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Journal articles on the topic 'Automated lidar'

Author: Grafiati

Published: 2 June 2025

Last updated: 19 July 2025

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1

Thorsen, Tyler J., and Qiang Fu. "Automated Retrieval of Cloud and Aerosol Properties from the ARM Raman Lidar. Part II: Extinction." Journal of Atmospheric and Oceanic Technology 32, no. 11 (2015): 1999–2023. http://dx.doi.org/10.1175/jtech-d-14-00178.1.

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AbstractA feature detection and extinction retrieval (FEX) algorithm for the Atmospheric Radiation Measurement Program’s (ARM) Raman lidar (RL) has been developed. Presented here is Part II of the FEX algorithm: the retrieval of cloud and aerosol extinction profiles. The directly retrieved extinction profiles using the Raman method are supplemented by other retrieval methods developed for elastic backscatter lidars. Portions of features where the extinction-to-backscatter ratios (i.e., lidar ratios) can be obtained are used to infer the lidar ratios for the regions where no such estimate can b

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Xue, Yuquan, Liming Wang, and Longmei Li. "Research on Automatic Recharging Technology for Automated Guided Vehicles Based on Multi-Sensor Fusion." Applied Sciences 14, no. 19 (2024): 8606. http://dx.doi.org/10.3390/app14198606.

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Automated guided vehicles (AGVs) play a critical role in indoor environments, where battery endurance and reliable recharging are essential. This study proposes a multi-sensor fusion approach that integrates LiDAR, depth cameras, and infrared sensors to address challenges in autonomous navigation and automatic recharging. The proposed system overcomes the limitations of LiDAR’s blind spots in near-field detection and the restricted range of vision-based navigation. By combining LiDAR for precise long-distance measurements, depth cameras for enhanced close-range visual positioning, and infrared

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Jamali, A., P. Kumar, and A. Abdul Rahman. "AUTOMATED EXTRACTION OF BUILDINGS FROM AERIAL LIDAR POINT CLOUDS AND DIGITAL IMAGING DATASETS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W16 (October 1, 2019): 303–8. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w16-303-2019.

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Abstract. To acquire 3D geospatial information, LiDAR technology provides the rapid, continuous and cost-effective capability. In this paper, two automated approaches for extracting building features from the integrated aerial LiDAR point cloud and digital imaging datasets are proposed. The assumption of the two approaches is that the LiDAR data can be used to distinguish between high- and low-rise objects while the multispectral dataset can be used to filter out vegetation from the data. Object-based image analysis techniques are applied to the extracted building objects. The two automated bu

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Widyaningrum, E., and B. G. H. Gorte. "CHALLENGES AND OPPORTUNITIES: ONE STOP PROCESSING OF AUTOMATIC LARGE-SCALE BASE MAP PRODUCTION USING AIRBORNE LIDAR DATA WITHIN GIS ENVIRONMENT. CASE STUDY: MAKASSAR CITY, INDONESIA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W1 (May 31, 2017): 365–69. http://dx.doi.org/10.5194/isprs-archives-xlii-1-w1-365-2017.

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LiDAR data acquisition is recognized as one of the fastest solutions to provide basis data for large-scale topographical base maps worldwide. Automatic LiDAR processing is believed one possible scheme to accelerate the large-scale topographic base map provision by the Geospatial Information Agency in Indonesia. As a progressive advanced technology, Geographic Information System (GIS) open possibilities to deal with geospatial data automatic processing and analyses. Considering further needs of spatial data sharing and integration, the one stop processing of LiDAR data in a GIS environment is c

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Lee, Hyunsuk, and Woojin Chung. "Extrinsic Calibration of Multiple 3D LiDAR Sensors by the Use of Planar Objects." Sensors 22, no. 19 (2022): 7234. http://dx.doi.org/10.3390/s22197234.

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Three-dimensional light detection and ranging (LiDAR) sensors have received much attention in the field of autonomous navigation owing to their accurate, robust, and rich geometric information. Autonomous vehicles are typically equipped with multiple 3D LiDARs because there are many commercially available low-cost 3D LiDARs. Extrinsic calibration of multiple LiDAR sensors is essential in order to obtain consistent geometric information. This paper presents a systematic procedure for the extrinsic calibration of multiple 3D LiDAR sensors using plane objects. At least three independent planes ar

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Yamamoto, T., and M. Nakagawa. "MERGING AIRBORNE LIDAR DATA AND SATELLITE SAR DATA FOR BUILDING CLASSIFICATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-4/W5 (May 13, 2015): 227–32. http://dx.doi.org/10.5194/isprsarchives-xl-4-w5-227-2015.

