Characterization of environmental loads related concrete pavement deflection behavior using Light Detection and Ranging technology

\nThe atmospheric monitoring is very important for the observation of air shower by air fluorescence technique.\nIn the Telescope Array (TA) experiment, LIDAR (LIght Detection And Ranging) system and CLF (Central Laser Facility) system have been used for the measurement of atmospheric transparency. The LIDAR system is located in the southeast of TA site. The CLF is located in the center of the TA site. The usefulness of the CLF and LIDAR systems is demonstrated by analyzing the time variation of atmospheric transparency with the systems. The two atmospheric monitor systems are complementary. Therefore, monitoring efficiency is advanced by a new LIDAR system that was installed at CLF system.\nClouds are observed with CCD camera, IR camera and eye scan visual check. In addition, we have also measured atmospheric parameters at the ground level using several weather systems.\n

The beam scanner is a predominant part in the light detection and ranging (LiDAR) system to achieve three-dimensional (3D) imaging. The solid-state beam-steering device has emerged as a promising candidate technology for a beam scanner with the advantages of robustness, stability, and high scanning speed. Here we propose a frequency modulated continuous wave (FMCW) LiDAR system with an in-fiber solid-state beam scanner. A 45° tilted fiber grating (TFG) is first employed to achieve in-fiber solid-state spectral scanning in the LiDAR system. A maximum output efficiency of 93.7% is achieved with proper polarization control. A single-mode fiber is then used to fabricate a 2-cm 45° TFG, which significantly reduces the size and the cost of the beam scanner in the LiDAR system. We experimentally realize 3D imaging of targets placed at a distance of 1.2 m based on our proposed LiDAR system. In addition, the system can achieve a detection distance of 6 m with a ranging precision of 24 mm.

Temperature and moisture variations across the depth of the Portland Cement Concrete (PCC) pavements result in a unique deflection behavior which has been recognized as curling and warping of the pavements since mid-1920s. The repeated slab curvature changes due to curling and warping, when combined with traffic loading, can accelerate fatigue failures including top-down and bottom-up transverse, longitudinal, and corner cracking. It is of paramount importance to measure the magnitude of curling and warping taking place in concrete pavements in order to develop performance measures and critical threshold magnitudes as well as gain a better understanding of their relationship to diurnal and seasonal temperature/moisture changes and pavement performance. Although several approaches have been proposed for this purpose for in-service pavements, they have certain limitations which inhibit their use for routine inspection for quality control and quality assurance. The primary objective of this study is to develop an economical and simple device for measuring curling and warping in pavements with accuracy comparable to the existing methodologies. Technical requirements are identified to establish assessment criteria for the proposed device. The detailed development and evaluation results for this device are presented and discussed with a focus on achieving reliable measurements in a cost-effective manner

An overlay study was conducted of thirty jointed reinforced concrete pavements (JRCP) and thirteen continuously reinforced concrete pavements (CRCP). These pavements were selected from the Indiana primary highway system based on an experimental design for levels of major factors affected pavement performance. An analysis was made of pavement deflection; condition; serviceability; materials; thicknesses; truck traffic; latest overlay thickness; age; climate zone and subgrade type, density and moisture content. Initially, a rational analysis was planned using a back calculated material properties as suggested in the 1986 AASHTO Design Guide. However, this approach was not successful and alternate analysis procedures were utilized. The performance of asphalt overlays of concrete pavement proved to be complex. Fortunately, analysis of the database built using experimental design techniques helped to explain this complex performance. Based on the performance data several performance regimes were characterized. For example, increased overlay thickness for jointed concrete pavements on stiff foundations was characterized by a relation using a PCI subset of cracking distresses. A statistical analysis was performed on the CRCP pavement data, and an overlay model was developed. However, because of the limited range of thickness, truck, traffic, etc., the equations should be used only as a guide for determining overlay thickness. Two statistical models were developed for the JRCP sections. This first is a structural model, to be used for thin to medium-thick (6” to 9”) Portland cement concrete (PCC) pavements with thin asphalt concrete (AC) overlays. The second is a functional model, to be used with thick (>9”) PCC pavements or an PCC pavements with thick (>5”) AC overlays. A procedure has been formulated for determining which of these equations is applicable for particular AC/PCC thickness combinations.

Airborne light detection and ranging (LIDAR) system uses in many field such as military, agriculture, geology and transportation. LIDAR data acquisition consumes several gigabytes from the storage capacity of the system. So, it's necessary to reduce the on board storage capacity as well as its transmission rate. Compression of LIDAR data means reducing the amount of data required to represent the digital data acquired by LIDAR system. This is done by removing data redundancies to achieve compression. In this paper we explain LIDAR system theory and component, compare between lossy and lossless compression techniques then we discuss LIDAR data compression techniques in order to choose a suitable one for LIDAR system that gives high compression ratio with suitable processing time. In most LIDAR data compression techniques classification of LIDAR data is an important issue as a preprocessing step to simplify the data. Using more than one compression algorithms increase the compression ratio but increase the processing time as well.

