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At least 55 records · Page 3

Perspectives of active Si photonics devices for data communication and optical sensing

Si photonics has made rapid progress in research and commercialization in the past two decades. While it started with electronic–photonic integration on Si to overcome the interconnect bottleneck in data communications, Si photonics has now greatly expanded into optical sensing, light detection and ranging (LiDAR), optical computing, and microwave/RF photonics applications. From an applied physics point of view, this perspective discusses novel materials and integration schemes of active Si photonics devices for a broad range of applications in data communications, spectrally extended complementary metal–oxide–semiconductor (CMOS) image sensing, as well as 3D imaging for LiDAR systems. We also present a brief outlook of future synergy between Si photonic integrated circuits and Si CMOS image sensors toward ultrahigh capacity optical I/O, ultrafast imaging systems, and ultrahigh sensitivity lab-on-chip molecular biosensing.

electronic band structure↗

Machine-learning identification of the variability of mean velocity and turbulence intensity for wakes generated by onshore wind turbines: Cluster analysis of wind LiDAR measurements

Light detection and ranging (LiDAR) measurements of isolated wakes generated by wind turbines installed at an onshore wind farm are leveraged to characterize the variability of the wake mean velocity and turbulence intensity during typical operations, which encompass a breadth of atmospheric stability regimes and rotor thrust coefficients. The LiDAR measurements are clustered through the k-means algorithm, which enables identifying the most representative realizations of wind turbine wakes while avoiding the imposition of thresholds for the various wind and turbine parameters. Considering the large number of LiDAR samples collected to probe the wake velocity field, the dimensionality of the experimental dataset is reduced by projecting the LiDAR data on an intelligently truncated basis obtained with the proper orthogonal decomposition (POD). The coefficients of only five physics-informed POD modes are then injected in the k-means algorithm for clustering the LiDAR dataset. The analysis of the clustered LiDAR data and the associated supervisory control and data acquisition and meteorological data enables the study of the variability of the wake velocity deficit, wake extent, and wake-added turbulence intensity for different thrust coefficients of the turbine rotor and regimes of atmospheric stability. Furthermore, the cluster analysis of the LiDAR data allows for the identification of systematic off-design operations with a certain yaw misalignment of the turbine rotor with the mean wind direction.

17 WIND ENERGY↗

NEON AOP Survey of Upper East River CO Watersheds: Waveform LiDAR Binary Data

The waveform Light Detection and Ranging (LiDAR) data in this package were generated through a National Ecological Observatory Network Airborne Observation Platform (NEON AOP) acquisition over watersheds of interest surrounding Crested Butte, Colorado. The remote sensing imagery acquired by the NEON AOP supports an interdisciplinary project on hydrology, biogeochemistry, and ecosystem functioning in a snow-dominated headwater environment. These waveform LiDAR data enable spatially continuous estimation of vegetation structure parameters to facilitate analyses of the major environmental drivers of structural and compositional variability. The package contains 97 compressed file archives in 7-zip (.7z) format, each corresponding to one acquisition flightpath. Within each .7z archive is a set of constituent files describing properties of the LiDAR waveforms, such as return intensity, geolocation, outgoing pulse and other behavior of the sensor and signals. Once downloaded, the files must first be unzipped using the widely distributed command-line software utility 7z, using the command '7z x \[filename\].7z \[target_directory\]'. All files within the .7z archives can be opened in IDL, MatLab, or the open-source R statistical computing environment. Further details about the data package are in the attached user guide (neon_aop_crbu_waveformlidar_userguide.pdf). This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

Solid-State, High Energy 2-Micron Laser Development for Space-Based Remote Sensing