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A frequent map revision is required in GIS applications, such as disaster prevention and urban planning. In general, airborne photogrammetry and LIDAR measurements are applied to geometrical data acquisition for automated map generation and revision. However, attribute data acquisition and classification depend on manual editing works including ground surveys. In general, airborne photogrammetry and LiDAR measurements are applied to geometrical data acquisition for automated map generation and revision. However, these approaches classify geometrical attributes. Moreover, ground survey and manu

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Gupta, Himanshu, Henrik Andreasson, Achim J. Lilienthal, and Polina Kurtser. "Robust Scan Registration for Navigation in Forest Environment Using Low-Resolution LiDAR Sensors." Sensors 23, no. 10 (2023): 4736. http://dx.doi.org/10.3390/s23104736.

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Automated forest machines are becoming important due to human operators’ complex and dangerous working conditions, leading to a labor shortage. This study proposes a new method for robust SLAM and tree mapping using low-resolution LiDAR sensors in forestry conditions. Our method relies on tree detection to perform scan registration and pose correction using only low-resolution LiDAR sensors (16Ch, 32Ch) or narrow field of view Solid State LiDARs without additional sensory modalities like GPS or IMU. We evaluate our approach on three datasets, including two private and one public dataset, and d

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Creek, Tristan, and Barry Mullins. "Analysis of Image Thresholding Algorithms for Automated Machine Learning Training Data Generation." International Conference on Cyber Warfare and Security 17, no. 1 (2022): 449–58. http://dx.doi.org/10.34190/iccws.17.1.57.

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Secured compounds often safeguard physical layout details of both internal and external facilities, but these details are at risk due to the growing inclusion of Light Detection and Ranging (LiDAR) sensors in consumer off-the-shelf (COTS) technology such as cell phones. The ability to record detailed distance data with cell phones facilitates the production of high-quality three-dimensional scans in a discrete manner which directly threatens the security of private compounds. Therefore, it behooves the organizations in charge of private compounds to detect LiDAR activity. Many security cameras

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Thorsen, Tyler J., Qiang Fu, Rob K. Newsom, David D. Turner, and Jennifer M. Comstock. "Automated Retrieval of Cloud and Aerosol Properties from the ARM Raman Lidar. Part I: Feature Detection." Journal of Atmospheric and Oceanic Technology 32, no. 11 (2015): 1977–98. http://dx.doi.org/10.1175/jtech-d-14-00150.1.

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AbstractA feature detection and extinction retrieval (FEX) algorithm for the Atmospheric Radiation Measurement Program’s (ARM) Raman lidar (RL) has been developed. Presented here is Part I of the FEX algorithm: the detection of features including both clouds and aerosols. The approach of FEX is to use multiple quantities— scattering ratios derived using elastic and nitrogen channel signals from two fields of view, the scattering ratio derived using only the elastic channel, and the total volume depolarization ratio—to identify features using range-dependent detection thresholds. FEX is designe

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Vaughan, Mark A., Kathleen A. Powell, David M. Winker, et al. "Fully Automated Detection of Cloud and Aerosol Layers in the CALIPSO Lidar Measurements." Journal of Atmospheric and Oceanic Technology 26, no. 10 (2009): 2034–50. http://dx.doi.org/10.1175/2009jtecha1228.1.

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Abstract Accurate knowledge of the vertical and horizontal extent of clouds and aerosols in the earth’s atmosphere is critical in assessing the planet’s radiation budget and for advancing human understanding of climate change issues. To retrieve this fundamental information from the elastic backscatter lidar data acquired during the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a selective, iterated boundary location (SIBYL) algorithm has been developed and deployed. SIBYL accomplishes its goals by integrating an adaptive context-sensitive profile scanne

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Moreno, Hugo, Constantino Valero, José María Bengochea-Guevara, Ángela Ribeiro, Miguel Garrido-Izard, and Dionisio Andújar. "On-Ground Vineyard Reconstruction Using a LiDAR-Based Automated System." Sensors 20, no. 4 (2020): 1102. http://dx.doi.org/10.3390/s20041102.

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Crop 3D modeling allows site-specific management at different crop stages. In recent years, light detection and ranging (LiDAR) sensors have been widely used for gathering information about plant architecture to extract biophysical parameters for decision-making programs. The study reconstructed vineyard crops using light detection and ranging (LiDAR) technology. Its accuracy and performance were assessed for vineyard crop characterization using distance measurements, aiming to obtain a 3D reconstruction. A LiDAR sensor was installed on-board a mobile platform equipped with an RTK-GNSS receive

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Li, Shuangping, Bin Zhang, Junxing Zheng, Dong Wang, and Zuqiang Liu. "Development of Automated 3D LiDAR System for Dimensional Quality Inspection of Prefabricated Concrete Elements." Sensors 24, no. 23 (2024): 7486. http://dx.doi.org/10.3390/s24237486.

