We present the demonstration of an integrated frequency modulated continuous wave LiDAR on a silicon platform. The waveform calibration, the scanning system, and the balanced detectors are ...implemented on a chip. Detection and ranging of a moving hard target at upto 60 m with less than 5 mW of output power is demonstrated in this paper.
Deriving land cover from remotely sensed data is fundamental to many operational mapping and reporting programs as well as providing core information to support science activities. The ability to ...generate land cover maps has benefited from free and open access to imagery, as well as increased storage and computational power. The accuracy of the land cover maps is directly linked to the calibration (or training) data used, the predictors and ancillary data included in the classification model, and the implementation of the classification, among other factors (e.g., classification algorithm, land cover heterogeneity). Various means for improving calibration data can be implemented, including using independent datasets to further refine training data prior to mapping. Opportunities also arise from a profusion of possible calibration datasets from pre-existing land cover products (static and time series) and forest inventory maps through to observation from airborne and spaceborne lidar observations. In this research, for the 650 Mha forested ecosystems of Canada, we explored approaches to refine calibration data, integrate novel predictors, and optimize classifier implementation. We refined calibration data using measures of forest vertical structure, integrated novel spatial (via distance-to metrics) model predictors, and implemented a regionalized approach for optimizing training data selection and model-building to ensure local relevance of calibration data and capture of regional variability in land cover conditions. We found that additional vetting of training data involved the removal of 44.7% of erroneous samples (e.g. treed vegetation without vertical structure) from the training pool. Nationally, distance to ephemeral waterbodies was a key predictor of land cover, while the importance of distance to permanent water bodies varied on a regional basis. Regionalization of model implementation ensured that classification models used locally relevant descriptors and resulted in improved classification outcomes (overall accuracy: 77.9% ± 1.4%) compared to a generalized, national model (70.3% ± 2.5%). The methodological developments presented herein are portable to other land cover projects, monitoring programs, and remotely sensed data sources. The increasing availability of remotely sensed data for land cover mapping, as well as non-image data for aiding with model development (from calibration data to complementary spatial data layers) provide new opportunities to improve and further automate land cover mapping procedures.
•Methodological framework to produce annual land cover from Landsat time series•Training data derived from existing land cover products and refined using lidar data•Novel distance-to surfaces to inform models with spatial-ecological information used•A regionalized approach to training data selection and model development implemented•Open datasets with roles in training and modeling serve to improve land cover maps
Im Zusammenhang mit dem Erreichen der Klimaziele durch den Einsatz erneuerbarer Energien wurde in der Physikalisch-Technischen Bundesanstalt (PTB) in den letzten Jahren ein bistatisches Wind-Lidar ...(Light detection and ranging) entwickelt und aufgebaut. Dieses Wind-Lidar ermöglicht die für Windenergieanlagen notwendige Rückführung von Windgeschwindigkeiten in Höhen von 5 m bis 250 m mit kleinsten Messunsicherheiten in beliebigem Gelände, und stellt damit erstmals eine unabhängige Alternative zu bisher eingesetzten, kostspieligen Windmessmasten dar. Der geplante Einsatz des PTB-Lidars als rückgeführtes Transfernormal im Bereich der Windfernmessung erfordert neben vorherigen Vergleichsmessungen mit anderen Windfernmesssystemen in freiem Gelände auch eine detaillierte Untersuchung des PTB-Lidars unter kontrollierbaren Strömungsbedingungen zur Validierung seiner Messunsicherheit und Überwachung seiner Langzeitstabilität. Aus diesem Grund wurde im Kompetenzzentrum für Windenergie (CCW) der PTB ein neuer, speziell konstruierter Windkanal mit einem Laser-Doppler-Anemometer (LDA) als Strömungsgeschwindigkeitsnormal auf einer Plattform in 8 m Höhe errichtet. Dies ermöglicht es, das PTB-Lidar unterhalb der Messstrecke des Windkanals zu positionieren und auf die SI-Einheiten-rückgeführte Strömungsgeschwindigkeitsmessungen mit dem Wind-Lidar durchzuführen. Der Windkanal nach Göttinger Bauart hat eine offene Messstrecke mit einer Länge von 75 cm und einer Querschnittsfläche von 50 × 50 cm
. In der Messstrecke wird eine hohe Strömungshomogenität und ein niedriger Turbulenzgrad von <0,35 % im Geschwindigkeitsbereich von 1 m/s bis 30 m/s erreicht. Die erweiterte Messunsicherheit des LDA-Referenznormals beträgt 0,16 %. Sämtliche im Windkanal durchgeführten Vergleichsmessungen zeigen eine Geschwindigkeitsabweichung zwischen dem Lidar-System und dem LDA-Referenznormal von unter ±0,5 %. Eine Optimierung der Methode zur Positionierung und damit Lokalisierung des Lidar-Messvolumens in der Windkanalmessstrecke über einen dünnen Partikelfilm führte zu einer reproduzierten Verringerung der Geschwindigkeitsabweichung auf circa −0,10 %.
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.
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.
•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.
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.
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.
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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