Lidar (light detection and ranging) remote sensing enjoys the advantages of excellent vertical and horizontal resolution; pointing capability; a signal source independent from natural light; and control and knowledge of transmitted wavelength, pulse shape, and polarization and received polarization. Lidar in space is an emerging technology now being developing to fit applications where passive sensors cannot meet current measurement requirements. Technical requirements for space lidar are more demanding than for ground-based or airborne systems. Perhaps the most distinguishing characteristics of space lidars are the environmental requirements. Space lidar systems must be specially designed to survive the mechanical vibration loads of launch and operate in the vacuum of space where exposure to ionizing radiation limits the electronic components available. Finally, space lidars must be designed to be highly reliable because they must operate without the need for repair or adjustment. Lifetime requirements tend to be important drivers of the overall system design. The maturity of the required technologies is a key to the development of any space lidar system. NASA entered a new era in the 1990 s with the approval of several space-based remote sensing missions employing laser radar (lidar) techniques. Following the steps of passive remote sensing and then active radar remote sensing, lidar sensors were a logical next step, providing independence from natural light sources, and better spatial resolution and smaller sensor size than radar sensors. The shorter electromagnetic wavelengths of laser light also allowed signal reflectance from air molecules and aerosol particles. The smaller receiver apertures allowed the concept of scanning the sensor field of view. However, technical problems with several space-based lidar missions during that decade led to concern at NASA about the risk of lidar missions. An external panel was convened to make recommendations to NASA. Their report in 2000 strongly advocated that NASA maintain in-house laser and lidar capability, and that NASA should work to lower the technology risk for all future lidar missions. A multi-Center NASA team formulated an integrated NASA strategy to provide the technology and maturity of systems necessary to make Lidar/Laser systems viable for space-based study and monitoring of the Earth's atmosphere. In 2002 the NASA Earth Science Enterprise (ESE) and Office of Aerospace Technology (OAT) created the Laser Risk Reduction Program (LRRP) and directed NASA Langley Research Center (LaRC) and Goddard Space Flight Center to carry out synergistic and complementary research towards solid-state lasers/lidars developments for space-based remote sensing applications.

Singh, Upendra N.↗

Evaluation of some wide dynamic range readout systems for photoelectric integrating spectrometers

Five types of electronic circuits commonly used for readout of currents from photomultiplier tubes were evaluated. This evaluation was conducted to define the experimental limits of achieving the widest possible dynamic range of light detection and concentration measurements in spectrochemical analysis. The circuits evaluated included the photon-counting technique and four dc circuits. These circuits displayed a dynamic range from 3 to about 4.5 decades within a repeatability criterion of 1 percent, or better. The maximum dynamic range allowed by the photomultiplier tube in this application was estimated to be about 6 decades.

Franklin, M. L.↗

The Kinematic Navigation and Cartography Knapsack (KNaCK) LiDAR System: Overview and Applications.

Improved terrain characterization and navigation sensors and methods are needed to enhance crew safety, ISRU return, and scientific understanding of future landing sites. Specific to the Artemis Program and sustained exploration at the lunar South Pole, extreme low-angle solar illumination conditions pose significant challenges to existing photogrammetry-based robotic navigation. Additionally, a major challenge for navigation on the Moon and other planetary surfaces is the lack of Global Positioning and Navigation Systems (GPS or GNSS). Thus, there is a need for an alternative to image-based navigation that allow for precise and accurate mapping in GPS-denied environments on any planetary body. Here, we describe the Kinematic Navigation and Cartography Knapsack (KNaCK) LiDAR system; a backpack-mounted, mobile navigation and terrain mapping system that uses a velocity-sensing coherent light detection and ranging (LiDAR) system based on a frequency modulated continuous wave (FMCW) technique, contains minimal moving parts, and employs sophisticated positioning algorithms. During a traverse, this instrument emits light pulses to continually scan a scene to build a three-dimensional point cloud representation of topography. A measure of the Doppler-velocity at each of millions of range points sampled per second allows for a 6 degree of freedom (6- DoF) estimate of the sensor’s position and the development of novel position-from-velocity mapping and positioning algorithms for loop-closure in GPS denied environments. Included with paper is the video presentation for the Figure 2: FMCW-LiDAR sensor on Kinematic Navigation and Cartography Knapsack (KNaCK) (Aeva Aeries 1)

