Journal articles on the topic 'LIDAR source'
To see the other types of publications on this topic, follow the link: LIDAR source.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'LIDAR source.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Zhang, Zhenhua, Peng Chen, and Zhihua Mao. "SOLS: An Open-Source Spaceborne Oceanic Lidar Simulator." Remote Sensing 14, no. 8 (April 12, 2022): 1849. http://dx.doi.org/10.3390/rs14081849.
Full textAbstract:
In recent years, oceanic lidar has seen a wide range of oceanic applications, such as optical profiling and detecting bathymetry. Furthermore, spaceborne lidars, CALIOP and ICESat-2, designed for atmospheric and ice science applications, have been used for ocean backscattering retrievals, but, until now, there has been no spaceborne lidar specifically designed for ocean detection. There is a demand for an effective lidar simulator to study the detection potential capability of spaceborne oceanic lidar. In this study, an open-source spaceborne oceanic lidar simulator named SOLS was developed, which is available freely. Moreover, the maximum detectable depth and corresponding optimal wavelength for spaceborne lidar were analyzed at a global scale by using SOLS. The factors controlling detection limits of a spaceborne ocean profiling lidar in different cases were discussed. Then, the maximum detectable depths with different relative measurement errors and the influence of solar background radiance were estimated. Subsequently, the effects of laser and detector parameters on maximum detectable depths were studied. The relationship between the lidar detectable depth and the ocean mixed layer depth was also discussed. Preliminary results show that the maximum detectable depth could reach deeper than 120 m in the oligotrophic sea at low latitudes. We found that 490 nm is the optimal wavelength for most of the open seawater. For coastal water, 532 nm is a more suitable choice considering both the technical maturity and geophysical parameters. If possible, a lidar equipped with 440 nm could achieve the greatest depth in oligotrophic seawater in subtropical gyres north and south of the equator. The upper mixed layer vertical structure in most of the global open ocean is within the lidar maximum detectable depth. These results show that SOLS can help the design of future spaceborne oceanic lidar systems a lot.
2
St. Peter, Joseph, Jason Drake, Paul Medley, and Victor Ibeanusi. "Forest Structural Estimates Derived Using a Practical, Open-Source Lidar-Processing Workflow." Remote Sensing 13, no. 23 (November 24, 2021): 4763. http://dx.doi.org/10.3390/rs13234763.
Full textAbstract:
Lidar data is increasingly available over large spatial extents and can also be combined with satellite imagery to provide detailed vegetation structural metrics. To fully realize the benefits of lidar data, practical and scalable processing workflows are needed. In this study, we used the lidR R software package, a custom forest metrics function in R, and a distributed cloud computing environment to process 11 TB of airborne lidar data covering ~22,900 km2 into 28 height, cover, and density metrics. We combined these lidar outputs with field plot data to model basal area, trees per acre, and quadratic mean diameter. We compared lidar-only models with models informed by spectral imagery only, and lidar and spectral imagery together. We found that lidar models outperformed spectral imagery models for all three metrics, and combination models performed slightly better than lidar models in two of the three metrics. One lidar variable, the relative density of low midstory canopy, was selected in all lidar and combination models, demonstrating the importance of midstory forest structure in the study area. In general, this open-source lidar-processing workflow provides a practical, scalable option for estimating structure over large, forested landscapes. The methodology and systems used for this study offered us the capability to process large quantities of lidar data into useful forest structure metrics in compressed timeframes.
3
Hicks-Jalali, Shannon, Robert J. Sica, Alexander Haefele, and Giovanni Martucci. "Calibration of a water vapour Raman lidar using GRUAN-certified radiosondes and a new trajectory method." Atmospheric Measurement Techniques 12, no. 7 (July 9, 2019): 3699–716. http://dx.doi.org/10.5194/amt-12-3699-2019.
Full textAbstract:
Abstract. Raman lidars have been designated as potential candidates for trend studies by the Network for the Detection of Atmospheric Composition Change (NDACC) and GCOS (Global Climate Observing System) Reference Upper Air Network (GRUAN); however, for such studies improved calibration techniques are needed as well as careful consideration of the calibration uncertainties. Trend determinations require frequent, accurate, and well-characterized measurements. However, water vapour Raman lidars produce a relative measurement and require calibration in order to transform the measurement into a mixing ratio, a conserved quantity when no sources or sinks for water vapour are present. Typically, the calibration is done using a reference instrument such as a radiosonde. We present an improved trajectory technique to calibrate water vapour Raman lidars based on the previous work of Whiteman et al. (2006), Leblanc and Mcdermid (2008), Adam et al. (2010), and Herold et al. (2011), who used radiosondes as an external calibration source and matched the lidar measurements to the corresponding radiosonde measurement. However, they did not consider the movement of the radiosonde relative to the air mass and fronts. Our trajectory method is a general technique which may be used for any lidar and only requires that the radiosonde report wind speed and direction. As calibrations can be affected by a lack of co-location with the reference instrument, we have attempted to improve their technique by tracking the air parcels measured by the radiosonde relative to the field of view of the lidar. This study uses GRUAN Vaisala RS92 radiosonde measurements and lidar measurements taken by the MeteoSwiss RAman Lidar for Meteorological Observation (RALMO), located in Payerne, Switzerland, from 2011 to 2016 to demonstrate this improved calibration technique. We compare this technique to the traditional radiosonde–lidar calibration technique which does not involve tracking the radiosonde and uses the same integration time for all altitudes. Both traditional and our trajectory methods produce similar profiles when the water vapour field is homogeneous over the 30 min calibration period. We show that the trajectory method reduces differences between the radiosonde and lidar by an average of 10 % when the water vapour field is not homogeneous over a 30 min calibration period. We also calculate a calibration uncertainty budget that can be performed on a nightly basis. The calibration uncertainty budget includes the uncertainties due to phototube paralysis, aerosol extinctions, the assumption of the Ångström exponent, and the radiosonde. The study showed that the radiosonde was the major source of uncertainty in the calibration at 4 % of the calibration value. This trajectory method showed small improvements for RALMO's calibration but would be more useful for stations in different climatological regions or when non-co-located radiosondes are the only available calibration source.
4
KOYAMA, Moriaki, and Tatsuo SHIINA. "Light Source Module for LED Mini-Lidar." Review of Laser Engineering 39, no. 8 (2011): 617–21. http://dx.doi.org/10.2184/lsj.39.617.
Full text
5
Diaz, Rosemary, Sze-Chun Chan, and Jia-Ming Liu. "Lidar detection using a dual-frequency source." Optics Letters 31, no. 24 (November 22, 2006): 3600. http://dx.doi.org/10.1364/ol.31.003600.
Full text
6
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 (March 1, 2021): 3015–33. http://dx.doi.org/10.5194/acp-21-3015-2021.
Full textAbstract:
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 explaining how backward trajectories or particle positions from a dispersion model can be combined with geographical information (a land cover classification and manually defined areas) to obtain a continuous and vertically resolved estimate of an air mass source above a certain location. Ideally, such an estimate depends on as few as possible a priori information and auxiliary data. An automated framework for the computation of such an air mass source is presented, and two applications are described. First, the air mass source information is used for the interpretation of air mass sources for three case studies with lidar observations from Limassol (Cyprus), Punta Arenas (Chile) and ship-borne off Cabo Verde. Second, air mass source statistics are calculated for two multi-week campaigns to assess potential observation biases of lidar-based aerosol statistics. Such an automated approach is a valuable tool for the analysis of short-term campaigns but also for long-term data sets, for example, acquired by EARLINET.
7
Talianu, Camelia, and Petra Seibert. "Analysis of sulfate aerosols over Austria: a case study." Atmospheric Chemistry and Physics 19, no. 9 (May 13, 2019): 6235–50. http://dx.doi.org/10.5194/acp-19-6235-2019.