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The dimensional quality inspection of prefabricated concrete (PC) elements is crucial for ensuring overall assembly quality and enhancing on-site construction efficiency. However, current practices remain heavily reliant on manual inspection, which results in high operator dependency and low efficiency. Existing Light Detection and Ranging (LiDAR)-based methods also require skilled professionals for scanning and subsequent point cloud processing, thereby presenting technical challenges. This study developed a 3D LiDAR system for the automatic identification and measurement of the dimensional q

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YAMADA, Hitoshi, and Kenichi YANAI. "LIDAR and Laser Technologies for Automated Driving." Review of Laser Engineering 48, no. 2 (2020): 78. http://dx.doi.org/10.2184/lsj.48.2_78.

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Gargoum, Suliman, Karim El-Basyouny, Joseph Sabbagh, and Kenneth Froese. "Automated Highway Sign Extraction Using Lidar Data." Transportation Research Record: Journal of the Transportation Research Board 2643, no. 1 (2017): 1–8. http://dx.doi.org/10.3141/2643-01.

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Traffic signs are integral elements of any transportation network; however, keeping records of those signs and their condition is a tedious, time-consuming, and labor-intensive process. As a result, many agencies worldwide have been working toward automating the process. One form of automation uses remote sensing techniques to extract traffic sign information. An algorithm is proposed that can automatically extract traffic signs from mobile light detection and ranging data. After the number of signs on a road segment has been determined, the coordinates of those signs are mapped onto the road

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Sun, Yusen, Xingji Jin, Timo Pukkala, and Fengri Li. "A Comparison of Four Methods for Automatic Delineation of Tree Stands from Grids of LiDAR Metrics." Remote Sensing 14, no. 24 (2022): 6192. http://dx.doi.org/10.3390/rs14246192.

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Increased use of laser scanning in forest inventories is leading to the adoption and development of automated stand delineation methods. The most common categories of these methods are region merging and region growing. However, recent literature proposes alternative methods that are based on the ideas of cellular automata, self-organizing maps, and combinatorial optimization. The studies where these methods have been described suggest that the new methods are potential options for the automated segmentation of a forest into homogeneous stands. However, no studies are available that compare th

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Churnside, James H., Eirik Tenningen, and James J. Wilson. "Comparison of data-processing algorithms for the lidar detection of mackerel in the Norwegian Sea." ICES Journal of Marine Science 66, no. 6 (2009): 1023–28. http://dx.doi.org/10.1093/icesjms/fsp026.

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Abstract Churnside, J. H., Tenningen, E., and Wilson, J. J. 2009. Comparison of data-processing algorithms for the lidar detection of mackerel in the Norwegian Sea. – ICES Journal of Marine Science, 66: 1023–1028. A broad-scale lidar survey was conducted in the Norwegian Sea in summer 2002. Since then, various data-processing techniques have been developed, including manual identification of fish schools, multiscale median filtering, and curve fitting of the lidar profiles. In the automated techniques, applying a threshold to the data, as carrried out already to eliminate plankton scattering,

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Brooks, Rheannon, Trisalyn Nelson, Krista Amolins, and G. Brent Hall. "Semi-Automated Building Footprint Extraction From Orthophotos." GEOMATICA 69, no. 2 (2015): 231–44. http://dx.doi.org/10.5623/cig2015-206.

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Here we describe and apply a semi-automated, object-based method for extracting vector-building footprint polygons from aerial photographs (orthophotos) within urban settings. The approach integrates the use of high resolution orthophotos and image segmentation software and is compared with methods using Light Detection and Ranging (LiDAR) as the source data input. LiDAR data gives the best results with less processing, but is not widely used by municipalities due to the expense. Results from semi-automated image segmentation of the orthophotos showed a high accuracy between extracted building

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Miao, Jilong, Ping Wang, Xinhong Wang, and Fuqiang Liu. "Research on automated annotation technology for radar range-angle-doppler data based on visual supervision mechanism." Journal of Physics: Conference Series 2991, no. 1 (2025): 012004. https://doi.org/10.1088/1742-6596/2991/1/012004.