M. Zanetti↗

Space-Based Lidar Systems

An overview of space-based lidar systems is presented. from the first laser altimeter on APOLLO 15 mission in 1971 to the Mercury Laser Altimeter on MESSENGER mission currently in orbit, and those currently under development. Lidar, which stands for Light Detection And Ranging, is a powerful tool in remote sensing from space. Compared to radars, lidars operate at a much shorter wavelength with a much narrower beam and much smaller transmitter and receiver. Compared to passive remote sensing instruments. lidars carry their own light sources and can continue measuring day and night. and over polar regions. There are mainly two types of lidars depending on the types of measurements. lidars that are designed to measure the distance and properties of hard targets are often called laser rangers or laser altimeters. They are used to obtain the surface elevation and global shape of a planet from the laser pulse time-of-night and the spacecraft orbit position. lidars that are designed to measure the backscattering and absorption of a volume scatter, such as clouds and aerosols, are often just called lidars and categorized by their measurements. such as cloud and aerosol lidar, wind lidar, CO2 lidar, and so on. The advantages of space-based lidar systems over ground based lidars are the abilities of global coverage and continuous measurements.

Sun, Xiaoli↗

Gas dispersion measurements using a mobile Raman lidar system

The exploitation of natural gas resources to supply energy demands has resulted in the need to engineer pipelines and plants capable of handling extremely high pressures and throughputs. Consequently, more attention has been directed to evaluating the consequences of releases of material whether accidental or deliberate in nature. An important aspect of assessing the consequences of a release is an understanding of how gas disperses in the atmosphere over a wide range of release and atmospheric conditions. The most cost effective way of providing such information is through the development and use of reliable theoretical prediction methods. The need for some form of remote sensing device was identified. The various possibilities studied led to the conclusion that LIDAR (Light Detection And Ranging) offered the most suitable method. The system designed and built is described, and its recent use in monitoring operational ventings from a high pressure transmission system is discussed.

Houston, J. D.↗

Topographic Quintet: Comparing Five Methods for Measuring Ultra-High Resolution Topography

We compare different methods for collecting ultra-high resolution topography data within an analog planetary, human landing site scale area. Our aim is to investigate the cost and benefits of different 3D terrain mapping techniques, their associated data collection methods, and how their different specifications (e.g., range, spatial resolution, scanning-time, mobility, operating constraints, GPS-Denied operation, etc.) might be applied to landing-site characterization and mission operations. We compare 3D terrain data collected during a field campaign in November 2021 from an outcrop at Kilbourne Hole in southern New Mexico using different Light Detection and Ranging (LiDAR) sensors on the ground and stereo-derived 3D data from framing cameras mounted on small uncrewed aerial systems (sUAS).Our foci for this experiment are ground-based, surveying, and autonomous vehicle-type 3D scanning sensors that might be used for planetary surface exploration from landed assets (e.g., lander, rover, astronaut-mounted sensors, decent imaging, hoppers, or drones).[e.g. 1]This test is not meant to benchmark these scanners against one another, nor provide a recommendation for a specific make or model. Rather, our goal is to quantify time, effort, resolution, and operational trade-offs that are important for selecting a topographic instrument/methodology for a given scope of terrain characterization. Our results indicate that each technique is capable of exceptional quality terrain characterization for planetary exploration and scientific inquiry, but we hypothesize the appropriate technique is highly dependent on the scope of operational specifications and science requirements.