Full textAbstract:
Abstract. An increase in the sulfate aerosols observed in the period 1–6 April 2014 over Austria is analyzed using in situ measurements at an Austrian air quality background station, lidar measurements at the closest EARLINET stations around Austria, CAMS near-real-time data, and particle dispersion modeling using FLEXPART, a Lagrangian transport model. In situ measurements of SO2, PM2.5, PM10, and O3 were performed at the air quality background station Pillersdorf, Austria (EMEP station AT30, 48∘43′ N, 15∘55′ E). A CAMS aerosol mixing ratio analysis for Pillersdorf and the lidar stations Leipzig, Munich, Garmisch, and Bucharest indicates the presence of an event of aerosol transport, with sulfate and dust as principal components. For the sulfate layers identified at Pillersdorf from the CAMS analysis, backward- and forward-trajectory analyses were performed, associating lidar stations with the trajectories. The lidar measurements for the period corresponding to trajectory overpass of associated stations were analyzed, obtaining the aerosol layers, the optical properties, and the aerosol types. The potential sources of transported aerosols were determined for Pillersdorf and the lidar stations using the source–receptor sensitivity computed with FLEXPART, combined with the MACCity source inventory. A comparative analysis for Pillersdorf and the trajectory-associated lidar stations showed consistent aerosol layers, optical properties and types, and potential sources. A complex pattern of contributions to sulfate over Austria was found in this paper. For the lower layers (below 2000 m) of sulfate, it was found that central Europe was the main source of sulfate. Medium to smaller contributions come from sources in eastern Europe, northwest Africa, and the eastern US. For the middle-altitude layers (between 2000 and 5000 m), sources from central Europe (northern Italy, Serbia, Hungary) contribute with similar emissions. Northwest Africa and the eastern US also have important contributions. For the high-altitude layers (above 5000 m), the main contributions come from northwest Africa, but sources from the southern and eastern US also contribute significantly. No contributions from Europe are seen for these layers. The methodology used in this paper can be used as a general tool to correlate measurements at in situ stations and EARLINET lidar stations around these in situ stations.
8
Shiina, Tatsuo. "LED Mini Lidar for Atmospheric Application." Sensors 19, no. 3 (January 29, 2019): 569. http://dx.doi.org/10.3390/s19030569.
Full textAbstract:
The creation of a compact and easy-to-use atmospheric lidar has been the aim of researchers for a long time. Micro Pulse Lidars (MPL) and commercialized ceilometers were designed for such purposes. Laser Diodes (LD) and Diode-Pumped Solid State (DPSS) Laser technology has evolved, making lidar system more compact; however, their vulnerability to static electricity and fluctuation of electrical power prevented the growth of atmospheric lidar technology as a system suited to all kinds of users. In this study, a mini lidar with a Light Emitting Diode (LED) -based light source was designed and developed. As LED lamp modules do not need a heat sink or fan, they are resilient and can emit light for long periods with constant intensity. They also offer ease of handling for non-professionals. On the other hand, a LED lamp module has a large divergence, when compared to laser beams. A prototype LED mini lidar was thus developed, with focus on transmitting power optimization and optical design. This low-cost lidar system is not only compact, but also offers near-range measurement applications. It visualizes rapid activities of small air cells in a close range (surface atmosphere), and can verify and predict the condition of the surface atmosphere. This paper summarizes the principle, design, practical use and applications of the LED mini-lidar.
9
Sannino, Alessia, Antonella Boselli, Domenico Maisto, Alberto Porzio, Changbo Song, Nicola Spinelli, and Xuan Wang. "Development of a High Spectral Resolution Lidar for day-time measurements of aerosol extinction." EPJ Web of Conferences 197 (2019): 02009. http://dx.doi.org/10.1051/epjconf/201919702009.
Full textAbstract:
Lidar technique is the most performing way to obtain the atmospheric vertical profile of aerosol optical properties with high space-time resolution. With elastic scattering lidars, the retrieval of aerosol optical properties (as the extinction profile) is realizable only with assumptions on aerosol extinction-to-backscatter ratio or with Raman measurement achievable in night-time. In order to overcome these problems, the High Spectral Resolution Lidar (HSRL) technique has been examined. In this paper we present an innovative prototype of High Spectral Resolution Lidar realized at Physics Department of University “Federico II” of Naples for the LISA (LIdar for Space study of the Atmosphere) project in the framework of the China-Italy international cooperation between CNISM and BRIT. The prototype which represents a first step of a spaceborne HSRL, is based on a laser source at 1064nm and 532nm with high spectral resolution ability at 532nm. The separation between the molecular and the aerosol components was obtained through the use of a confocal Fabry-Perot interferometer (CFPI) cavity.
10
Sherstobitov, Artem, Viktor Banakh, Alexander Nadeev, Igor Razenkov, Igor Smalikho, and Andrey Falits. "Development of an All-Fiber Coherent Doppler Lidar in the IAO SB RAS." EPJ Web of Conferences 237 (2020): 06005. http://dx.doi.org/10.1051/epjconf/202023706005.
Full textAbstract:
Paper presents a model of the all-fiber pulsed coherent Doppler lidar (IAO-lidar) build in the IAO SB RAS. Here is described lidar design, the algorithm for processing of lidar signals and the software-hardware system that implements signal processing in real time, created with the use of open source software. The results of joint measurements of the radial velocity by the IAO-lidar and the HALO Photonics (Stream Line) lidar are given.
11
Awadallah, Mahmoud Omer Mahmoud, Ana Juárez, and Knut Alfredsen. "Comparison between Topographic and Bathymetric LiDAR Terrain Models in Flood Inundation Estimations." Remote Sensing 14, no. 1 (January 5, 2022): 227. http://dx.doi.org/10.3390/rs14010227.
Full textAbstract:
Remotely sensed LiDAR data has allowed for more accurate flood map generation through hydraulic simulations. Topographic and bathymetric LiDARs are the two types of LiDAR used, of which the former cannot penetrate water bodies while the latter can. Usually, the topographic LiDAR is more available than bathymetric LiDAR, and it is, therefore, a very interesting data source for flood mapping. In this study, we made comparisons between flood inundation maps from several flood scenarios generated by the HEC-RAS 2D model for 11 sites in Norway using both bathymetric and topographic terrain models. The main objective is to investigate the accuracy of the flood inundations generated from the plain topographic LiDAR, the links of the inaccuracies with geomorphic features, and the potential of using corrections for missing underwater geometry in the topographic LiDAR data to improve accuracy. The results show that the difference in inundation between topographic and bathymetric LiDAR models decreases with increasing the flood size, and this trend was found to be correlated with the amount of protection embankments in the reach. In reaches where considerable embankments are constructed, the difference between the inundations increases until the embankments are overtopped and then returns to the general trend. In addition, the magnitude of the inundation error was found to correlate positively with the sinuosity and embankment coverage and negatively with the angle of the bank. Corrections were conducted by modifying the flood discharge based on the flight discharge of the topographic LiDAR or by correcting the topographic LiDAR terrain based on the volume of the flight discharge, where the latter method generally gave better improvements.
12
Naqvi, Rizwan Ali, Muhammad Arsalan, Talha Qaiser, Tariq Mahmood Khan, and Imran Razzak. "Sensor Data Fusion Based on Deep Learning for Computer Vision Applications and Medical Applications." Sensors 22, no. 20 (October 21, 2022): 8058. http://dx.doi.org/10.3390/s22208058.
Full textAbstract:
Sensor fusion is the process of merging data from many sources, such as radar, lidar and camera sensors, to provide less uncertain information compared to the information collected from single source [...]
13
Petras, V., A. Petrasova, J. Jeziorska, and H. Mitasova. "PROCESSING UAV AND LIDAR POINT CLOUDS IN GRASS GIS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 22, 2016): 945–52. http://dx.doi.org/10.5194/isprs-archives-xli-b7-945-2016.
