Abstract
We combine observations of optically thin cirrus clouds made by lidar at Davis, Antarctica (69°S, 78°E), during 14–15 June 2011 with a microphysical retrieval algorithm to constrain the ice ...water content (IWC) of these clouds. The cirrus clouds were embedded in a tropopause jet that flowed around a ridge of high pressure extending southward over Davis from the Southern Ocean. Cloud optical depths were 0.082 ± 0.001, and subvisual cirrus were present during 11% of the observation period. The macrophysical cirrus cloud properties obtained during this case study are consistent with those previously reported at lower latitudes. MODIS satellite imagery and AIRS surface temperature data are used as inputs into a radiative transfer model in order to constrain the IWC and ice water path of the cirrus. The derived cloud IWC is consistent with in situ observations made at other locations but at similarly cold temperatures. The optical depths derived from the model agree with those calculated directly from the lidar data. This study demonstrates the value of a combination of ground-based lidar observations and a radiative transfer model in constraining microphysical cloud parameters that could be utilized at locations where other lidar measurements are made.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In the last two decades, airborne LiDAR, as an active remote sensing technique, has emerged as one of the most effective and reliable means of 3D point clouds collection. This paper presents a survey ...of the literature related to these techniques, emphasizing state-of-art trends in system design as well as data processing techniques and their impact on various applications. With the challenging requirements of airborne surveying and mapping, the novel LiDAR system design appears to improve data collection ability and derived product resolution/accuracy. Based on a full range of spectral, spatial and temporal properties of the data obtained, recently proposed methods and techniques are presented here to instigate further possibilities for land and urban topography, forest and bathymetric surveying. The conclusion discusses possible developments for more advanced high performance airborne LiDAR systems, allowing spectral detection and geometrical extraction for improved understanding of urban infrastructure planning and natural resource management.
Currently, with the popularity of smart devices, assured Position Navigation and Time (PNT) is critical for these devices and some fundamental infrastructures, i.e., the power grid. The Global ...Navigation Satellite System (GNSS) is dominant in providing PNT information due to its coverage and high accuracy. However, its signals are weak, and it is vulnerable; multipath and None-Line-Of-Signals (NLOS) are the major errors that occur with regard to the GNSS in applications in urban areas. Advanced signal processing methods are expected to improve its resilience and assurance. In addition, the GNSS is fragile to interference and spoofing, which should be emphasized for unmanned systems and smart devices. This Special Issue aimed to provide a platform for researchers to publish innovative work on the advanced technologies for position and navigation under GNSS signal-challenging or -denied environments.
•This paper reported that a Na-K lidar was built at 2016 at são josé dos Compose, Brazil, by the joint work of NSSC and INPE. This system realized the potassium and sodium metal layer at the ...simultaneously observe in Brazil, and this is the first time of potassium layer detection in South America.•The original echo photon count of potassium layer is about 1633 (200 s, 96 m) and the signal-to-noise ratio is up to 40:1. Compared with the available detection results of Germany reported that using all-solid-state laser system detection potassium layer obtained 357 photons (1 min, 100 m), and the Na-K lidar observe in Brazil obtained 450 photons with the same resolution.The detection capability of potassium lidar has reached the leading position.•The simultaneous phenomena of Nas and Ks, and a ultra-high density K layers have been observed, the K density in these narrow layers exceeds 1019 cm−3.