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Abstract With the development of autonomous driving technology, vehicles integrate camera, lidar, and radar modules for environment perception. In mass-produced models, cameras and lidars mostly serve as primary sensors, while radar is mainly limited to distance detection and collision prevention. Given radar’s unique working principle, it potentially offers stronger sensing capabilities. However, its signals are hard to process and annotate, and relevant research lacks sufficient dataset support. This study presents a method for processing radar raw signals and proposes an image-supervised au

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Baars, H., A. Ansmann, R. Engelmann, and D. Althausen. "Continuous monitoring of the boundary-layer top with lidar." Atmospheric Chemistry and Physics 8, no. 23 (2008): 7281–96. http://dx.doi.org/10.5194/acp-8-7281-2008.

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Abstract. Continuous lidar observations of the top height of the boundary layer (BL top) have been performed at Leipzig (51.3° N, 12.4° E), Germany, since August 2005. The results of measurements taken with a compact, automated Raman lidar over a one–year period (February 2006 to January 2007) are presented. Main goals of the study are (a) to demonstrate that BL top monitoring with lidar throughout the year is possible, (b) to present the required data analysis method that permits an automated, robust retrieval of BL top at all weather situations, and (c) to use this opportunity to compare the

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O'Dea, Annika, Katherine L. Brodie, and Preston Hartzell. "Continuous Coastal Monitoring with an Automated Terrestrial Lidar Scanner." Journal of Marine Science and Engineering 7, no. 2 (2019): 37. http://dx.doi.org/10.3390/jmse7020037.

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This paper details the collection, geo-referencing, and data processing algorithms for a fully-automated, permanently deployed terrestrial lidar system for coastal monitoring. The lidar is fixed on a 4-m structure located on a shore-backing dune in Duck, North Carolina. Each hour, the lidar collects a three-dimensional framescan of the nearshore region along with a 30-min two-dimensional linescan time series oriented directly offshore, with a linescan repetition rate of approximately 7 Hz. The data are geo-referenced each hour using a rigorous co-registration process that fits 11 fixed planes

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Di Paolantonio, Marco, Davide Dionisi, and Gian Luigi Liberti. "A semi-automated procedure for the emitter–receiver geometry characterization of motor-controlled lidars." Atmospheric Measurement Techniques 15, no. 5 (2022): 1217–31. http://dx.doi.org/10.5194/amt-15-1217-2022.

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Abstract. To correctly understand and interpret lidar-acquired signals and to provide high-quality data, the characterization of the lidar transmitter–receiver geometry is required. For example, being fundamental to correctly align lidar systems, this characterization is useful to improve the efficiency of the alignment procedure. In addition, some applications (e.g. air quality monitoring) need to quantitatively interpret the observations even in the range where the overlap between the telescope field of view and the laser beam is incomplete. This is generally accomplished by correcting for t

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Kinzig, Christian, Markus Horn, Martin Lauer, Michael Buchholz, Christoph Stiller, and Klaus Dietmayer. "Automatic multimodal sensor calibration of the UNICARagil vehicles." tm - Technisches Messen 89, no. 4 (2022): 289–99. http://dx.doi.org/10.1515/teme-2021-0110.

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Abstract Automated vehicles rely on a precise intrinsic and extrinsic calibration of all sensors. An exact calibration leads to accurate localization and object detection results. Especially for sensor data fusion, the transformation between different sensor frames must be well known. Moreover, modular and redundant platforms require a large number of sensors to cover their full surroundings. This makes the calibration process complex and challenging. In this article, we describe the procedure to calibrate the full sensor setup of a modular autonomous driving platform, consisting of camera, li

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Barnwal, Surbhi, Mansi Koshti, and Salil Goel. "Automated Pipeline for Multi-LiDAR Extrinsic Calibration: Experimental Evaluation and Performance Analysis." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-4-2024 (October 18, 2024): 37–44. http://dx.doi.org/10.5194/isprs-annals-x-4-2024-37-2024.

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Abstract. In recent years, 3D LiDAR (Light Detection and Ranging) has become a crucial sensor in various applications such as autonomous vehicles, robotics, object detection, precision forestry, and agriculture. However, specific LiDAR sensors, such as Velodyne VLP16, exhibit some drawbacks, such as a limited field of view and sparse data density, making them inadequate for certain specific applications. Hence, this research proposes a method for calibrating two VLP16 LiDAR sensors to improve coverage and reduce blind spots. The pipeline for performing the calibration begins with mounting LiDA

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Brown, Kyle M., Crispin H. Hambidge, and Jonathan M. Brownett. "Progress in operational flood mapping using satellite synthetic aperture radar (SAR) and airborne light detection and ranging (LiDAR) data." Progress in Physical Geography: Earth and Environment 40, no. 2 (2016): 196–214. http://dx.doi.org/10.1177/0309133316633570.