Full textAbstract:
Today’s methods of acquiring Earth surface data, namely lidar and unmanned aerial vehicle (UAV) imagery, non-selectively collect or generate large amounts of points. Point clouds from different sources vary in their properties such as number of returns, density, or quality. We present a set of tools with applications for different types of points clouds obtained by a lidar scanner, structure from motion technique (SfM), and a low-cost 3D scanner. To take advantage of the vertical structure of multiple return lidar point clouds, we demonstrate tools to process them using 3D raster techniques which allow, for example, the development of custom vegetation classification methods. Dense point clouds obtained from UAV imagery, often containing redundant points, can be decimated using various techniques before further processing. We implemented and compared several decimation techniques in regard to their performance and the final digital surface model (DSM). Finally, we will describe the processing of a point cloud from a low-cost 3D scanner, namely Microsoft Kinect, and its application for interaction with physical models. All the presented tools are open source and integrated in GRASS GIS, a multi-purpose open source GIS with remote sensing capabilities. The tools integrate with other open source projects, specifically Point Data Abstraction Library (PDAL), Point Cloud Library (PCL), and OpenKinect libfreenect2 library to benefit from the open source point cloud ecosystem. The implementation in GRASS GIS ensures long term maintenance and reproducibility by the scientific community but also by the original authors themselves.
14
Petras, V., A. Petrasova, J. Jeziorska, and H. Mitasova. "PROCESSING UAV AND LIDAR POINT CLOUDS IN GRASS GIS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 22, 2016): 945–52. http://dx.doi.org/10.5194/isprsarchives-xli-b7-945-2016.
Full textAbstract:
Today’s methods of acquiring Earth surface data, namely lidar and unmanned aerial vehicle (UAV) imagery, non-selectively collect or generate large amounts of points. Point clouds from different sources vary in their properties such as number of returns, density, or quality. We present a set of tools with applications for different types of points clouds obtained by a lidar scanner, structure from motion technique (SfM), and a low-cost 3D scanner. To take advantage of the vertical structure of multiple return lidar point clouds, we demonstrate tools to process them using 3D raster techniques which allow, for example, the development of custom vegetation classification methods. Dense point clouds obtained from UAV imagery, often containing redundant points, can be decimated using various techniques before further processing. We implemented and compared several decimation techniques in regard to their performance and the final digital surface model (DSM). Finally, we will describe the processing of a point cloud from a low-cost 3D scanner, namely Microsoft Kinect, and its application for interaction with physical models. All the presented tools are open source and integrated in GRASS GIS, a multi-purpose open source GIS with remote sensing capabilities. The tools integrate with other open source projects, specifically Point Data Abstraction Library (PDAL), Point Cloud Library (PCL), and OpenKinect libfreenect2 library to benefit from the open source point cloud ecosystem. The implementation in GRASS GIS ensures long term maintenance and reproducibility by the scientific community but also by the original authors themselves.
15
Chen, Yuwei, Esa Räikkönen, Sanna Kaasalainen, Juha Suomalainen, Teemu Hakala, Juha Hyyppä, and Ruizhi Chen. "Two-channel Hyperspectral LiDAR with a Supercontinuum Laser Source." Sensors 10, no. 7 (July 23, 2010): 7057–66. http://dx.doi.org/10.3390/s100707057.
Full text
16
Geiser, P., U. Willer, D. Walter, and W. Schade. "A subnanosecond pulsed laser-source for mid-infrared LIDAR." Applied Physics B 83, no. 2 (March 14, 2006): 175–79. http://dx.doi.org/10.1007/s00340-006-2158-5.
Full text
17
Chen, Shoubin, Baoding Zhou, Changhui Jiang, Weixing Xue, and Qingquan Li. "A LiDAR/Visual SLAM Backend with Loop Closure Detection and Graph Optimization." Remote Sensing 13, no. 14 (July 10, 2021): 2720. http://dx.doi.org/10.3390/rs13142720.
Full textAbstract:
LiDAR (light detection and ranging), as an active sensor, is investigated in the simultaneous localization and mapping (SLAM) system. Typically, a LiDAR SLAM system consists of front-end odometry and back-end optimization modules. Loop closure detection and pose graph optimization are the key factors determining the performance of the LiDAR SLAM system. However, the LiDAR works at a single wavelength (905 nm), and few textures or visual features are extracted, which restricts the performance of point clouds matching based loop closure detection and graph optimization. With the aim of improving LiDAR SLAM performance, in this paper, we proposed a LiDAR and visual SLAM backend, which utilizes LiDAR geometry features and visual features to accomplish loop closure detection. Firstly, the bag of word (BoW) model, describing the visual similarities, was constructed to assist in the loop closure detection and, secondly, point clouds re-matching was conducted to verify the loop closure detection and accomplish graph optimization. Experiments with different datasets were carried out for assessing the proposed method, and the results demonstrated that the inclusion of the visual features effectively helped with the loop closure detection and improved LiDAR SLAM performance. In addition, the source code, which is open source, is available for download once you contact the corresponding author.
18
Wang, Chuan, Shijie Liu, Xiaoyan Wang, and Xiaowei Lan. "Time Synchronization and Space Registration of Roadside LiDAR and Camera." Electronics 12, no. 3 (January 20, 2023): 537. http://dx.doi.org/10.3390/electronics12030537.
Full textAbstract:
The sensing system consisting of Light Detection and Ranging (LiDAR) and a camera provides complementary information about the surrounding environment. To take full advantage of multi-source data provided by different sensors, an accurate fusion of multi-source sensor information is needed. Time synchronization and space registration are the key technologies that affect the fusion accuracy of multi-source sensors. Due to the difference in data acquisition frequency and deviation in startup time between LiDAR and the camera, asynchronous data acquisition between LiDAR and camera is easy to occur, which has a significant influence on subsequent data fusion. Therefore, a time synchronization method of multi-source sensors based on frequency self-matching is developed in this paper. Without changing the sensor frequency, the sensor data are processed to obtain the same number of data frames and set the same ID number, so that the LiDAR and camera data correspond one by one. Finally, data frames are merged into new data packets to realize time synchronization between LiDAR and camera. Based on time synchronization, to achieve spatial synchronization, a nonlinear optimization algorithm of joint calibration parameters is used, which can effectively reduce the reprojection error in the process of sensor spatial registration. The accuracy of the proposed time synchronization method is 99.86% and the space registration accuracy is 99.79%, which is better than the calibration method of the Matlab calibration toolbox.
19
Zhang, Peng, Ming Ming Xi, Manman Wang, Pu Liu, Tao Liu, Hui Peng, Gui Dong Ren, and Chun Lin Tian. "Study on Features of 532nm Laser as Laser Source of Lidar." Applied Mechanics and Materials 851 (August 2016): 544–49. http://dx.doi.org/10.4028/www.scientific.net/amm.851.544.
Full textAbstract:
The laser source of Lidar usually use the high power solid laser, the performance of Lidar depend on the laser features, so that to study the laser features is contribute to optimize the performance of Lidar. Set up and design a pulse solid laser of Nd3+:YAG as the working substance. Through adopt the KTP crystal frequency multiplication technology outside the laser cavity and electro-optic q-switch technique, the maximum dynamic pulse energy of 155mJ and pulse width of 9.6 ns with the 532nm laser is generated. Using the oscilloscope, photoelectric pulse sensor and laser energy meter to measurement the experimental data of the laser source features Through analyze and discuss the experimental data, the relationship between the pulse width, the static and dynamic ratio, the peak power of the pulse Nd3+:YAG laser, the frequency doubling efficiency of the KTP crystal and the input power of laser are given, the solid laser system and the experimental data can provide a basic equipment and reference data to the further study.