P Whelley↗

Improving Land Cover Classification Using Extended Multi-Attribute Profiles (EMAP) Enhanced Color, Near Infrared, and LiDAR Data

Hyperspectral (HS) data have found a wide range of applications in recent years. Researchers observed that more spectral information helps land cover classification performance in many cases. However, in some practical applications, HS data may not be available, due to cost, data storage, or bandwidth issues. Instead, users may only have RGB and near infrared (NIR) bands available for land cover classification. Sometimes, light detection and ranging (LiDAR) data may also be available to assist land cover classification. A natural research problem is to investigate how well land cover classification can be achieved under the aforementioned data constraints. In this paper, we investigate the performance of land cover classification while only using four bands (RGB+NIR) or five bands (RGB+NIR+LiDAR). A number of algorithms have been applied to a well-known dataset (2013 IEEE Geoscience and Remote Sensing Society Data Fusion Contest). One key observation is that some algorithms can achieve better land cover classification performance by using only four bands as compared to that of using all 144 bands in the original hyperspectral data with the help of synthetic bands generated by Extended Multi-attribute Profiles (EMAP). Moreover, LiDAR data do improve the land cover classification performance even further.

58 GEOSCIENCES↗

Development of flashlamp-pumped Q-switched Ho:Tm:Cr:YAG lasers for mid-infrared LIDAR application

A flashlamp-pumped 2.1 micron Ho:Tm:Cr:YAG laser was studied for both normal mode and Q-switched operations under a wide variety of experimental conditions in order to optimize performance. Laser output energy, slope efficiency, threshold and pulselength were determined as a function of operating temperature, output mirror reflectivity, input electrical energy and Q-switch opening time. The measured normal-mode laser thresholds of a Ho(3+) (0.45 atomic percent):Tm(3+) (2.5 atomic percent):Cr(3+) (0.8 atomic percent):YAG crystal ranged form 26 to 50 J between 120 and 200 K with slope efficiencies up to 0.36 percent with a 60 percent reflective output mirror. Under Q-switched operation the slope efficiency was 90 percent of the normal-mode result. Development of solid state lasers with Ho(3+), Tm(3+) and/or Er(3+) doped crystals has been pursued by NASA for eye-dafe mid-infrared LIDAR (light detection and ranging) application. As a part of the project, the authors have been working on evaluating Ho(3+):Tm(3+):Cr(3+):YAG crystals for normal-mode and Q-switched 2.1 micron laser operations in order to determine an optimum Tm(3+) concentration under flashlamp pumping conditions. Lasing properties of the Ho(3+) in the mid-infrared region have been studied by many research groups since the early 1960's. However, the technology of those lasers is still premature for lidar application. In order to overcome the inefficiency related to narrow absorption bands of the Ho(3+), Tm(3+) and Er(3+), the erbium has been replaced by chromium. The improvement in flashlamp-pumped Ho(3+) laser efficiency has been demonstrated recently by several research groups by utilizing the broad absorption spectrum of Cr(3+) which covers the flashlamp's emission spectrum. Efficient energy transfer to the Tm(3+) and then the Ho(3+) occurs subsequently. It is known that high Tm(3+) concentration and low Ho(3+) concentration are preferred to achieve a quantum efficiency approaching two and to avoid large reabsorption losses. However, determination of the optimum Tm(3+) concentration required to ensure efficient energy transfer from Cr(3+) to Tm(3+) and from Tm(3+) to Ho(3+) has not been made in the Ho:Tm:CR:YAG crystal. The results obtained so far are given.

Choi, Young S.↗

Use of an Uninhabited Aircraft System (UAS) for Atmospheric Observations During an Acoustic Flight Test

