present an alternative, allowing observations of the quantity and morphology of wheat ears from point clouds, which are directly linked to grain yield. However, exploiting these observations under field conditions presents challenges, mainly due to reduced resolution and non-homogenous properties of point clouds. In response, we propose an approach for in-field wheat yield estimation using machine learning and stochastic features of TLS point clouds that are specifically handcrafted to be less sensitive to the abovementioned phenomena. This approach avoids the need for explicit 3D reconstruction of individual plants and plant organs. Our initial results show limited success in yield estimation when posed as a regression problem. However, when framed as a classification problem focusing on detecting top- and bottom-performing plant phenotypes, we achieved a promising accuracy of 84.4% and AUC of 0.93. While encouraging, these are only the first results under relaxed conditions and further work is needed to enhance practical applicability.ISSN:1682-1750ISSN:2194-9034ISSN:1682-177

Keypoint-based deformation monitoring using a terrestrial laser scanner from a single station: Case study of a bridge pier

errestrial laser scanners (TLSs) offer a possibility for more automated and efficient deformation monitoring of civil engineering structures with higher spatial resolution than standard methods, as well as without the necessity of permanently installing the monitoring equipment. In such applications, scanners are usually placed so that the lines of sight are roughly aligned with the main directions of the expected deformations, and the deformations are estimated from point cloud differences between multiple epochs. This allows high sensitivity in the direction of the surface normal, but deformations along the surface are often undetected or hard to precisely quantify. In this work, we propose an algorithm based on the detection and matching of keypoints identified within TLS intensity images. This enables precise quantification of deformations along the scanned surfaces. We also present the application of the algorithm for monitoring a bridge pier of the Hochmoselbrücke in Germany, as a case study. Deformations up to about 4 cm due to thermal expansion and bending of the pier were successfully detected from scans taken throughout the day from a single location, up to 180 m from the monitored surfaces. The results agreed within a few millimeters to independent monitoring using state-of-the-art processing of TLS point clouds obtained from a different location and using a different type/brand of instrument. The newly proposed algorithm can either be used to complement existing TLS-based deformation analysis methods by adding sensitivity in certain directions, or it can be valuable as a standalone solution

Decreasing the Uncertainty of the Target Center Estimation at Terrestrial Laser Scanning by Choosing the Best Algorithm and by Improving the Target Design

During the registration and georeferencing of terrestrial laser scans, it is common to use targets to mark discrete points. To improve the accuracy of the registration, the uncertainties of the target center estimation (TCE) have to be minimized. The present study examines different factors influencing the precision of the TCE. Here, the focus is on the algorithm and the target design. It is determined that, in general, the uncertainties of the TCE are much smaller than those indicated by the manufacturers. By comparing different algorithms for the first time, it was possible to clearly determine that an algorithm using image correlations yields the smallest standard deviations for the TCE. A comparison of different target designs could not identify an ideal commercially available target. For this reason, a new target, the BOTA8 (BOnn TArget with 8-fold pattern) was developed, which leads to smaller standard deviations than the previous targets. By choosing the best algorithm and improving the target design, standard deviations of 0.5 mm in distance direction and 1.2 arcsec in angular direction for a scan distance up to 100 m were achieved with the laser scanner Leica ScanStation P20. The uncertainties could be reduced by several millimetres and angular seconds compared to the manufacturer’s targets and software

Vibration monitoring of a bridge using 2D profile laser scanning: Lessons learned from the comparison of two spatio-temporal processing strategies

Profile laser scanning allows sub-millimeter precise contact-free measurements with high spatial and temporal resolution. That makes it an appealing solution for structural health monitoring focusing on vibrations of engineering structures, such as the analysis of eigenmodes and eigenfrequencies of bridges. In this work, we use the profile scanning mode of a Zoller+Fröhlich Imager 5016 terrestrial laser scanner (TLS) to observe bridge dynamics, focusing on the free decay processes following trains passing the bridge and exciting the structure. We compare two vibration monitoring strategies and implement an open-source semi-automatic software that integrates both approaches. We successfully estimate a spatio-temporal vibration model (including dampening coefficient) despite the maximum vibration amplitude reaching only 0.3 mm during the free decay process. Both strategies allow the estimation of the first eigenfrequency with a precision better than 0.1 Hz. Within the paper, we highlight the advantages and tackle the identified challenges of these vibration monitoring strategies. We also report on a preliminary investigation of appropriate instrument positioning for estimating the parameters of a spatio-temporal vibration model

Assessing the alignment between geometry and colors in TLS colored point

The integration of the color information from RGB cameras with the point cloud geometry is used in numerous applications. However, little attention has been paid on errors that occur when aligning colors to points in terrestrial laser scanning (TLS) point clouds. Such errors may impact the performance of algorithms that utilize colored point clouds. Herein, we propose a procedure for assessing the alignment between the TLS point cloud geometry and colors. The procedure is based upon identifying artificial targets observed in both LiDAR-based point cloud intensity data and camera-based RGB data, and quantifying the quality of the alignment using differences between the target center coordinates estimated separately from these two data sources. Experimental results with eight scanners show that the quality of the alignment depends on the scanner, the software used for colorizing the point clouds, and may change with changing environmental conditions. While we found the effects of misalignment to be negligible for some scanners, they exhibited clearly systematic patterns exceeding the beam divergence, image and scan resolution for four of the scanners. The maximum deviations were about 2 mrad perpendicular to the line-of-sight when colorizing the point clouds with the respective manufacturer’s software or scanner in-built functions, while they were up to about 5 mrad when using a different software. Testing the alignment quality, e.g., using the approach presented herein, is thus important for applications requiring accurate alignment of the RGB colors with the point cloud geometry.ISSN:2194-9042ISSN:2194-905

Vibration monitoring of a bridge using 2D profile laser scanning: Lessons learned from the comparison of two spatio-temporal processing strategies

[EN] Profile laser scanning allows sub-millimeter precise contact-free measurements with high spatial and temporal resolution. That makes it an appealing solution for structural health monitoring focusing on vibrations of engineering structures, such as the analysis of eigenmodes and eigenfrequencies of bridges. In this work, we use the profile scanning mode of a Zoller+Fröhlich Imager 5016 terrestrial laser scanner (TLS) to observe bridge dynamics, focusing on the free decay processes following trains passing the bridge and exciting the structure. We compare two vibration monitoring strategies and implement an open-source semi-automatic software that integrates both approaches. We successfully estimate a spatio-temporal vibration model (including dampening coefficient) despite the maximum vibration amplitude reaching only 0.3 mm during the free decay process. Both strategies allow the estimation of the first eigenfrequency with a precision better than 0.1 Hz. Within the paper, we highlight the advantages and tackle the identified challenges of these vibration monitoring strategies. We also report on a preliminary investigation of appropriate instrument positioning for estimating the parameters of a spatio-temporal vibration model.Meyer, N.; Schmid, L.; Wieser, A.; Medic, T. (2023). Vibration monitoring of a bridge using 2D profile laser scanning: Lessons learned from the comparison of two spatio-temporal processing strategies. Editorial Universitat Politècnica de València. 177-184. https://doi.org/10.4995/JISDM2022.2022.1381317718