20
Weissmann, Martin, Kathrin Folger, and Heiner Lange. "Height Correction of Atmospheric Motion Vectors Using Airborne Lidar Observations." Journal of Applied Meteorology and Climatology 52, no. 8 (August 2013): 1868–77. http://dx.doi.org/10.1175/jamc-d-12-0233.1.
Full textAbstract:
AbstractUncertainties in the height assignment of atmospheric motion vectors (AMVs) are the main contributor to the total AMV wind error, and these uncertainties introduce errors that can be horizontally correlated over several hundred kilometers. As a consequence, only a small fraction of the available AMVs are currently used in numerical weather prediction systems. For this reason, alternative approaches for the height assignment of AMVs are investigated in this study: 1) using collocated airborne lidar observations and 2) treating AMVs as layer winds instead of winds at a discrete level. Airborne lidar observations from a field campaign in the western North Pacific Ocean region are used to demonstrate the potential of improving AMV heights in an experimental framework. On average, AMV wind errors are reduced by 10%–15% when AMV winds are assigned to a 100–150-hPa-deep layer beneath the cloud top derived from nearby lidar observations. In addition, the lidar–AMV height correction is expected to reduce the correlation of AMV errors as lidars provide independent cloud height information. This suggests that satellite lidars may be a valuable source of information for the AMV height assignment in the future. Furthermore, AMVs are compared with dropsonde and radiosonde winds averaged over vertical layers of different depth to investigate the optimal height assignment for AMVs in data assimilation. Consistent with previous studies, it is shown that AMV winds better match sounding winds vertically averaged over ~100 hPa than sounding winds at a discrete level. The comparison with deeper layers further reduces the RMS difference but introduces systematic differences of wind speeds.
21
Sinčić, Marko, Sanja Bernat Gazibara, Martin Krkač, Hrvoje Lukačić, and Snježana Mihalić Arbanas. "The Use of High-Resolution Remote Sensing Data in Preparation of Input Data for Large-Scale Landslide Hazard Assessments." Land 11, no. 8 (August 21, 2022): 1360. http://dx.doi.org/10.3390/land11081360.
Full textAbstract:
The objective of the study is to show that landslide conditioning factors derived from different source data give significantly different relative influences on the weight factors derived with statistical models for landslide susceptibility modelling and risk analysis. The analysis of the input data for large-scale landslide hazard assessment was performed on a study area (20.2 km2) in Hrvatsko Zagorje (Croatia, Europe), an area highly susceptible to sliding with limited geoinformation data, including landslide data. The main advantage of remote sensing technique (i.e., LiDAR, Light Detection and Ranging) data and orthophoto images is that they enable 3D surface models with high precision and spatial resolution that can be used for deriving all input data needed for landslide hazard assessment. The visual interpretation of LiDAR DTM (Digital Terrain Model) morphometric derivatives resulted in a detailed and complete landslide inventory map, which consists of 912 identified and mapped landslides, ranging in size from 3.3 to 13,779 m2. This inventory was used for quantitative analysis of 16 input data layers from 11 different sources to analyse landslide presence in factor classes and thus comparing landslide conditioning factors from available small-scale data with high-resolution LiDAR data and orthophoto images, pointing out the negative influence of small-scale source data. Therefore, it can be concluded that small-scale landslide factor maps derived from publicly available sources should not be used for large-scale analyses because they will result in incorrect assumptions about conditioning factors compared with LiDAR DTM derivative factor maps. Furthermore, high-resolution LiDAR DTM and orthophoto images are optimal input data because they enable derivation of the most commonly used landslide conditioning factors for susceptibility modelling and detailed datasets about elements at risk (i.e., buildings and traffic infrastructure data layers).
22
Adam, Mariana, Doina Nicolae, Iwona S. Stachlewska, Alexandros Papayannis, and Dimitris Balis. "Biomass burning events measured by lidars in EARLINET – Part 1: Data analysis methodology." Atmospheric Chemistry and Physics 20, no. 22 (November 18, 2020): 13905–27. http://dx.doi.org/10.5194/acp-20-13905-2020.
Full textAbstract:
Abstract. The methodology of analysing the biomass burning events recorded in the database of the European Aerosol Research Lidar Network in the framework of the Aerosol, Clouds and Trace Gases Research Infrastructure is presented. The period of 2008–2017 was chosen to analyse all of the events stored in the database under the Forest Fire category for a total of 14 stations available. The data provided ranged from complete datasets (particle backscatter, extinction and linear depolarization ratio profiles) to single profiles (particle backscatter coefficient profile). Smoke layers geometry was evaluated and the mean optical properties within each layer were computed. The back-trajectory technique was used to double-check the source of all pollution layers. The biomass burning layers were identified by taking into account the presence of the fires along the back trajectory. The biomass burning events are analysed by the means of the intensive parameters. The analysis was structured in three directions: (I) common biomass burning source (fire) recorded by at least two stations, (II) long-range transport from North America, and (III) analysis over four geographical regions (south-eastern Europe, north-eastern Europe, central Europe, and south-western Europe). Based on back-trajectory calculations and fire locations, the lidar measurements can be labelled either as measurements of a “single fire” or “mixed fires” (case I), measurements of North American fires, or measurements of mixed North American and local fires (case II). The histogram of the fire locations reveals the smoke sources for each region. For each region, statistics on intensive parameters are performed. The source origin of the intensive parameters is categorized based on the continental origin of the air mass (European, African, Asian, North American, or a combination of them). The methodology presented here is meant to provide a perspective to explore a large number of lidar data and deliver novel approaches to analyse the intensive parameters based on the assigned biomass burning sources. A thorough consideration of all potential fire sources reveals that most of the time the lidar measurements characterize the smoke from a mixture of fires. A comprehensive discussion of all the results (based on the intensive parameters and the source locations) will be given in a companion paper submitted to the ACP EARLINET special issue.
23
Cairo, F., G. Di Donfrancesco, L. Di Liberto, and M. Viterbini. "The RAMNI airborne lidar for cloud and aerosol research." Atmospheric Measurement Techniques Discussions 5, no. 1 (February 9, 2012): 1253–92. http://dx.doi.org/10.5194/amtd-5-1253-2012.
Full textAbstract:
Abstract. We describe an airborne lidar for the characterization of atmospheric aerosol. The system has been set up in response to the need to monitor extended regions where the air traffic may be posed at risk by the presence of potentially harmful volcanic ash, and to study the characteristics of volcanic emissions both near the source region and when transported over large distances. The lidar provides backscatter and linear depolarization profiles at 532 nm, from which aerosol and cloud properties can be derived. The paper presents the characteristics and capabilities of the lidar system and gives examples of its airborne deployment. Observations from three flights, aimed at assessing the system capabilities in unperturbed atmospheric conditions, and at characterizing the emissions near a volcanic ash source region, the Mt. Etna, and transported far away from the source, are presented and discussed.
24
Cairo, F., G. Di Donfrancesco, L. Di Liberto, and M. Viterbini. "The RAMNI airborne lidar for cloud and aerosol research." Atmospheric Measurement Techniques 5, no. 7 (July 25, 2012): 1779–92. http://dx.doi.org/10.5194/amt-5-1779-2012.
Full textAbstract:
Abstract. We describe an airborne lidar for the characterization of atmospheric aerosol. The system has been set up in response to the need to monitor extended regions where the air traffic may be posed at risk by the presence of potentially harmful volcanic ash, and to study the characteristics of volcanic emissions both near the source region and when transported over large distances. The lidar provides backscatter and linear depolarization profiles at 532 nm, from which aerosol and cloud properties can be derived. The paper presents the characteristics and capabilities of the lidar system and gives examples of its airborne deployment. Observations from three flights, aimed at assessing the system capabilities in unperturbed atmospheric conditions, and at characterizing the emissions near a volcanic ash source (Mt. Etna) and transported far away from the source, are presented and discussed.