A jet noise test was performed at Niagara Falls International Airport using a Calspan Learjet 25 by acoustics researchers at NASA Glenn Research Center in partnership with Calspan personnel and Uninhabited Aircraft Systems (UAS) pilots and sensor operators from NASA Langley Research Center. To account for atmospheric attenuation in the de-propagation of jet noise from a ground-based microphone array to the source for comparison with model data collected in a facility at NASA GRC, a vertical profile of atmospheric conditions was required. To that end, a sUAS was flown with a weather sensor package measuring atmospheric pressure, humidity, and temperature in a range of altitudes from ground level to 304.8 m (1,000 ft) above ground level (AGL). The sUAS flights were performed concurrently with and adjacent to the Learjet flight path. Data from these UAS flights are presented herein; additionally, comparisons with conventional balloon-borne instrumentation are made with a particular focus on the quality and capability of UAS-based observations for acoustic flight test applications. Furthermore, a ground-based light detection and ranging (LiDAR) system was deployed for collecting wind magnitude and direction for discrete altitudes up to 304.8 m (1,000 ft) AGL. Data from the LiDAR unit will be presented and discussed in the context of aircraft acoustic flight testing. This effort was supported by NASA’s Commercial Supersonic Technology project.

UAS↗

Simulation of Satellite, Airborne and Terrestrial LiDAR with DART (I):Waveform Simulation with Quasi-Monte Carlo Ray Tracing

Light Detection And Ranging (LiDAR) provides unique data on the 3-D structure of atmosphere constituents and the Earth's surface. Simulating LiDAR returns for different laser technologies and Earth scenes is fundamental for evaluating and interpreting signal and noise in LiDAR data. Different types of models are capable of simulating LiDAR waveforms of Earth surfaces. Semi-empirical and geometric models can be imprecise because they rely on simplified simulations of Earth surfaces and light interaction mechanisms. On the other hand, Monte Carlo ray tracing (MCRT) models are potentially accurate but require long computational time. Here, we present a new LiDAR waveform simulation tool that is based on the introduction of a quasi-Monte Carlo ray tracing approach in the Discrete Anisotropic Radiative Transfer (DART) model. Two new approaches, the so-called "box method" and "Ray Carlo method", are implemented to provide robust and accurate simulations of LiDAR waveforms for any landscape, atmosphere and LiDAR sensor configuration (view direction, footprint size, pulse characteristics, etc.). The box method accelerates the selection of the scattering direction of a photon in the presence of scatterers with non-invertible phase function. The Ray Carlo method brings traditional ray-tracking into MCRT simulation, which makes computational time independent of LiDAR field of view (FOV) and reception solid angle. Both methods are fast enough for simulating multi-pulse acquisition. Sensitivity studies with various landscapes and atmosphere constituents are presented, and the simulated LiDAR signals compare favorably with their associated reflectance images and Laser Vegetation Imaging Sensor (LVIS) waveforms. The LiDAR module is fully integrated into DART, enabling more detailed simulations of LiDAR sensitivity to specific scene elements (e.g., atmospheric aerosols, leaf area, branches, or topography) and sensor configuration for airborne or satellite LiDAR sensors.

Gastellu-Etchegorry, Jean-Philippe↗

The Intelligent Landing System for Safe and Precise Landing on Europa

Europa, the smallest of Jupiter’s Galilean moons, is thought to harbor a vast liquid water ocean beneath its icy crust, making it one of the most scientifically intriguing targets for a robotic surface sampling mission in our Solar System. However, autonomously landing a spacecraft safely and precisely on Europa poses unique challenges, such as very little existing high-resolution reconnaissance imagery, a surface expected to be very rough and hazardous over a wide range of scales, an extremely intense ionizing radiation environment, and very limited lander resources for mass and volume. To address these challenges, we propose a novel Intelligent Landing System (ILS) combining four Guidance, Navigation & Control (GN&C) sensing functions – velocimetry, altimetry, map-relative localization, and hazard detection – that would together enable safe and precise landing on Europa’s surface. The ILS is a smart sensor system, combining an inertial measurement unit (IMU), a monocular, passive-optical camera, and a light detection and ranging (Li-DAR) sensor with dedicated computing resources as well as an onboard 3D terrain map. The ILS leverages more than a decade of technology development from programs such as the Lander Vision System, currently baselined on the Mars 2020 mission. This paper provides a detailed description of the proposed ILS architecture and concept of operations, as well as select preliminary simulation results to assess performance and robustness.