Agricultural production, the main pillar of food security, is highly dependent on soil quality, and threatened by erosion processes that degrade soil quality. This article is part of a research to verify the usefulness of differential interferometric analysis on TopSAR (Terrain Observation with Progressive Scans SAR, Synthetic Aperture Radar) images to measure water and tillage erosion in small agricultural basins. For this, images from the Sentinel 1 mission are used, analyzing the deformations on the earth’s surface. The purpose of this research is to verify the accuracy of the proposed method by comparing its measures with the ones taken with the gold standard laser terrestrial LIDAR (Light Detection and Ranging) system, as well as to establish a basic step period framework that guarantees an admissible loss of coherence. The results on a pilot plot in El Molar (north of Madrid, Spain) showed that the differences lay within the range of the error associated with the very LIDAR system and showed that coherence losses correspond with the deformations measured. Given the economic and labor advantages of the differential interferometric analysis, this method could be regarded as an excellent alternative to the use of LIDAR in large-scale studies for measuring ground deformation caused by water and tillage erosion.

Portland Cement Concrete (PCC) pavement was studied with incorporation of an environmentally friendly eco-additive, sodium acetate (C2H3NaO2). This additive was added to PCC pavement in three different percentages of 2%, 4% and 6% of binder weight. For a comprehensive elucidation of the eco-additive incorporation on the performance of PCC pavement, casted samples were cured in three different environments, namely: water, outdoors and pond water. Water absorption tests, flexural and compressive strength tests after 7 and 28 days of curing were conducted and results compared with the control samples without any addition of sodium acetate. Results demonstrated a significant improvement in the impermeability, compressive strength and flexural strength of PCC pavement when sodium acetate concrete is cured in a water bath and outdoors. However, no/little improvement in the impermeability, compressive strength and flexural strength was observed in sodium acetate samples that were cured in pond water. Microstructural analysis of treated samples by using scanning electron microscopy (SEM) illustrated the strengthening effect that sodium acetate provides to the pore structure of concrete pavement.

Improving classification accuracy of airborne LiDAR intensity data by geometric calibration and radiometric correction

The advantages and limitations of the ZephIR®, a continuous‐wave, focused light detection and ranging (LiDAR) wind profiler, to observe offshore winds and turbulence characteristics were tested during a 6 month campaign at the transformer/platform of Horns Rev, the world's largest wind farm. The LiDAR system is a ground‐based sensing technique which avoids the use of high and costly meteorological masts. Three different inflow conditions were selected to perform LiDAR wind profiling. Comparisons of LiDAR mean wind speeds against cup anemometers from different masts showed high correlations for the open sea sectors and good agreement with their longitudinal turbulence characteristics. Cup anemometer mean wind speed profiles were extended with LiDAR profiles up to 161 m on each inflow sector. The extension resulted in a good profile match for the three surrounding masts. These extended profiles, averaged over all observed stabilities and surface roughness lengths, were compared to the logarithmic profile. The observed deviations were relatively small. Offshore wind farm wakes were also observed from LiDAR measurements where the wind speed deficits were detected at all LiDAR heights. Profile‐derived friction velocities and roughness lengths were compared to Charnock's sea roughness model. These average values were found to be close to the model, although the scatter of the individual estimations of sea roughness length was large. Copyright © 2008 John Wiley & Sons, Ltd.

Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LIDAR scanning

Sustainable pavement design requires a balanced consideration of economic, environmental, and social impacts. In line with Federal Highway Administration (FHWA) guidelines for sustainable roadway infrastructure, incorporating recycled materials such as reclaimed asphalt pavement (RAP), recycled pavement material (RPM), recycled asphalt shingles (RASs), and warm-mix asphalt (WMA) has been shown to reduce natural resource depletion while promoting circular construction practices. This study investigates the structural performance of Portland cement concrete (PCC) pavements constructed on RAP and RPM base layers. A series of design scenarios was modeled using site-specific laboratory and field data—particularly subgrade soil properties and climatic conditions—from El Paso and San Antonio, Texas. The analysis incorporates unsaturated soil parameters and follows the performance thresholds set by the Mechanistic-Empirical Pavement Design Guide (MEPDG). Findings indicate that concrete mixture design, pavement structure, and local weather conditions are the primary drivers of distress in jointed plain concrete pavements (JPCPs). However, subsoil characteristics have a significant impact on joint faulting in JPCP and punchout occurrences in continuously reinforced concrete pavements (CRCPs), especially in thinner sections. Notably, the use of up to 50% recycled material in the base layer had minimal adverse effects on pavement performance, underscoring its viability as a sustainable design strategy for rigid pavements.

