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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Estimating Surface Soil Moisture in Simulated AVIRIS Spectra

Soil albedo is influenced by many physical and chemical constituents, with moisture being the most influential on the spectra general shape and albedo (Stoner and Baumgardner, 1981). Without moisture, the intrinsic or matrix reflectance of dissimilar soils varies widely due to differences in surface roughness, particle and aggregate sizes, mineral types, including salts, and organic matter contents. The influence of moisture on soil reflectance can be isolated by comparing similar soils in a study of the effects that small differences in moisture content have on reflectance. However, without prior knowledge of the soil physical and chemical constituents within every pixel, it is nearly impossible to accurately attribute the reflectance variability in an image to moisture or to differences in the physical and chemical constituents in the soil. The effect of moisture on the spectra must be eliminated to use hyperspectral imagery for determining minerals and organic matter abundances of bare agricultural soils. Accurate soil mineral and organic matter abundance maps from air- and space-borne imagery can improve GIS models for precision farming prescription, and managing irrigation and salinity. Better models of soil moisture and reflectance will also improve the selection of soil endmembers for spectral mixture analysis.

Whiting, Michael L.↗
NASA NTRS2005

Mars Express OMEGA Observations over Terra Meridiani

The OMEGA hyperspectral imager (0.35 to 5.08 micrometers) covered the hematite-bearing plains and underlying etched terrains of Terra Meridiani during several orbits with spatial resolutions ranging from several hundred meters to approximately 2 km. We extracted and analyzed surface reflectance spectra from OMEGA data for the approximately 864,000 square kilometers surrounding the Opportunity site. In this paper we focus on analysis of OMEGA orbit 485 data for the plains and etched terrains located to the northeast of the Opportunity landing site.

Arvidson, R. E.↗
NASA NTRS2018

The Wide-Field Spatio-Spectral Interferometer: System Overview, Data Synthesis and Analysis

The Wide-field Imaging Interferometry Testbed (WIIT) is a double Fourier (DF) interferometer operating at optical wavelengths, and provides data that are highly representative of those from a space-based far-infrared interferometer like SPIRIT. We have used the testbed to observe both geometrically simple and astronomically representative test scenes. Here we present an overview of the astronomical importance of high angular resolution at the far infrared, followed by the description of the optical set-up of WIIT, including the source simulator CHIP (Calibrated Hyperspectral Image Projector). We describe our synthesis algorithms used in the reconstruction of the input test scenes via a simulation of the most recent measurements. The updated algorithms, which include instruments artifacts that allow the synthesis of DF experimental data, are presented and the most recent results analyzed.

Juanola-Parramon, Roser↗
NASA NTRS2005

Design and Construction of a Field Capable Snapshot Hyperspectral Imaging Spectrometer

The computed-tomography imaging spectrometer (CTIS) is a device which captures the spatial and spectral content of a rapidly evolving same in a single image frame. The most recent CTIS design is optically all reflective and uses as its dispersive device a stated the-art reflective computer generated hologram (CGH). This project focuses on the instrument's transition from laboratory to field. This design will enable the CTIS to withstand a harsh desert environment. The system is modeled in optical design software using a tolerance analysis. The tolerances guide the design of the athermal mount and component parts. The parts are assembled into a working mount shell where the performance of the mounts is tested for thermal integrity. An interferometric analysis of the reflective CGH is also performed.

Arik, Glenda H.↗
NASA NTRS2011

Metric Learning for Hyperspectral Image Segmentation

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

Compact Reconnaissance Imaging Spectrometer (CRISM↗
NASA NTRS2005

NASA Tech Briefs, August 2005

Topics include: Hidden Identification on Parts: Magnetic Machine-Readable Matrix Symbols; System for Processing Coded OFDM Under Doppler and Fading; Multipurpose Hyperspectral Imaging System; Magnetic-Flux-Compensated Voltage Divider; High-Performance Satellite/Terrestrial-Network Gateway; Internet-Based System for Voice Communication With the ISS; Stripline/Microstrip Transition in Multilayer Circuit Board; Dual-Band Feed for a Microwave Reflector Antenna; Quadratic Programming for Allocating Control Effort; Range Process Simulation Tool; Simulator of Space Communication Networks; Computing Q-D Relationships for Storage of Rocket Fuels; Contour Error Map Algorithm; Portfolio Analysis Tool; Glass Frit Filters for Collecting Metal Oxide Nanoparticles; Anhydrous Proton-Conducting Membranes for Fuel Cells; Portable Electron-Beam Free-Form Fabrication System; Miniature Laboratory for Detecting Sparse Biomolecules; Multicompartment Liquid-Cooling/Warming Protective Garments; Laser Metrology for an Optical-Path-Length Modulator; PCM Passive Cooling System Containing Active Subsystems; Automated Electrostatics Environmental Chamber; Estimating Aeroheating of a 3D Body Using a 2D Flow Solver; Artificial Immune System for Recognizing Patterns; Computing the Thermodynamic State of a Cryogenic Fluid; Safety and Mission Assurance Performance Metric; Magnetic Control of Concentration Gradient in Microgravity; Avionics for a Small Robotic Inspection Spacecraft; and Simulation of Dynamics of a Flexible Miniature Airplane.