Trawny, Nikolas↗

Hydrologic Evaluation of Smallmouth Bass Spawning Sites in the Upper Green River Using LiDAR

The smallmouth bass has been considered one of the most problematic invasive species in the upper Colorado River basin. As a predator of larval fish and juveniles, this nonnative species is an impediment to conservation efforts for endangered fish species of the Colorado River basin including Colorado pikeminnow (Ptychocheilus lucius), razorback sucker (Xyrauchen texanus), humpback chub (Gila cypha), and bonytail chub (Gila elegans). Several measures have been recommended to control smallmouth bass populations to conserve the endangered fish species. Among these measures are efforts to control flows during the spawning season to disrupt smallmouth bass reproduction. Previous work has suggested that smallmouth bass spawning in areas of the Green River could be inhibited during higher flows from the Flaming Gorge Dam due to lack of suitable habitat. Little research has been conducted to evaluate an optimal range of flow increases (“flow spikes”) needed to disrupt smallmouth bass reproduction in the Green River. Current research proposals to evaluate the effectiveness of flow spikes on controlling smallmouth bass reproduction target post-spawning flows of 4,500 cfs, maintained for three days, to inundate side-channel spawning habitats. In this report, we present results of a topographic study of smallmouth bass spawning sites in the upper Green River to characterize flow levels needed to inundate spawning habitats. This study used remotely sensed Light Detection and Ranging (LiDAR) data collected along the entire Green River, including channel margins and floodplain areas, to model water surface elevations and flow spikes needed to connect and inundate smallmouth bass spawning sites.

59 BASIC BIOLOGICAL SCIENCES↗

Applications of ArcticDEM for measuring volcanic dynamics, landslides, retrogressive thaw slumps, snowdrifts, and vegetation heights

Topographical changes are of fundamental interest to a wide range of Arctic science disciplines faced with the need to anticipate, monitor, and respond to the effects of climate change, including geohazard management, glaciology, hydrology, permafrost, and ecology. This study demonstrates several geomorphological, cryospheric, and biophysical applications of ArcticDEM – a large collection of publicly available, time-dependent digital elevation models (DEMs) of the Arctic. Our study illustrates ArcticDEM's applicability across different disciplines and five orders of magnitude of elevation derivatives, including measuring volcanic lava flows, ice cauldrons, post-failure landslides, retrogressive thaw slumps, snowdrifts, and tundra vegetation heights. We quantified surface elevation changes in different geological settings and conditions using the time series of ArcticDEM. Following the 2014–2015 Bárðarbunga eruption in Iceland, ArcticDEM analysis mapped the lava flow field, and revealed the post-eruptive ice flows and ice cauldron dynamics. The total dense-rock equivalent (DRE) volume of lava flows is estimated to be (1431 ± 2) million m 3 . Then, we present the aftermath of a landslide in Kinnikinnick, Alaska, yielding a total landslide volume of (400 ± 8) × 103 m 3 and a total area of 0.025 km 2 . ArcticDEM is further proven useful for studying retrogressive thaw slumps (RTS). The ArcticDEM-mapped RTS profile is validated by ICESat-2 and drone photogrammetry resulting in a standard deviation of 0.5 m. Volume estimates for lake-side and hillslope RTSs range between 40,000 ± 9000 m 3 and 1,160,000 ± 85,000 m 3 , highlighting applicability across a range of RTS magnitudes. A case study for mapping tundra snow demonstrates ArcticDEM's potential for identifying high-accumulation, late-lying snow areas. The approach proves effective in quantifying relative snow accumulation rather than absolute values (standard deviation of 0.25 m, bias of −0.41 m, and a correlation coefficient of 0.69 with snow depth estimated by unmanned aerial systems photogrammetry). Furthermore, ArcticDEM data show its feasibility for estimating tundra vegetation heights with a standard deviation of 0.3 m (no bias) and a correlation up to 0.8 compared to the light detection and ranging (LiDAR). The demonstrated capabilities of ArcticDEM will pave the way for the broad and pan-Arctic use of this new data source for many disciplines, especially when combined with other imagery products. The wide range of signals embedded in ArcticDEM underscores the potential challenges in deciphering signals in regions affected by various geological processes and environmental influences.