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During flooding, operational tools for mapping flood extent and depth of water in flood-prone areas are required by those planning emergency response, including UK statutory agencies such as the Environment Agency. Satellite data have become a source of information to map and monitor floods, but many of the methods developed to process the data are unsuitable for accurate, near real-time production of flood information products. This paper describes a new semi-automated methodology developed to provide operational mapping of flood extent and flood depth using satellite synthetic aperture radar

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Benkert, Johannes, Robert Maack, and Tobias Meisen. "Chances and Challenges: Transformation from a Laser-Based to a Camera-Based Container Crane Automation System." Journal of Marine Science and Engineering 11, no. 9 (2023): 1718. http://dx.doi.org/10.3390/jmse11091718.

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In recent years, a steady increase in maritime business and annual container throughput has been recorded. To meet this growing demand, terminal operators worldwide are turning to automated container handling. For the automated operation of a crane, a reliable capture of the environment is required. In current state-of-the-art applications this is mostly achieved with light detection and ranging (LiDAR) sensors. These sensors enable precise three-dimensional sampling of the surroundings, even at great distances. However, the use of LiDAR sensors has a number of disadvantages, such as high acqu

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Voudouri, Kalliopi Artemis, Nikolaos Siomos, Konstantinos Michailidis, et al. "Comparison of two automated aerosol typing methods and their application to an EARLINET station." Atmospheric Chemistry and Physics 19, no. 16 (2019): 10961–80. http://dx.doi.org/10.5194/acp-19-10961-2019.

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Abstract. In this study we apply and compare two algorithms for the automated aerosol-type characterization of the aerosol layers derived from Raman lidar measurements over the EARLINET station of Thessaloniki, Greece. Both automated aerosol-type characterization methods base their typing on lidar-derived aerosol-intensive properties. The methodologies are briefly described and their application to three distinct cases is demonstrated and evaluated. Then the two classification schemes were applied in the automatic mode to a more extensive dataset. The dataset analyzed corresponds to ACTRIS/EAR

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Ramalho de Oliveira, Luiz Felipe, H. Andrew Lassiter, Ben Wilkinson, et al. "Moving to Automated Tree Inventory: Comparison of UAS-Derived Lidar and Photogrammetric Data with Manual Ground Estimates." Remote Sensing 13, no. 1 (2020): 72. http://dx.doi.org/10.3390/rs13010072.

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Unmanned aircraft systems (UAS) have advanced rapidly enabling low-cost capture of high-resolution images with cameras, from which three-dimensional photogrammetric point clouds can be derived. More recently UAS equipped with laser scanners, or lidar, have been employed to create similar 3D datasets. While airborne lidar (originally from conventional aircraft) has been used effectively in forest systems for many years, the ability to obtain important tree features such as height, diameter at breast height, and crown dimensions is now becoming feasible for individual trees at reasonable costs t

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Zhang, J., W. Jiang, and S. Jiang. "AUTOMATED MOUNTING BIAS CALIBRATION FOR AIRBORNE LIDAR SYSTEM." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences I-4 (July 20, 2012): 263–68. http://dx.doi.org/10.5194/isprsannals-i-4-263-2012.

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Deshpande, Sagar S., Mike Falk, and Nathan Plooster. "Semi-Automated Roller Parameters Extraction from Terrestrial Lidar." Photogrammetric Engineering & Remote Sensing 87, no. 12 (2021): 879–90. http://dx.doi.org/10.14358/pers.21-00005r2.

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Rollers are an integral part of a hot-rolling steel mill. They transport hot metal from one end of the mill to another. The quality of the steel highly depends on the surface quality of the rollers. This paper presents semi-automated methodologies to extract roller parameters from terrestrial lidar points. The procedure was divided into two steps. First, the three-dimensional points were converted to a two-dimensional image to detect the extents of the rollers using fast Fourier transform image matching. Lidar points for every roller were iteratively fitted to a circle. The radius and center o

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Lindenthal, S. M., V. R. Ussyshkin, J. G. Wang, and M. Pokorny. "AIRBORNE LIDAR: A FULLY-AUTOMATED SELF-CALIBRATION PROCEDURE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII-5/W12 (September 3, 2012): 73–78. http://dx.doi.org/10.5194/isprsarchives-xxxviii-5-w12-73-2011.