25
Li, Yunsong, Chiru Ge, Weiwei Sun, Jiangtao Peng, Qian Du, and Keyan Wang. "Hyperspectral and LiDAR Data Fusion Classification Using Superpixel Segmentation-Based Local Pixel Neighborhood Preserving Embedding." Remote Sensing 11, no. 5 (March 6, 2019): 550. http://dx.doi.org/10.3390/rs11050550.
Full textAbstract:
A new method of superpixel segmentation-based local pixel neighborhood preserving embedding (SSLPNPE) is proposed for the fusion of hyperspectral and light detection and ranging (LiDAR) data based on the extinction profiles (EPs), superpixel segmentation and local pixel neighborhood preserving embedding (LPNPE). A new workflow is proposed to calibrate the Goddard’s LiDAR, hyperspectral and thermal (G-LiHT) data, which allows our method to be applied to actual data. Specifically, EP features are extracted from both sources. Then, the derived features of each source are fused by the SSLPNPE. Using the labeled samples, the final label assignment is produced by a classifier. For the open standard experimental data and the actual data, experimental results prove that the proposed method is fast and effective in hyperspectral and LiDAR data fusion.
26
Zhou, Tan, and Sorin Popescu. "waveformlidar: An R Package for Waveform LiDAR Processing and Analysis." Remote Sensing 11, no. 21 (October 30, 2019): 2552. http://dx.doi.org/10.3390/rs11212552.
Full textAbstract:
A wealth of Full Waveform (FW) LiDAR (Light Detection and Ranging) data are available to the public from different sources, which is poised to boost extensive applications of FW LiDAR data. However, we lack a handy and open source tool that can be used by potential users for processing and analyzing FW LiDAR data. To this end, we introduce waveformlidar, an R package dedicated to FW LiDAR processing, analysis and visualization as a solution to the constraint. Specifically, this package provides several commonly used waveform processing methods such as Gaussian, Adaptive Gaussian and Weibull decompositions and deconvolution approaches (Gold and Richard-Lucy (RL)) with users’ customized settings. In addition, we also developed functions to derive commonly used waveform metrics for characterizing vegetation structure. Moreover, a new way to directly visualize FW LiDAR data is developed by converting waveforms into points to form the Hyper Point Cloud (HPC), which can be easily adopted and subsequently analyzed with existing discrete-return LiDAR processing tools such as LAStools and FUSION. Basic explorations of the HPC such as 3D voxelization of the HPC and conversion from original waveforms to composite waveforms are also available in this package. All of these functions are developed based on small-footprint FW LiDAR data but they can be easily transplanted to the large footprint FW LiDAR data such as Geoscience Laser Altimeter System (GLAS) and Global Ecosystem Dynamics Investigation (GEDI) data analysis. It is anticipated that these functions will facilitate the widespread use of FW LiDAR and be beneficial for better estimating biomass and characterizing vegetation structure at various scales.
27
Ramesh, K., S. Sridharan, and K. Raghunath. "Comprehensive Study on Tropical (10°N-15°N) Mesospheric Inversion Layers Using Lidar and Satellite (Timed-Saber) Observations." EPJ Web of Conferences 237 (2020): 04001. http://dx.doi.org/10.1051/epjconf/202023704001.
Full textAbstract:
One of the interesting and poorly understood features of mesosphere and lower thermosphere (MLT) region is the phenomenon of Mesospheric Inversion Layers (MILs). The poor understanding of MILs is due to limited access of their occurrence height region, however the lidars are more efficient tools which provide stratosphere and mesosphere nocturnal temperatures with high temporal and vertical resolutions. The state-of-the-art lidar system comprising Mie, Rayleigh lidars installed at National Atmospheric Research Laboratory (NARL), Gadanki (13.5°N, 79.2°E), India has provided an excellent opportunity to undertake this study. The Nd:YAG laser source with lower power (11W) has been replaced by the one with higher power (30W) in January 2007. As the laser power has been increased, the molecular back scatter signal is also increased and consequently the top height level of the temperature retrieval has been increased to ~90-95 km. In the present study, the role of dominant causative mechanisms for the occurrence of MILs has been discussed using mainly the lidar and satellite (TIMED-SABER) observations over Gadanki region.
28
Zhang, Xinyuan, Yihua Hu, Shilong Xu, Fei Han, and Yicheng Wang. "Application of Image Fusion Algorithm Combined with Visual Saliency in Target Extraction of Reflective Tomography Lidar Image." Computational Intelligence and Neuroscience 2022 (February 27, 2022): 1–10. http://dx.doi.org/10.1155/2022/8247344.
Full textAbstract:
Reflective tomography Lidar has been proved to be a new Lidar system with long distance and high resolution. The reflective tomography Lidar image is prone to clutter and artifacts; thus, it is important for space target recognition to extract the target from the image. In this study, we proposed image fusion algorithm combined with visual saliency could be applied to the target extraction of reflective tomography Lidar image, which can not only preserve the target information but also eliminate the clutter and artifacts in the image. The efficiency of this algorithm is shown by simulation and the experiment of the reflective tomography Lidar system. Also, we analyzed the main source of reflective tomography Lidar image artifacts and the reason why this algorithm could remove clutter and artifacts.
29
Sherrill, K. R., M. A. Lefsky, J. B. Bradford, and M. G. Ryan. "Forest structure estimation and pattern exploration from discrete-return lidar in subalpine forests of the central Rockies." Canadian Journal of Forest Research 38, no. 8 (August 2008): 2081–96. http://dx.doi.org/10.1139/x08-059.
Full textAbstract:
This study evaluates the relative ability of simple light detection and ranging (lidar) indices (i.e., mean and maximum heights) and statistically derived canonical correlation analysis (CCA) variables attained from discrete-return lidar to estimate forest structure and forest biomass variables for three temperate subalpine forest sites. Both lidar and CCA explanatory variables performed well with lidar models having slightly higher explained variance and lower root mean square error. Adjusted R2 values were 0.93 and 0.93 for mean height, 0.74 and 0.73 for leaf area index, and 0.93 and 0.85 for all carbon in live biomass for the lidar and CCA explanatory regression models, respectively. The CCA results indicate that the primary source of variability in canopy structure is related to forest height, biomass, and total leaf area, and the second most important source of variability is related to the amount of midstory foliage and tree density. When stand age is graphed as a function of individual plot scores for canonicals one and two, there is a clear relationship with stand age and the development of stand structure. Lidar-derived biomass and related estimates developed in this work will be used to parameterize decision-support tools for analysis of carbon cycle impacts as part of the North American Carbon Program.
30
Omar, Ali. "A Decade of CALIPSO Observations of Asian and Saharan Dust Properties near Source and Transport Regions." E3S Web of Conferences 99 (2019): 02008. http://dx.doi.org/10.1051/e3sconf/20199902008.
Full textAbstract:
The lidar on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, makes robust measurements of dust and has generated a length of record that is significant both seasonally and inter-annually. We exploit this record to determine a multi-year climatology of the properties of Asian and Saharan dust, in particular seasonal optical depths, layer frequencies, and layer heights of dust gridded in accordance with the Level 3 data products protocol between 2006 and 2016. The data are screened using standard CALIPSO quality assurance flags, cloud aerosol discrimination (CAD) scores, overlying features and layer properties. To evaluate the effects of transport on small-scale phenomena such as morphology, vertical extent and size of the dust layers, we compare probability distribution functions of the layer integrated volume depolarization ratios, geometric depths and integrated attenuated color ratios near the source to the same distributions in the far field or transport region. To evaluate the uncertainty in the lidar ratios, we compare the values computed from dust layers overlying opaque water clouds, considered accurate, with the constant lidar ratio value used in the CALIOP algorithms for dust
31
Tinkham, Wade T., Hongyu Huang, Alistair M. S. Smith, Rupesh Shrestha, Michael J. Falkowski, Andrew T. Hudak, Timothy E. Link, Nancy F. Glenn, and Danny G. Marks. "A Comparison of Two Open Source LiDAR Surface Classification Algorithms." Remote Sensing 3, no. 3 (March 22, 2011): 638–49. http://dx.doi.org/10.3390/rs3030638.