Deterioration of concrete pavement subjected to coupled fatigue loading and hydrodynamic scouring

<p>LiDAR (Light Detection and Ranging) is a technology that provides three-dimensional point cloud data with high spatial accuracy. It is increasingly used in various applications and disciplines, including engineering. Along with other capabilities, LiDAR systems are able to record reflected backscattered energy as intensity data and measured distances to targets as range data. As the laser signal wavelength that operates in LiDAR sensors is typically in the near-infrared (NIR) spectrum, high spectral reflectance separability can be observed and a number of different materials distinguished. These capabilities have motivated researchers to study the applicability of using LiDAR range and intensity data for pavement crack extraction.</p> <p>The main goal of the present research is to examine the potential use of LiDAR range and intensity data for automated pavement crack detection. The study explores the following: a) crack detection using the two image classification logics of pixel-based and object-based image classification; b) crack detection using the Maximum Likelihood Classifier (MLC), the Random Trees Classifier (RTC), and the Support Vector Machine (SVM) classifier; c) crack detection by conducting image classification of four scenarios of multi-layer images generated from LiDAR data; and d) crack detection using LiDAR data with different point spacing.</p> <p>The experimental results indicate that the use of LiDAR data independently is effective for pavement crack detection. In addition, the results show that object-based image classification logic optimizes classification accuracy and crack detection results, and that employing SVM enhances the classification process and improves crack detection accuracy. It is also observed that using range data separately produces high accuracy for the crack detection results while the accuracy is slightly reduced when intensity data are combined with range data compared with using range data only. Furthermore, in the classification process, adding slope and aspect layers to range and intensity data decreases the accuracy of crack detection results, while increasing LiDAR data point spacing reduces crack extraction accuracy.</p>

Estimates of forest stand mean height using airborne LiDAR (light detection and ranging) instruments have been reported previously with accuracies comparable to traditional ground‐based measurements. However, the small area covered by a LiDAR sensor in a single aircraft overpass is a significant hindrance for large‐scale forest inventories. In comparison, airborne interferometric synthetic aperture radar (InSAR) systems are also able to make estimates of surface height, but the swath coverage is often far greater, typically five or ten times that of the LiDAR coverage. A set of interferometric data takes was acquired by the ESAR airborne sensor over a managed pine plantation at Thetford Forest, UK. Scattering phase centre height estimates were made from two single‐pass X‐band acquisitions and polarimetric repeat‐pass L‐band acquisitions and compared with height estimates made from a separate LiDAR acquisition. The relationship between the scattering phase centre heights and stand top heights estimated, and the accuracy of stand top height estimates estimated from InSAR and LiDAR is quantified by the root mean square error (rmse). General yield class models by the Forestry Commission (UK) were used to estimate stand top height from a GIS database used for forest management. The longer wavelength L‐band radiation penetrates deeper into the canopy than the X‐band, and the scattering phase centre height is affected by both forest structural parameters (canopy density, understorey, and gaps) and sensor parameters (look‐angle and reduced coherence through temporal and volume decorrelation). Consequently, a simple translation of scattering phase centre height into stand top height gives noisy results for L‐band, with observed rmse values between ±3.1 m in the near‐range and ±6.4 m in the far‐range. The X‐band based top height estimates are more accurate, with rmse between ±2.9 m in the near‐ and ±4.1 m in the far‐range, which can be further reduced by an empirical incidence angle correction. Stand top height estimates from LiDAR achieved an rmse of only ±2.0 m. The X‐band scattering phase centre heights have also been related to mean stand height and are comparable with heights observed from the LiDAR sensor and field measurements. An rmse of ±2.5 m for the mean stand height estimates based on the X‐band dataset was found. Finally, we briefly discuss error propagation from the use of a terrain model, here provided by the Ordnance Survey.

: Recent improvements in mechanical and optical instrumentation precision have occurred. Therefore, the removal of meteorologically caused systematic errors is now a major consideration in stellar position accuracy and in the repeatability of arrangement in positions taken during nightly observations. The two problems singled out in this report are absolute water vapor content and temperature structure measurements. The study revealed that (1) estimates of water vapor distribution with an accuracy of approximately 20% would routinely correct position errors of 0.01 of angle and (2) that knowledge of the temperature structure with an accuracy of 0.5K would remove the systematic errors caused by isopycnic tilts, which range from 0.01 up to 0.1 of angle at extreme zenith viewing angles. The study showed that a remote-sensing solution to the measurement problems of the U.S. Naval Observatory in Washington, DC, is provided by LIDAR (Light Detection and Ranging). Two major LIDAR systems that fulfill the Observatory's needs are based on Raman and DIAL (Differential Absorption Lidar) techniques. A study and review of experimental system using the DIAL and Raman techniques indicate tht a DIAL system is the recommended approach for simultaneous measurement of water vapor density and temperature. A DIAL system should be constructed to obtain ground-based vertical water vapor and temperature measurements. Further, alexandrite should be used as the lasing medium for the LIDAR system.