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Thornton, Douglas A., Keith Redmill, and Benjamin Coifman. "Automated parking surveys from a LIDAR equipped vehicle." Transportation Research Part C: Emerging Technologies 39 (February 2014): 23–35. http://dx.doi.org/10.1016/j.trc.2013.11.014.

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Ludwig, Jürgen. "Development Potentials of Lidar Sensors for Automated Vehicles." ATZelectronics worldwide 14, no. 4 (2019): 40–43. http://dx.doi.org/10.1007/s38314-019-0017-5.

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Muckenhuber, Stefan, Hannes Holzer, and Zrinka Bockaj. "Automotive Lidar Modelling Approach Based on Material Properties and Lidar Capabilities." Sensors 20, no. 11 (2020): 3309. http://dx.doi.org/10.3390/s20113309.

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Development and validation of reliable environment perception systems for automated driving functions requires the extension of conventional physical test drives with simulations in virtual test environments. In such a virtual test environment, a perception sensor is replaced by a sensor model. A major challenge for state-of-the-art sensor models is to represent the large variety of material properties of the surrounding objects in a realistic manner. Since lidar sensors are considered to play an essential role for upcoming automated vehicles, this paper presents a new lidar modelling approach

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Parmehr, Ebadat G., Marco Amati, and Clive S. Fraser. "MAPPING URBAN TREE CANOPY COVER USING FUSED AIRBORNE LIDAR AND SATELLITE IMAGERY DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-7 (June 7, 2016): 181–86. http://dx.doi.org/10.5194/isprsannals-iii-7-181-2016.

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Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shap

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Parmehr, Ebadat G., Marco Amati, and Clive S. Fraser. "MAPPING URBAN TREE CANOPY COVER USING FUSED AIRBORNE LIDAR AND SATELLITE IMAGERY DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-7 (June 7, 2016): 181–86. http://dx.doi.org/10.5194/isprs-annals-iii-7-181-2016.

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Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shap

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Van Nieuwenhuizen, Nigel, John B. Lindsay, and Ben DeVries. "Automated Mapping of Transportation Embankments in Fine-Resolution LiDAR DEMs." Remote Sensing 13, no. 7 (2021): 1308. http://dx.doi.org/10.3390/rs13071308.

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Fine-resolution LiDAR DEMs can represent surface features such as road and railway embankments with high fidelity. However, transportation embankments are problematic for several environmental modelling applications, and particularly hydrological modelling. Currently, there are no automated techniques for the identification and removal of embankments from LiDAR DEMs. This paper presents a novel algorithm for identifying embankments in LiDAR DEMs. The algorithm utilizes repositioned transportation network cells as seed points in a region-growing operation. The embankment region grows based on d

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Reger, Matthias, Jörn Stumpenhausen, and Heinz Bernhardt. "Evaluation of LiDAR for the Free Navigation in Agriculture." AgriEngineering 4, no. 2 (2022): 489–506. http://dx.doi.org/10.3390/agriengineering4020033.

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Driverless transport systems (DTS) or automated guided vehicles (AGV) have been part of intralogistics for over six decades. The uniform and structured environment conditions in industrial halls provided the ideal conditions for simple automation, such as in goods transport. Initially, implementing simply-designed safety devices, e.g., bumpers, could reduce risk to an acceptable level. However, these conditions are not present in an agricultural environment. Soiling and harsh weather conditions are anticipated both indoors and outdoors. The state of the art in intralogistics are light detectio

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Dilmurat, Kamila, Vasit Sagan, Maitiniyazi Maimaitijiang, Stephen Moose, and Felix B. Fritschi. "Estimating Crop Seed Composition Using Machine Learning from Multisensory UAV Data." Remote Sensing 14, no. 19 (2022): 4786. http://dx.doi.org/10.3390/rs14194786.

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The pre-harvest estimation of seed composition from standing crops is imperative for field management practices and plant phenotyping. This paper presents for the first time the potential of Unmanned Aerial Vehicles (UAV)-based high-resolution hyperspectral and LiDAR data acquired from in-season stand crops for estimating seed protein and oil compositions of soybean and corn using multisensory data fusion and automated machine learning. UAV-based hyperspectral and LiDAR data was collected during the growing season (reproductive stage five (R5)) of 2020 over a soybean test site near Columbia, M

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Previtali, M., L. Barazzetti, and M. Scaioni. "AUTOMATED ROAD INFORMATION EXTRACTION FROM HIGH RESOLUTION AERIAL LIDAR DATA FOR SMART ROAD APPLICATIONS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 533–39. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-533-2020.