Full text
32
Izwan Ahmad Arshad, Khairil, Helmi Z.M. Shafri, Shattri Mansor, and Raja Azlina Raja Mahmood. "Development of LiDAR Database Management System using Open Source Software." Research Journal of Applied Sciences, Engineering and Technology 13, no. 9 (November 5, 2016): 706–16. http://dx.doi.org/10.19026/rjaset.13.3344.
Full text
33
Vasil'ev, B. I., and Cheon W. Cho. "NH3laser as a radiation source for a two-frequency lidar." Quantum Electronics 30, no. 12 (December 31, 2000): 1105–6. http://dx.doi.org/10.1070/qe2000v030n12abeh001877.
Full text
34
Määttänen, Anni, François Ravetta, Franck Montmessin, Didier Bruneau, Jean-François Mariscal, Mathilde Van Haecke, Guillaume Fayolle, Christophe Montaron, and David Coscia. "The marbll experiment: towards a martian wind lidar." EPJ Web of Conferences 176 (2018): 06006. http://dx.doi.org/10.1051/epjconf/201817606006.
Full textAbstract:
Operating a lidar on Mars would fulfill the need of accessing wind and aerosol profiles in the atmospheric boundary layer. This is the purpose of the MARs Boundary Layer Lidar (MARBLL) instrument. We report recent developments of this compact direct-detection wind lidar designed to operate from the surface of Mars. A new laser source has been developed and an azimuthal scanning capability has been added. Preliminary results of a field campaign are presented.
35
Lee, Dong-Cheon, David H. Lee, and Dae Geon Lee. "Determination of Building Model Key Points Using Multidirectional Shaded Relief Images Generated from Airborne LiDAR Data." Journal of Sensors 2019 (April 21, 2019): 1–19. http://dx.doi.org/10.1155/2019/2985014.
Full textAbstract:
Light detection and ranging (LiDAR) data collected from airborne laser scanner system is one of the major sources to reconstruct Earth’s surface features. This paper presents a method for detecting model key points (MKPs) of the buildings using LiDAR point clouds. The proposed approach utilizes shaded relief images (SRIs) derived from the LiDAR data. The SRIs based on the concept of the shape from shading could provide unique information about individual surface patches of the building roofs. The main advantage of the proposed approach is to detect directly MKPs, which are primitives for 3D building modeling, without segmenting point clouds. Depending on the location of the light source, the SRIs are created differently. Therefore, integration of the multidirectional SRIs created from different locations of the light source could provide more reliable results. In addition, the vertical exaggeration (i.e., scaling Z-coordinates) is also beneficial because constituent surface patches of the roofs in the SRIs created with vertically exaggerated LiDAR data are more distinguishable. To determine the MKPs of the roofs, building data was separated from other objects using modified marker-controlled watershed algorithm in accordance with criteria to specify buildings such as area, height, and standard deviation. This process could remove the unnecessary objects such as trees, vegetation, and cars. The curvature scale space (CSS) corner detector was used to determine MKP since this method is robust to geometric changes such as rotation, translation, and scale. The proposed method was applied to simulated and real LiDAR datasets with various roof types. The experimental results show that the proposed method is effective in determining MKPs of various roof types with high level of detail (LoD).
36
Chwedczuk, Katarzyna, Daniel Cienkosz, Michal Apollo, Lukasz Borowski, Paulina Lewinska, Celso Augusto Guimarães Santos, Kennedy Eborka, et al. "Challenges related to the determination of altitudes of mountain peaks presented on cartographic sources." Geodetski vestnik 66, no. 01 (2022): 49–59. http://dx.doi.org/10.15292/geodetski-vestnik.2022.01.49-59.
Full textAbstract:
This study aimed to measure and validate altitudes from existing sources with direct GNSS measurements and airborne lidar data. For this purpose, 12 mountain peaks located in the south part of Polish territory were selected. Measurements were performed using a GNSS receiver using the Real-Time Kinematic (RTK) or static techniques enabling altitude measurements with accuracy of 10 cm. GNSS was treated as the primary data source, as the direct field measurements can determine the highest point on each peak. The obtained results were confronted with historical, internet sources, and official altitude data. Moreover, each altitude was determined using lidar data from an airborne lidar dataset of Poland from the ISOK program and provided by the national agency. Significant discrepancies in data were already detected during the analysis of internet materials and traditional maps, up to a few meters. The differences between measured and internet sources in altitude of mountain peak range from 27 cm to 504 cm. This study has shown the need to re-measure the altitudes of the mountain peaks and determine the highest point correctly.
37
Liu, Z., D. Liu, J. Huang, M. Vaughan, I. Uno, N. Sugimoto, C. Kittaka, et al. "Airborne dust distributions over the Tibetan Plateau and surrounding areas derived from the first year of CALIPSO lidar observations." Atmospheric Chemistry and Physics 8, no. 16 (August 29, 2008): 5045–60. http://dx.doi.org/10.5194/acp-8-5045-2008.
Full textAbstract:
Abstract. Using an analysis of the first full year of CALIPSO lidar measurements, this paper derives unprecedented, altitude-resolved seasonal distributions of desert dust transported over the Tibetan Plateau (TP) and the surrounding areas. The CALIPSO lidar observations include numerous large dust plumes over the northern slope and eastern part of the TP, with the largest number of dust events occurring in the spring of 2007, and some layers being lofted to altitudes of 11–12 km. Generation of the Tibetan airborne dusts appears to be largely associated with source regions to the north and on the eastern part of the plateau. Examination of the CALIPSO time history reveals an "airborne dust corridor" due to the eastward transport of dusts originating primarily in these source areas. This corridor extends from west to east and shows a seasonality largely modulated by the TP through its dynamical and thermal forcing on the atmospheric flows. On the southern side, desert dust particles originate predominately in Northwest India and Pakistan. The dust transport occurs primarily in dry seasons around the TP western and southern slopes and dust particles become mixed with local polluted aerosols. No significant amount of dust appears to be transported over the Himalayas. Extensive forward trajectory simulations are also conducted to confirm the dust transport pattern from the nearby sources observed by the CALIPSO lidar. Comparisons with the OMI and MODIS measurements show the unique capability of the CALIPSO lidar to provide unambiguous, altitude-resolved dust measurements.
38
Jin, Shichao, Yanjun Su, Shang Gao, Tianyu Hu, Jin Liu, and Qinghua Guo. "The Transferability of Random Forest in Canopy Height Estimation from Multi-Source Remote Sensing Data." Remote Sensing 10, no. 8 (July 26, 2018): 1183. http://dx.doi.org/10.3390/rs10081183.
Full textAbstract:
Canopy height is an important forest structure parameter for understanding forest ecosystem and improving global carbon stock quantification accuracy. Light detection and ranging (LiDAR) can provide accurate canopy height measurements, but its application at large scales is limited. Using LiDAR-derived canopy height as ground truth to train the Random Forest (RF) algorithm and therefore predict canopy height from other remotely sensed datasets in areas without LiDAR coverage has been one of the most commonly used method in large-scale canopy height mapping. However, how variances in location, vegetation type, and spatial scale of study sites influence the RF modelling results is still a question that needs to be addressed. In this study, we selected 16 study sites (100 km2 each) with full airborne LiDAR coverage across the United States, and used the LiDAR-derived canopy height along with optical imagery, topographic data, and climate surfaces to evaluate the transferability of the RF-based canopy height prediction method. The results show a series of findings from general to complex. The RF model trained at a certain location or vegetation type cannot be transferred to other locations or vegetation types. However, by training the RF algorithm using samples from all sites with various vegetation types, a universal model can be achieved for predicting canopy height at different locations and different vegetation types with self-predicted R2 higher than 0.6 and RMSE lower than 6 m. Moreover, the influence of spatial scales on the RF prediction accuracy is noticeable when spatial extent of the study site is less than 50 km2 or the spatial resolution of the training pixel is finer than 500 m. The canopy height prediction accuracy increases with the spatial extent and the targeted spatial resolution.
