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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Using Ensemble Decisions and Active Selection to Improve Low-Cost Labeling for Multi-View Data

This paper seeks to improve low-cost labeling in terms of training set reliability (the fraction of correctly labeled training items) and test set performance for multi-view learning methods. Co-training is a popular multiview learning method that combines high-confidence example selection with low-cost (self) labeling. However, co-training with certain base learning algorithms significantly reduces training set reliability, causing an associated drop in prediction accuracy. We propose the use of ensemble labeling to improve reliability in such cases. We also discuss and show promising results on combining low-cost ensemble labeling with active (low-confidence) example selection. We unify these example selection and labeling strategies under collaborative learning, a family of techniques for multi-view learning that we are developing for distributed, sensor-network environments.

machine learning↗

Features of Point Clouds Synthesized from Multi-View ALOS/PRISM Data and Comparisons with LiDAR Data in Forested Areas

LiDAR waveform data from airborne LiDAR scanners (ALS) e.g. the Land Vegetation and Ice Sensor (LVIS) havebeen successfully used for estimation of forest height and biomass at local scales and have become the preferredremote sensing dataset. However, regional and global applications are limited by the cost of the airborne LiDARdata acquisition and there are no available spaceborne LiDAR systems. Some researchers have demonstrated thepotential for mapping forest height using aerial or spaceborne stereo imagery with very high spatial resolutions.For stereo imageswith global coverage but coarse resolution newanalysis methods need to be used. Unlike mostresearch based on digital surface models, this study concentrated on analyzing the features of point cloud datagenerated from stereo imagery. The synthesizing of point cloud data from multi-view stereo imagery increasedthe point density of the data. The point cloud data over forested areas were analyzed and compared to small footprintLiDAR data and large-footprint LiDAR waveform data. The results showed that the synthesized point clouddata from ALOSPRISM triplets produce vertical distributions similar to LiDAR data and detected the verticalstructure of sparse and non-closed forests at 30mresolution. For dense forest canopies, the canopy could be capturedbut the ground surface could not be seen, so surface elevations from other sourceswould be needed to calculatethe height of the canopy. A canopy height map with 30 m pixels was produced by subtracting nationalelevation dataset (NED) fromthe averaged elevation of synthesized point clouds,which exhibited spatial featuresof roads, forest edges and patches. The linear regression showed that the canopy height map had a good correlationwith RH50 of LVIS data with a slope of 1.04 and R2 of 0.74 indicating that the canopy height derived fromPRISM triplets can be used to estimate forest biomass at 30 m resolution.

LiDARD↗

A Compact, Multi-view Net Flux Radiometer for Future Uranus and Neptune Probes

A Net Flux Radiometer (NFR) is presented that can be included in an atmospheric structure instrument suite for future probe missions to the icy giants Uranus and Neptune. The baseline design has two spectral channels i.e., a solar channel (0.4-to-3.5 m) and a thermal channel (4-to-300 m). The NFR is capable of viewing five distinct viewing angles during the descent. Non-imaging Winston cones with band-pass filters are used for each spectral channel and to define a 5 angular acceptance. Uncooled thermopile detectors are used in each spectral channel and are read out using a custom radiation hard application specific integrated circuit (ASIC). The baseline design can easily be changed to increase the number of detector channels from two to seven.