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Abstract. Automatic extraction of road features from LiDAR data is a fundamental task for different applications, including asset management. The availability of updated and reliable models is even more important in the context of smart roads. One of the main advantages of LiDAR data compared with other sensing instruments is the possibility to directly get 3D information. However, the task of deriving road networks form LiDAR data acquired with Airborne Laser Scanning (ALS) may be quite complex due to occlusions, low feature separability and shadowing from contextual objects. Indeed, even if

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Kurniawan, Tomi, and Risfendra Risfendra. "Pemetaan 2D Indoor menggunakan Automated Guided Vehicle (AGV) dengan LiDAR." JTEIN: Jurnal Teknik Elektro Indonesia 4, no. 1 (2023): 169–78. https://doi.org/10.24036/jtein.v4i1.373.

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AGV dibuat untuk proses produksi terhindar dari human error dengan keuntungan fleksibelitas dan pergerakan yang mudah. Jalur pemandu AGV pada umumnya dibuat berbentuk garis hitam dan juga terdapat RFID, hal tersebut membuat AGV tersebut tidak efektif dan merusak pemandangan ruangan. Oleh karena itu, penelitian ini bertujuan untuk membentuk suatu peta yang diketahui oleh robot dan tidak merusak pemandangan ruangan dengan menggunakan sensor LiDAR dan metode SLAM. Dengan menggunakan metode experimental untuk pengujian kelayakan LiDAR pada area sebesar 220 x 110 cm serta metode try-and-error untuk

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Wulder, Michael A., Christopher W. Bater, Nicholas C. Coops, Thomas Hilker, and Joanne C. White. "The role of LiDAR in sustainable forest management." Forestry Chronicle 84, no. 6 (2008): 807–26. http://dx.doi.org/10.5558/tfc84807-6.

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Forest characterization with light detection and ranging (LiDAR) data has recently garnered much scientific and operational attention. The number of forest inventory attributes that may be directly measured with LiDAR is limited; however, when considered within the context of all the measured and derived attributes required to complete a forest inventory, LiDAR can be a valuable tool in the inventory process. In this paper, we present the status of LiDAR remote sensing of forests, including issues related to instrumentation, data collection, data processing, costs, and attribute estimation. Th

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Baars, H., A. Ansmann, R. Engelmann, and D. Althausen. "Continuous monitoring of the boundary-layer top with lidar." Atmospheric Chemistry and Physics Discussions 8, no. 3 (2008): 10749–90. http://dx.doi.org/10.5194/acpd-8-10749-2008.

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Abstract. Continuous lidar observations of the top height of the boundary layer (BL top) have been performed at Leipzig (51.3° N, 12.4° E), Germany, since August 2005. The results of measurements taken with a compact, automated Raman lidar over a one-year period (February 2006 to January 2007) are presented. Four different methods for the determination of the BL top are discussed. The most promising technique, the wavelet covariance algorithm, is improved by implementing some modifications so that an automated, robust retrieval of BL depths from lidar data is possible. Three case studies of si

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Tarsha Kurdi, Fayez, Zahra Gharineiat, Elżbieta Lewandowicz, and Jie Shan. "Modeling the Geometry of Tree Trunks Using LiDAR Data." Forests 15, no. 2 (2024): 368. http://dx.doi.org/10.3390/f15020368.

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The effective development of digital twins of real-world objects requires sophisticated data collection techniques and algorithms for the automated modeling of individual objects. In City Information Modeling (CIM) systems, individual buildings can be modeled automatically at the second Level of Detail or LOD2. Similarly, for Tree Information Modeling (TIM) and building Forest Digital Twins (FDT), automated solutions for the 3D modeling of individual trees at different levels of detail are required. The existing algorithms support the automated modeling of trees by generating models of the can

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Duan, Cong, Haomiao Bian, Yuan Guo, Bijun Li, Maosheng Yan, and Jian Zhou. "MapCalib: Toward Large-Scale Automatic Calibration for Roadside LiDAR Using High-Definition Map." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-G-2025 (July 10, 2025): 231–38. https://doi.org/10.5194/isprs-annals-x-g-2025-231-2025.

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Abstract. Roadside LiDAR sensors are critical components in automated driving systems and mobile mapping systems. These sensors, typically deployed along roadsides to provide continuous data for perception tasks, require precise calibration to ensure the safety and performance of intelligent connected vehicles. However, large-scale deployment presents new challenges, including low sensor overlap and variability in sensor types, complicating the calibration process. To address these challenges, this study introduces Map- Calib, an innovative method for the automatic calibration of roadside LiDA

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Radenz, Martin, Patric Seifert, Holger Baars, Athena Augusta Floutsi, Zhenping Yin, and Johannes Bühl. "Automated time–height-resolved air mass source attribution for profiling remote sensing applications." Atmospheric Chemistry and Physics 21, no. 4 (2021): 3015–33. http://dx.doi.org/10.5194/acp-21-3015-2021.