39
Gerçekcioğlu, Hamza. "Performance of bit error rate of laser beams for LIDAR used in marine atmospheric weak turbulence." Journal of the Optical Society of America B 40, no. 1 (December 23, 2022): A51. http://dx.doi.org/10.1364/josab.469694.
Full textAbstract:
The performance of laser beams is investigated for light detection and ranging (LIDAR) systems in marine weak atmospheric turbulence by using the Rytov method. Formulation, on-axis, of the scintillation indices of LIDAR systems, which is obtained for plane, collimated Gaussian, and spherical beams, is appraised for average bit error rate (BER) by utilizing the log-normal distributed intensity. Values, obtained for these beams, are checked against source sizes, target sizes, normalized target size parameters, propagation lengths, and the average signal-to-noise ratio (SNR) for specified parameters. It is observed that the target size that minimizes the scintillation index is independent of the source size. The target size minimizing scintillation index is approximately 10 − 3 c m . Variations in source size and target size values, independently of each other, affect the scintillation index and the performance of marine LIDAR system links. The contribution of the outer scale turbulence to the deterioration is more evident than the inner scale turbulence.
40
Ancellet, Gerard, Iogannes E. Penner, Jacques Pelon, Vincent Mariage, Antonin Zabukovec, Jean Christophe Raut, Grigorii Kokhanenko, and Yuri S. Balin. "Aerosol monitoring in Siberia using an 808 nm automatic compact lidar." Atmospheric Measurement Techniques 12, no. 1 (January 11, 2019): 147–68. http://dx.doi.org/10.5194/amt-12-147-2019.
Full textAbstract:
Abstract. Our study provides new information on aerosol-type seasonal variability and sources in Siberia using observations (ground-based lidar and sun photometer combined with satellite measurements). A micropulse lidar emitting at 808 nm provided almost continuous aerosol backscatter measurements for 18 months (April 2015 to September 2016) in Siberia, near the city of Tomsk (56∘ N, 85∘ E). A total of 540 vertical profiles (300 daytime and 240 night-time) of backscatter ratio and aerosol extinction have been retrieved over periods of 30 min, after a careful calibration factor analysis. Lidar ratio and extinction profiles are constrained with sun-photometer aerosol optical depth at 808 nm (AOD808) for 70 % of the daytime lidar measurements, while 26 % of the night-time lidar ratio and AOD808 greater than 0.04 are constrained by direct lidar measurements at an altitude greater than 7.5 km and where a low aerosol concentration is found. An aerosol source apportionment using the Lagrangian FLEXPART model is used in order to determine the lidar ratio of the remaining 48 % of the lidar database. Backscatter ratio vertical profile, aerosol type and AOD808 derived from micropulse lidar data are compared with sun-photometer AOD808 and satellite observations (CALIOP space-borne lidar backscatter and extinction profiles, Moderate Resolution Imaging Spectroradiometer (MODIS) AOD550 and Infrared Atmospheric Sounding Interferometer (IASI) CO column) for three case studies corresponding to the main aerosol sources with AOD808>0.2 in Siberia. Aerosol typing using the FLEXPART model is consistent with the detailed analysis of the three case studies. According to the analysis of aerosol sources, the occurrence of layers linked to natural emissions (vegetation, forest fires and dust) is high (56 %), but anthropogenic emissions still contribute to 44 % of the detected layers (one-third from flaring and two-thirds from urban emissions). The frequency of dust events is very low (5 %). When only looking at AOD808>0.1, contributions from taiga emissions, forest fires and urban pollution become equivalent (25 %), while those from flaring and dust are lower (10 %–13 %). The lidar data can also be used to assess the contribution of different altitude ranges to the large AOD. For example, aerosols related to the urban and flaring emissions remain confined below 2.5 km, while aerosols from dust events are mainly observed above 2.5 km. Aerosols from forest fire emissions are observed to be the opposite, both within and above the planetary boundary layer (PBL).
41
Montlahuc, J., A. Polette, A. Tahan, J. P. Pernot, and L. Rivest. "MULTI-SOURCE POINT CLOUD SEMANTIC SEGMENTATION USING NEURAL NETWORK." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (May 30, 2022): 515–22. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-515-2022.
Full textAbstract:
Abstract. The purpose of this study is to enhance point cloud semantic segmentation by using point clouds from multiple distinct technologies on the same capture location and to determine whether employing various technologies throughout the acquisition process yields better performance during classification. The different point clouds were captured in the same geographical location and have previously been aligned and classified by professionals of the field. Three locations have been scanned with airborne lidar, terrestrial lidar and photogrammetry using UAV or helicopter. The use of various sources of capture on the same location opens the door to creating new features, such as the proportion of each source involved in the semantic segmentation of point clouds. This plurality of sources also enables us to spread various features, such as RGB colors, that have been propagated to other sources via the neighborhood. The initial results lean towards capture using different technologies as the overall accuracy increase by two to four points and the mean Matthews correlation coefficient increase by four to seven points. The main drawbacks are the cost of some technologies, as well as the processing time, which is greater than with a single technology.
42
Engelmann, Ronny, Julian Hofer, Abduvosit N. Makhmudov, Holger Baars, Karsten Hanbuch, Albert Ansmann, Sabur F. Abdullaev, Andreas Macke, and Dietrich Althausen. "CADEX and beyond: Installation of a new PollyXT site in Dushanbe." E3S Web of Conferences 99 (2019): 02010. http://dx.doi.org/10.1051/e3sconf/20199902010.
Full textAbstract:
During the 18-month Central Asian Dust Experiment we conducted continuous lidar measurements at the Physical Technical Institute of the Academy of Sciences of Tajikistan in Dushanbe between 2015 and 2016. Mineral dust plumes from various source regions have been observed and characterized in terms of their occurrence, and their optical and microphysical properties with the Raman lidar PollyXT. Currently a new container-based lidar system is constructed which will be installed for continuous long-term measurements in Dushanbe.
43
Debnath, Sourabhi, Manoranjan Paul, and Tanmoy Debnath. "Applications of LiDAR in Agriculture and Future Research Directions." Journal of Imaging 9, no. 3 (February 24, 2023): 57. http://dx.doi.org/10.3390/jimaging9030057.
Full textAbstract:
Light detection and ranging (LiDAR) sensors have accrued an ever-increasing presence in the agricultural sector due to their non-destructive mode of capturing data. LiDAR sensors emit pulsed light waves that return to the sensor upon bouncing off surrounding objects. The distances that the pulses travel are calculated by measuring the time for all pulses to return to the source. There are many reported applications of the data obtained from LiDAR in agricultural sectors. LiDAR sensors are widely used to measure agricultural landscaping and topography and the structural characteristics of trees such as leaf area index and canopy volume; they are also used for crop biomass estimation, phenotype characterisation, crop growth, etc. A LiDAR-based system and LiDAR data can also be used to measure spray drift and detect soil properties. It has also been proposed in the literature that crop damage detection and yield prediction can also be obtained with LiDAR data. This review focuses on different LiDAR-based system applications and data obtained from LiDAR in agricultural sectors. Comparisons of aspects of LiDAR data in different agricultural applications are also provided. Furthermore, future research directions based on this emerging technology are also presented in this review.