Chunli Dai↗

Modulation induced by very-large-scale motions on the inclination angle of wall-attached eddies: an atmospheric surface layer experiment

The forward leaning inclination angle, 𝛾, of coherent turbulent structures is a well-known feature of wall-bounded turbulent flows. Although invariant across friction Reynolds numbers within the range 𝑅𝑒 𝜏 =10 3 −10 6 , 𝛾 can vary significantly across turbulent scales within a high-Reynolds-number flow. Very-large-scale motions (VLSMs) are known to induce significant changes in the instantaneous shear profile, which is a conditioning event that could trigger variability in the inclination angle of smaller coherent turbulent structures. Although this aspect has been extensively studied via numerical and laboratory experiments, few studies have explored this feature for a very-high-Reynolds-number atmospheric flow. In this work, the inclination angle of turbulent structures within the atmospheric surface layer at a very high Reynolds number (𝑅𝑒 𝜏 =7.9 ×10 5 ) is investigated by deploying a scanning Doppler light detection and ranging and a super large particle image velocimetry (SLPIV) apparatus. The inclination angle of wall-attached eddies is inferred either from the two-point correlation of streamwise velocity (𝛾 =41.1∘) or with a scale-dependent approach through the spectral linear stochastic estimator (SLSE). The SLSE (and, thus, the scale-dependent inclination angle) is conditionally evaluated based on the high- and low-momentum events induced by VLSMs, both in the streamwise (𝑢′𝑉𝐿𝑆𝑀) and in the vertical (𝑤′ 𝑉𝐿𝑆𝑀) velocity components. As a result, lower inclination angles (𝛾 =30° −50°) are found for 𝑢$^{'}_{VLSM}$ >0 (𝑤$^{'}_{VLSM}$ <0), while higher values (50° −85°) are ascribed to 𝑢$^{'}_{VLSM}$ <0 (𝑤$^{'}_{VLSM}$ >0). This result emphasises the primary role that VLSMs play in shaping the wall-attached eddy geometry, which, in turn, is crucial to determine the Reynolds stress balance within the wall-attached eddy range.

42 ENGINEERING↗

Global Ecosystem Dynamics Investigation (GEDI) Instrument Alignment and Test

NASA's Global Ecosystem Dynamics Investigation (GEDI) instrument was launched Dec. 5, 2018, and installed on the International Space Station 419 km from Earth. The GEDI is a Light Detection and Ranging (LIDAR) instrument; measuring the time of flight of transmitted laser beams to the Earth and back to determine altitude for geospatial mapping of forest canopy heights. The need for very dense cross track sampling for slope measurements of canopy height is accomplished by using three individual laser transmitter systems, where each beam is split into two beams by a birefringent crystal. Furthermore, one transmitter is equipped with a diffractive optical element splitting the two beams into four, for a total of 8 beams. The beams are reflected off of the features and imaged by an 800 mm diameter Receiver Telescope Assembly, composed of a Ritchey-Chretien telescope, a refractive aft optics assembly and focal plane array which collects and focuses the light from the 8 probe beams into the 8 science fibers, each with a field of view on the Earth subtending 300 mu rad. The dense cross-track sampling mandated a custom designed dual-fiber interface. The science fibers had to be aligned to the nominal, projected laser spots. The alignment was highly dependent on optimization and co-positioning of the fibers pair-wise due to mechanical constraints. This paper presents the end-to-end alignment and metrology of the full optical system from transmitter elements through receiver telescope, aft-optics, focal plane and receiver fibers performed at NASA Goddard Space Flight Center.[GRAPHICS]

Bente Eegholm↗