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Abstract. Height-resolved air mass source attribution is crucial for the evaluation of profiling ground-based remote sensing observations, especially when using lidar (light detection and ranging) to investigate different aerosol types throughout the atmosphere. Lidar networks, such as EARLINET (European Aerosol Research Lidar Network) in the frame of ACTRIS (Aerosol, Clouds and Trace Gases), observe profiles of optical aerosol properties almost continuously, but usually, additional information is needed to support the characterization of the observed particles. This work presents an approach

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Pao, Wing Yi, Joshua Howorth, Long Li, et al. "Investigation of Automotive LiDAR Vision in Rain from Material and Optical Perspectives." Sensors 24, no. 10 (2024): 2997. http://dx.doi.org/10.3390/s24102997.

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With the emergence of autonomous functions in road vehicles, there has been increased use of Advanced Driver Assistance Systems comprising various sensors to perform automated tasks. Light Detection and Ranging (LiDAR) is one of the most important types of optical sensor, detecting the positions of obstacles by representing them as clusters of points in three-dimensional space. LiDAR performance degrades significantly when a vehicle is driving in the rain as raindrops adhere to the outer surface of the sensor assembly. Performance degradation behaviors include missing points and reduced reflec

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Zhou, Jingmeng. "A Review of LiDAR sensor Technologies for Perception in Automated Driving." Academic Journal of Science and Technology 3, no. 3 (2022): 255–61. http://dx.doi.org/10.54097/ajst.v3i3.2993.

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After more than 20 years of research, ADAS is common in modern vehicles on the market. Automated driving systems have gradually moved from the research stage to public roads for commercial testing. These systems rely on information provided by onboard sensors that describe the state of the vehicle, its environment, and other participants. The selection and placement of sensing sensors are key factors in system design. In order to better understand the principles and functional implementation of sensing sensors, this paper reviews the existing and latest sensing sensor technologies and presents

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Morille, Y., M. Haeffelin, P. Drobinski, and J. Pelon. "STRAT: An Automated Algorithm to Retrieve the Vertical Structure of the Atmosphere from Single-Channel Lidar Data." Journal of Atmospheric and Oceanic Technology 24, no. 5 (2007): 761–75. http://dx.doi.org/10.1175/jtech2008.1.

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Abstract Today several lidar networks around the world provide large datasets that are extremely valuable for aerosol and cloud research. Retrieval of atmospheric constituent properties from lidar profiles requires detailed analysis of spatial and temporal variations of the signal. This paper presents an algorithm called Structure of the Atmosphere (STRAT), which is designed to retrieve the vertical distribution of cloud and aerosol layers in the boundary layer and through the free troposphere and to identify near-particle-free regions of the vertical profile and the range at which the lidar s

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Vierhub-Lorenz, Valentin, Maximilian Kellner, Oliver Zipfel, and Alexander Reiterer. "A Study on the Effect of Multispectral LiDAR Data on Automated Semantic Segmentation of 3D-Point Clouds." Remote Sensing 14, no. 24 (2022): 6349. http://dx.doi.org/10.3390/rs14246349.

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Mobile mapping is an application field of ever-increasing relevance. Data of the surrounding environment is typically captured using combinations of LiDAR systems and cameras. The large amounts of measurement data are then processed and interpreted, which is often done automated using neural networks. For the evaluation the data of the LiDAR and the cameras needs to be fused, which requires a reliable calibration of the sensors. Segmentation solemnly on the LiDAR data drastically decreases the amount of data and makes the complex data fusion process obsolete but on the other hand often perform

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Xu, Tao, Jingjing Fan, Wenbo Chu, Li Wang, and Yan Zhao. "Person Recognition Method in Cross-Country Environment Based on Improved Euclidean Clustering." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 14 (2020): 2056011. http://dx.doi.org/10.1142/s021800142056011x.

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Automated unmanned vehicles can carry equipment for teams, greatly reducing the load of person. Most of the working environment of unmanned vehicles is in the field. The identification of persons in a cross-country environment is the basic requirement for automated driving vehicles, and the problem of identification has received much attention. Aiming at the problem of person identification from lidar point cloud data, particularly the special problem of identification in a cross-country environment, this paper designs an improved identification algorithm based on Euclidean clustering, theoret

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