Aslam, S.↗

Remote Sensing of Aerosol and their Radiative Forcing of Climate

Remote sensing of aerosol and aerosol radiative forcing of climate is going through a major transformation. The launch in next few years of new satellites designed specifically for remote sensing of aerosol is expected to further revolutionized aerosol measurements: until five years ago satellites were not designed for remote sensing of aerosol. Aerosol optical thickness was derived as a by product, only over the oceans using one AVHRR channel with errors of approx. 50%. However it already revealed a very important first global picture of the distribution and sources of aerosol. In the last 5 years we saw the introduction of polarization and multi-view observations (POLDER and ATSR) for satellite remote sensing of aerosol over land and ocean. Better products are derived from AVHRR using its two channels. The new TOMS aerosol index shows the location and transport of aerosol over land and ocean. Now we anticipate the launch of EOS-Terra with MODIS, MISR and CERES on board for multi-view, multi-spectral remote sensing of aerosol and its radiative forcing. This will allow application of new techniques, e.g. using a wide spectral range (0.55-2.2 microns) to derive precise optical thickness, particle size and mass loading. Aerosol is transparent in the 2.2 microns channel, therefore this channel can be used to detect surface features that in turn are used to derive the aerosol optical thickness in the visible part of the spectrum. New techniques are developed to derive the aerosol single scattering albedo, a measure of absorption of sunlight, and techniques to derive directly the aerosol forcing at the top of the atmosphere. In the last 5 years a global network of sun/sky radiometers was formed, designed to communicate in real time the spectral optical thickness from 50-80 locations every day, every 15 minutes. The sky angular and spectral information is also measured and used to retrieve the aerosol size distribution, refractive index, single scattering albedo and the spectral flux reaching the surface. Effort to introduce remote sensing from lidars will literally additional dimension to aerosol remote sensing. The vertical dimension is a critical link between the global satellite observations and modeling of aerosol transport. Lidars are also critical to study aerosol impact on cloud microphysics and reflectance. Both lidar ground networks and satellite systems are in development. This new capability is expected to put remote sensing in the forefront of aerosol and climate studies. Together with field experiments, chemical analysis and chemical transport models we anticipate, in the next decade, to be able to resolve some of the outstanding questions regarding the role of aerosol in climate, in atmospheric chemistry and its influence on human health and life on this planet.

Kaufman, Yoram J.↗

Advanced NDE research in electromagnetic, thermal, and coherent optics

A new inspection technology called magneto-optic/eddy current imaging was investigated. The magneto-optic imager makes readily visible irregularities and inconsistencies in airframe components. Other research observed in electromagnetics included (1) disbond detection via resonant modal analysis; (2) AC magnetic field frequency dependence of magnetoacoustic emission; and (3) multi-view magneto-optic imaging. Research observed in the thermal group included (1) thermographic detection and characterization of corrosion in aircraft aluminum; (2) a multipurpose infrared imaging system for thermoelastic stress detection; (3) thermal diffusivity imaging of stress induced damage in composites; and (4) detection and measurement of ice formation on the space shuttle main fuel tank. Research observed in the optics group included advancements in optical nondestructive evaluation (NDE).

Skinner, S. Ballou↗

Simulator Investigation of Pilot Aids for Helicopter Terminal Area Operations with One Engine Inoperative

Two recent piloted simulation experiments have investigated advanced display concepts applied to civil transport helicopter terminal area operations. Civil Category A helicopter operations apply to multi-engine helicopters wherein a safe recovery (land or fly out) is required in the event of a single engine failure. The investigation used the NASA Ames Research Center Vertical Motion Simulator, which has a full six degrees of freedom, to simulate the flight task as closely as possible. The goal of these experiments was to use advanced cockpit displays to improve flight safety and enhance the mission performance of Category A terminal area operations in confined areas. The first experiment investigated the use of military display formats to assist civil rotorcraft in performing a Category A takeoff in confined terminal areas. Specifically, it addressed how well a difficult hovering backup path could be followed using conventional instruments in comparison to panel mounted integrated displays. The hovering backup takeoff, which enables pilots to land back to the confined area pad in the event of an engine failure, was chosen since it is a difficult task to perform. Seven NASA and Army test pilots participated in the experiment. Evaluations, based on task performance and pilot workload, showed that an integrated display enabled the pilot to consistently achieve adequate or desired performance with reasonable pilot workload. Use of conventional instruments, however, frequently resulted in unacceptable performance (poor flight path tracking), higher pilot workload, and poor situational awareness. Although OEI landbacks were considered a visual task, the improved performance on the backup portion, in conjunction with increased situational awareness resulting from use of integrated displays, enabled the pilots to handle an engine failure and land back safely. In contrast, use of conventional instruments frequently led to excessive rates of sink at touchdown. A second simulation (in progress - July - August) is being conducted to investigate the use of advanced displays to perform vertical and short takeoffs and landings. One Engine Inoperative trajectories, which were optimized based on safety of flight restrictions, are utilized. Based on comments from the first experiment and further analytic development, appropriate fly out and approach guidance was added. Displays include conventional instruments with raw data, and the following integrated displays: multi-view and side-view hover displays based on the Apache Pilot Night Vision System, and variations of the pathway-in-the-sky displays with a flight-path-vector, a leader and flight director modifications. Panel mounted and head-up displays are being evaluated. Engine modifications have been incorporated to simulate 30 second and 2 minute contingency power ratings. Evaluations are based on task performance and pilot workload. NASA, Army, FAA, and industry test pilots participated. Details concerning the design, conduct, and the results of the experiment will be reported in the proposed paper.