44
Chen, Zhuqiu, Yanguang Yu, Yuxi Ruan, Bairun Nie, Jiangtao Xi, Qinghua Guo, and Jun Tong. "Dual-Frequency Doppler LiDAR Based on External Optical Feedback Effect in a Laser." Sensors 20, no. 21 (November 5, 2020): 6303. http://dx.doi.org/10.3390/s20216303.
Full textAbstract:
A novel Dual-frequency Doppler LiDAR (DFDL) is presented where the dual-frequency light source is generated by using external optical feedback (EOF) effect in a laser diode (LD). By operating a LD at period-one (P1) state and choosing suitable LD related parameters, a dual-frequency light source can be achieved. Such a dual-frequency source has advantages of the minimum part-count scheme, low cost in implementation, and ease in optical alignment. Theory and system design are presented for the proposed DFDL for velocity measurement with high measurement resolution. The proposed design has a potential contribution to the Light Detection And Ranging (LiDAR) in practical engineering applications.
45
Okano, Masayuki, and Changho Chong. "Swept Source Lidar: simultaneous FMCW ranging and nonmechanical beam steering with a wideband swept source." Optics Express 28, no. 16 (July 29, 2020): 23898. http://dx.doi.org/10.1364/oe.396707.
Full text
46
Pang, Yong, and Zengyuan Li. "SUBTROPICAL FOREST BIOMASS ESTIMATION USING AIRBORNE LiDAR AND HYPERSPECTRAL DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 747–49. http://dx.doi.org/10.5194/isprs-archives-xli-b8-747-2016.
Full textAbstract:
Forests have complex vertical structure and spatial mosaic pattern. Subtropical forest ecosystem consists of vast vegetation species and these species are always in a dynamic succession stages. It is very challenging to characterize the complexity of subtropical forest ecosystem. In this paper, CAF’s (The Chinese Academy of Forestry) LiCHy (LiDAR, CCD and Hyperspectral) Airborne Observation System was used to collect waveform Lidar and hyperspectral data in Puer forest region, Yunnan province in the Southwest of China. The study site contains typical subtropical species of coniferous forest, evergreen broadleaf forest, and some other mixed forests. The hypersectral images were orthorectified and corrected into surface reflectance with support of Lidar DTM product. The fusion of Lidar and hyperspectral can classify dominate forest types. The lidar metrics improved the classification accuracy. Then forest biomass estimation was carried out for each dominate forest types using waveform Lidar data, which get improved than single Lidar data source.
47
Pang, Yong, and Zengyuan Li. "SUBTROPICAL FOREST BIOMASS ESTIMATION USING AIRBORNE LiDAR AND HYPERSPECTRAL DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 747–49. http://dx.doi.org/10.5194/isprsarchives-xli-b8-747-2016.
Full textAbstract:
Forests have complex vertical structure and spatial mosaic pattern. Subtropical forest ecosystem consists of vast vegetation species and these species are always in a dynamic succession stages. It is very challenging to characterize the complexity of subtropical forest ecosystem. In this paper, CAF’s (The Chinese Academy of Forestry) LiCHy (LiDAR, CCD and Hyperspectral) Airborne Observation System was used to collect waveform Lidar and hyperspectral data in Puer forest region, Yunnan province in the Southwest of China. The study site contains typical subtropical species of coniferous forest, evergreen broadleaf forest, and some other mixed forests. The hypersectral images were orthorectified and corrected into surface reflectance with support of Lidar DTM product. The fusion of Lidar and hyperspectral can classify dominate forest types. The lidar metrics improved the classification accuracy. Then forest biomass estimation was carried out for each dominate forest types using waveform Lidar data, which get improved than single Lidar data source.
48
Guo, Feng, David Schlipf, Hailong Zhu, Andy Platt, Po Wen Cheng, and Florian Thomas. "Updates on the OpenFAST Lidar Simulator." Journal of Physics: Conference Series 2265, no. 4 (May 1, 2022): 042030. http://dx.doi.org/10.1088/1742-6596/2265/4/042030.
Full textAbstract:
Abstract Lidar systems are able to measure the wind speed remotely by detecting the aerosol movement caused by wind. A nacelle-based lidar system scanning the wind in front of a wind turbine can provide a preview of the incoming wind before the wind interacts with the turbine. Implementing a realistic lidar simulator into the wind turbine aero-elastic simulation tool can be beneficial for various wind energy related fields, such as lidar-assisted control, load validation, and load monitoring. In previous work, a lidar simulation module has been integrated into the open-source aero-elastic simulation tool OpenFAST, covering already lidar characteristics like different scan patterns, the volume averaging along the beam, and the coupling with the nacelle motion due to turbine tower dynamics. This paper focuses on adding further features to the lidar simulation module of OpenFAST to make the lidar simulation more realistic: the evolving turbulence, the blade blockage effect, and the adjustable data availability. Further, the wind preview quality with the new features is assessed.
49
Bosch, M., A. Leichtman, D. Chilcott, H. Goldberg, and M. Brown. "METRIC EVALUATION PIPELINE FOR 3D MODELING OF URBAN SCENES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W1 (May 31, 2017): 239–46. http://dx.doi.org/10.5194/isprs-archives-xlii-1-w1-239-2017.
Full textAbstract:
Publicly available benchmark data and metric evaluation approaches have been instrumental in enabling research to advance state of the art methods for remote sensing applications in urban 3D modeling. Most publicly available benchmark datasets have consisted of high resolution airborne imagery and lidar suitable for 3D modeling on a relatively modest scale. To enable research in larger scale 3D mapping, we have recently released a public benchmark dataset with multi-view commercial satellite imagery and metrics to compare 3D point clouds with lidar ground truth. We now define a more complete metric evaluation pipeline developed as publicly available open source software to assess semantically labeled 3D models of complex urban scenes derived from multi-view commercial satellite imagery. Evaluation metrics in our pipeline include horizontal and vertical accuracy and completeness, volumetric completeness and correctness, perceptual quality, and model simplicity. Sources of ground truth include airborne lidar and overhead imagery, and we demonstrate a semi-automated process for producing accurate ground truth shape files to characterize building footprints. We validate our current metric evaluation pipeline using 3D models produced using open source multi-view stereo methods. Data and software is made publicly available to enable further research and planned benchmarking activities.
50
Iungo, Giacomo Valerio, Yu-Ting Wu, and Fernando Porté-Agel. "Field Measurements of Wind Turbine Wakes with Lidars." Journal of Atmospheric and Oceanic Technology 30, no. 2 (February 1, 2013): 274–87. http://dx.doi.org/10.1175/jtech-d-12-00051.1.
Full textAbstract:
AbstractField measurements of the wake flow produced from a 2-MW Enercon E-70 wind turbine were performed using three scanning Doppler wind lidars. A GPS-based technique was used to determine the position of the wind turbine and the wind lidar locations, as well as the direction of the laser beams. The lidars used in this study are characterized by a high spatial resolution of 18 m, which allows the detailed characterization of the wind turbine wake. Two-dimensional measurements of wind speed were carried out by scanning a single lidar over the vertical symmetry plane of the wake. The mean axial velocity field was then retrieved by averaging 2D scans performed consecutively. To investigate wake turbulence, single lidar measurements were performed by staring the laser beam at fixed directions and using the maximum sampling frequency. From these tests, peaks in the velocity variance are detected within the wake in correspondence of the turbine top tip height; this enhanced turbulence could represent a source of dangerous fatigue loads for downstream turbines. The spectral density of the measured velocity fluctuations shows a clear inertial-range scaling behavior. Then, simultaneous measurements with two lidars were performed in order to characterize both the axial and the vertical velocity components. For this setup, the two velocity components were retrieved only for measurement points for which the two laser beams crossed nearly at a right angle. Statistics were computed over the sample set for both velocity components, and they showed strong flow fluctuations in the near-wake region at turbine top tip height, with a turbulence intensity of about 30%.