This paper reports that the sodium–potassium (Na–K) lidar was completed in November 2016 at São José Dos Compose, Brazil (23°S, 45°W), by the joint effort of the National Space Science Center, Chinese Academy of Sciences (NSSC) and Instituto Nacional de Pesquisas Espaciais (INPE). This system realized the Na and K metal layers simultaneously observe in Brazil, and this is the first instance of K layer detection in South America. Some of the key parameters and technologies have been optimized based on the Na and K layer dual-wave lidar in Beijing Yanqing station, such as improve technical parameters for receiving telescope, the narrow linewidth, efficient laser frequency doubling, the wavelength automatic locking techniques. By adopting these technologies, the output were 589 nm and 770 nm lasers, with high emission powers of 75 mJ and 83 mJ, respectively, and backscattered signals of Na and K layers with high signal quality were obtained. Observation data showed that the original echo photon count of the Na layer was approximately 42,486 (time resolution: 200 s, spatial resolution: 96 m) and the number of noise photons was 286 in a single data acquisition. The signal-to-noise ratio was up to 205:1. At the same spatiotemporal resolution, the original echo photon count of the K layer was approximately 1633, the noise photons were 38, and the signal-to-noise ratio was up to 40:1. The initial photocounts received has demonstrated that the Brazil K lidar has produced high quality signal with signal-to-noise level required by intended science studies. Moreover, the simultaneous phenomena of sporadic Na (Nas) and sporadic K (Ks), and the highly concentrated layers of atomic K have been observed, the K density in these narrow layers exceeds 1019 cm−3.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Determining the extrinsic parameter between multiple light detection and rangings (LiDARs) and cameras is essential for autonomous robots, especially for solid-state LiDARs, where each LiDAR unit has ...a very small field-of-view (FoV), and multiple units are often used collectively. The majority of extrinsic calibration methods are proposed for 360° mechanical spinning LiDARs where the FoV overlap with other LiDAR or camera sensors is assumed. A few research works have been focused on the calibration of small FoV LiDARs and cameras nor on the improvement of the calibration speed. In this work, we consider the problem of extrinsic calibration among small FoV LiDARs, and cameras, with the aim to shorten the total calibration time and further improve the calibration precision. We first implement an adaptive voxelization technique in the extraction and matching of LiDAR feature points. Such a process could avoid the redundant creation of <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>-d trees in LiDAR extrinsic calibration and extract LiDAR feature points in a more reliable and fast manner than existing methods. We then formulate the multiple LiDAR extrinsic calibration into a LiDAR bundle adjustment (BA) problem. By deriving the cost function up to second order, the solving time and precision of the nonlinear least square problem are further boosted. Our proposed method has been verified on data collected in four targetless scenes and under two types of solid-state LiDARs with a completely different scanning pattern, density, and FoV. The robustness of our work has also been validated under eight initial setups, with each setup containing 100 independent trials. Compared with the state-of-the-art methods, our work has increased the calibration speed 15 times for LiDAR-LiDAR extrinsic calibration (averaged result from 100 independent trials) and 1.5 times for LiDAR-camera extrinsic calibration (averaged result from 50 independent trials) while remaining accurate. To benefit the robotics community, we have also open-sourced our implementation code on GitHub.
Multi‐temporal digital terrain models (DTMs) derived from airborne or uncrewed aerial vehicle (UAV)‐borne light detection and ranging (LiDAR) platforms are frequently used tools in geomorphic impact ...studies. Accurate estimation of mobilized sediments from multi‐temporal DTMs is indispensable for hazard assessment. To study volumetric changes in alpine environments it is crucial to identify and discuss different kind of error sources in multi‐temporal data. We subdivided errors into those caused by data acquisition, data processing, and spatial properties of the terrain. In terms of the quantification of surface changes, the propagation of errors can lead to high uncertainties.
Three alpine catchments with different LiDAR point clouds of different origins (airborne laser scanning ALS, UAV‐borne laser scanning ULS), varying point densities, accuracies and qualities were analysed, and used as basis for interpolating DTMs. The workflow was developed in the Schöttlbach area in Styria and later applied to further catchments in Austria. The main aim of the presented work is a comprehensive DTM uncertainty analysis specially designed for geomorphic impact studies, with a resulting uncertainty analysis serving as input for a change detection tool. Our findings reveal that geomorphic impact studies need the careful distinction between actual surface changes and different data uncertainties. ULS combines the benefits of terrestrial laser scanning with all the benefits of ALS. However, the use of ULS data does not necessarily improve the results of the analysis since the high level of detail is not always helpful in geomorphic impact studies. In order to make the different point clouds and DTMs comparable the quality of the ULS point cloud had to be reduced to fit the accuracy of the reference data (older ALS point clouds). Using a point cloud with a high point density with a regular planimetric point spacing and less data gaps, in the best case collected during leaf‐off conditions (e.g., cross‐flight strategy) turned out to be sufficient for our geomorphic research purposes.