Iseler, Laura↗

Photogrammetry Toolbox Reference Manual

Specialized photogrammetric and image processing MATLAB functions useful for wind tunnel and other ground-based testing of aerospace structures are described. These functions include single view and multi-view photogrammetric solutions, basic image processing to determine image coordinates, 2D and 3D coordinate transformations and least squares solutions, spatial and radiometric camera calibration, epipolar relations, and various supporting utility functions.

Liu, Tianshu↗

Neural Radiance Fields for Shadow Removal and Relighting of Satellite Imagery

Multi-view stereo photogrammetric techniques have been conventionally utilized to generate Global Digital Elevation Models (GDEM) of planetary and lunar surfaces. However, these methods, relying on conventional feature detectors, are often subject to inaccuracies caused by changes in lighting conditions, including diffuse reflection and harsh shading. This has limited the ability of these methods to accurately reconstruct shadowed regions in orbital imagery, such as highly shaded urban areas and the permanently shadowed regions (PSRs) located in the lunar surface, which are critical targets for NASA's Artemis program. Neural Radiance Fields (NeRFs) offer a novel solution to these limitations by breaking away from traditional photogrammetric assumptions of ridged, opaque surfaces. NeRFs are capable of reconstructing 3D objects with variably transmissive properties, such as fluids, PSRs, and reflective surfaces. In this work, we demonstrate the robustness of NeRFs in generating high-fidelity 3D models of terrain from highly shaded orbital imagery acquired from small satellites in low earth orbit (LEO). Our results showcase the ability of NeRF to overcome the limitations of traditional photogrammetric methods and provide a promising solution for reconstructing complex scenes in challenging lighting conditions.

Caleb Ashmore Adams↗

3D Cloud Tomography and Droplet Size Retrieval from Multi-Angle Polarimetric Imaging of Scattered Sunlight from Above

Tomography aims to recover a three-dimensional (3D) density map of a medium or an object. In medical imaging,it is extensively used for diagnostics via X-ray computed tomography (CT). We define and derive a tomographyof cloud droplet distributions via passive remote sensing. We use multi-view polarimetric images to fit a 3Dpolarized radiative transfer (RT) forward model. Our motivation is 3D volumetric probing of vertically-developedconvectively-driven clouds that are ill-served by current methods in operational passive remote sensing. Currenttechniques are indeed based on strictly 1D RT modeling and applied to a single cloudy pixel, where cloud geometrydefaults to that of a plane-parallel slab. Incident unpolarized sunlight, once scattered by cloud droplets, changesits polarization state according to droplet size. Therefore, polarimetric measurements in the rainbow and gloryangular regions can be used to infer the droplet size distribution. This work defines and derives a framework for afull 3D tomography of cloud droplets for both their mass concentration in space and their distribution across arange of sizes. This gridded 3D retrieval of key microphysical properties is made tractable by our novel approachthat involves a restructuring and partial linearization of an open-source polarized 3D RT code to accommodate aspecial two-step iterative optimization technique. Physically-realistic synthetic clouds are used to demonstrate themethodology with rigorous uncertainty quantification, while a real-world cloud imaged by AirMSPI is processedto illustrate the new remote sensing capability

Schechner, Yoav Y.↗