Our work shows that geomorphic impact studies need a careful distinction between surface change and inherent data noise. A comprehensive DTM uncertainty analysis was applied to ensure the quality of geomorphic impact studies. ULS combines the benefits of TLS with all the benefits from ALS. Quality differences between ULS and ALS lead to significant limitations in the quality of geomorphic impact studies. The full potential of ULS data (high point density, representation of small‐scale structures) can only be used when being compared to data with a similar or same accuracy and quality.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Abstract
The boundary layer controls on shallow cumulus (ShCu) convection are examined using a suite of remote and in situ sensors at ARM Southern Great Plains (SGP). A key instrument in the study is ...a Doppler lidar that measures vertical velocity in the CBL and along cloud base. Using a sample of 138 ShCu days, the composite structure of the ShCu CBL is examined, revealing increased vertical velocity (VV) variance during periods of medium cloud cover and higher VV skewness on ShCu days than on clear-sky days. The subcloud circulations of 1791 individual cumuli are also examined. From these data, we show that cloud-base updrafts, normalized by convective velocity, vary as a function of updraft width normalized by CBL depth. It is also found that 63% of clouds have positive cloud-base mass flux and are linked to coherent updrafts extending over the depth of the CBL. In contrast, negative mass flux clouds lack coherent subcloud updrafts. Both sets of clouds possess narrow downdrafts extending from the cloud edges into the subcloud layer. These downdrafts are also present adjacent to cloud-free updrafts, suggesting they are mechanical in origin. The cloud-base updraft data are subsequently combined with observations of convective inhibition to form dimensionless “cloud inhibition” (CI) parameters. Updraft fraction and liquid water path are shown to vary inversely with CI, a finding consistent with CIN-based closures used in convective parameterizations. However, we also demonstrate a limited link between CBL vertical velocity variance and cloud-base updrafts, suggesting that additional factors, including updraft width, are necessary predictors for cloud-base updrafts.
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Accurate and efficient registration of unmanned aerial vehicle light detection and ranging (UAV‐lidar) and terrestrial lidar (T‐lidar) data is crucial for forest structure parameter extraction. This ...study proposes a novel method based on a starburst pattern for the automatic registration of UAV‐lidar and T‐lidar data in forest scenes. It employs density‐based spatial clustering of applications with noise (DBSCAN) for individual tree identification, constructs starburst patterns separately from both lidar sources, and utilises polar coordinate rotation and matching to achieve coarse registration. Fine registration is achieved using the iterative closest point (ICP) algorithm. Experimental results demonstrate that the starburst‐pattern‐based method achieves the desired registration accuracy (average coarse registration error of 0.157 m). Further optimisation with ICP yields slight improvements with an average fine registration error of 0.149 m. Remarkably, the proposed method is insensitive to the individual tree detection number when exceeding 10, and the tree position error has minimal impact on registration accuracy. Furthermore, our proposed method outperforms two existing methods in T‐lidar and UAV‐lidar registration over forest environments.
This study proposed a novel method based on a starburst pattern to achieve the automated registration of unmanned aerial vehicle light detection and ranging (UAV‐lidar) and terrestrial lidar (T‐lidar) point clouds in forests. The proposed method outperforms the existing methods in T‐lidar and UAV‐lidar point cloud registration in forest environments and demonstrates high robustness.
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Atmospheric water vapor is a crucial factor in the Earth's water cycle. As an important greenhouse gas, changes in the spatio‐temporal distribution of atmospheric water vapor can contribute to the ...occurrence of various extreme weather phenomena. Lidar, with its high spatial and temporal resolutions, has great potential for applications in water vapor profile detection. Raman lidar and differential absorption lidar (DIAL) have been successfully used to detect atmospheric water vapor. System calibration is crucial to ensure that the measured profile accurately represents the concentration profile of atmospheric water vapor. Choosing an effective system calibration method can ensure the accuracy of long‐term lidar measurements. This paper reviews the latest progress and applications of atmospheric water vapor lidar calibration in recent years. The basic principles of Raman lidar and DIAL calibration are introduced. Various methods and benefits of system calibration are discussed. Raman lidar has three commonly used calibration methods: external calibration, internal calibration, and hybrid calibration methods. The most commonly used method is external calibration based on radiosondes. DIAL is usually implemented with an advantageous self‐calibration method. Finally, potential development directions for atmospheric water vapor lidar and calibration technology are discussed.
This article is categorized under:
Science of Water > Methods
Engineering Water > Methods
Human Water > Value of Water
How can I be sure that the profile measured by lidar is the true water vapor concentration profile? System calibration can answer this question. Choosing the perfect system calibration method can guarantee the long‐term accuracy of lidar measurements.
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