Source record↗
NASA NTRS2019

Multi-Band Atmospheric Correction Algorithm for Ocean Color Retrievals

NASA's current Atmospheric Correction (AC) algorithm for ocean color utilizes two bands and their ratio in the Near Infrared (NIR) to estimate aerosol reflectance and aerosol type. The algorithm then extrapolates the spectral dependence of aerosol reflectance to the visible wavelengths based on modeled spectral dependence of the identified aerosol type. Future advanced ocean color sensors, such as the Ocean Color Instrument (OCI) that will be carried on the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) satellite, will be capable of measuring the hyperspectral radiance from 340 to 890 nm at 5-nm spectral resolution and at 7 discrete Short-wave Infrared (SWIR) channels: 940, 1038,1250, 1378, 1615, 2130, and 2260 nm. To optimally employ this unprecedented instrument capability, we propose an improved AC algorithm that utilizes all atmospheric-window channels in the NIR to SWIR spectral range to reduce the uncertainty in the AC process. A theoretical uncertainty analysis of this, namely Multi-Band AC (MBAC), indicates that the algorithm can reduce the uncertainty in remote sensing reflectance (Rrs) retrievals of the ocean caused by sensor random noise. Furthermore, in optically complex waters, where the NIR signal is affected by contributions from highly-reflective turbid waters, the MBAC algorithm can be adaptively weighted to the strongly-absorbing SWIR channels to enable improved ocean color retrievals in coastal waters. We provide here a description of the algorithm and demonstrate the improved performance in ocean color retrievals, relative to the current NASA standard AC algorithm, through comparison with field measurements and assessment of propagated uncertainties in applying the MBAC algorithm to MODIS and simulated PACE OCI data.

PACE↗
NASA NTRSDate not supplied

Impacts of Assimilating Infrared Sounders from Geostationary Orbit

A set of observing system simulation experiments (OSSEs) was used to assess the impact of assimilating hyperspectral infrared (IR) radiances from geostationary platforms. This was done in preparation for the proposed National Oceanic and Atmospheric Administration (NOAA) Geostationary eXtended Observations (GeoXO) Sounder (GXS), expected to launch in the 2030s, using the National Aeronautics and Space Administration (NASA) Global Modeling and Assimilation Office (GMAO) OSSE framework. From a numerical weather prediction (NWP) perspective, a global “ring” of geostationary IR sounders was found to improve both the analysis and forecasts and provide beneficial impacts as measured by the forecast sensitivity observation impact (FSOI) metric.

Geostationary orbit↗
NASA NTRSDate not supplied

Validation of CrIS Ozone and Carbon Oxide Products from CrIS Single-Field-of-View Retrievals

Single Field-of-view Sounder Atmospheric Products (SiFSAP) from Cross-track Infrared Sounder (CrIS) on S-NPP have been developed at NASA Langley Research center, and recently a significant improvement in its trace gases products has been made. These products are derived based on the Principal Component (PC)-based Radiative Transfer Model (PCRTM) and an optimal estimation retrieval method (PCRTM-RA). Use of the PCRTM in this method allows for fast and accurate calculations for thousands of spectral channels under clear and cloudy sky conditions. The use of principal component to compress information from all spectral channels into the PC domain enables to reduce the observational noise and use the information from all hyperspectral infrared channels. The retrieval is made on PC-domain, and temperature, water vapor, trace gases, cloud and surface parameters are retrieved simultaneously. This presentation will present some validation to the SiFSAP ozone (O3) and carbon monoxide (CO) products. Since the SiFSAP has a spatial resolution of about 14 km at nadir, which is better than most global weather and climate models and enables to make process-oriented analysis of the transport of these gases, this study will focus on validation of CO and O3 products under some extreme weather and/or climate events, such as CO emission and transport from large biomass burning, and O3 variation impacted by fire emission, stratospheric intrusion, and tropical cyclones. Data used in our validation include CO and O3 from NASA aircraft campaigns, plus other satellite products such as CO and O3 from AIRS, IASI and TROPOMI, MOPPIT CO and OMPS O3. Some comparison of SiFSAP O3 with the O3 from the fifth-generation ECMWF reanalysis (ERA5) data the NASA Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) will also present. Such a validation not only helps to quantify the performance of the retrievals in these extreme conditions, but also displays the capability of satellite observation to capture the fine-scale spatial pattern of CO and O3 variation.

Xiaozhen Xiong↗
NASA NTRS2020

Mapping tall shrub biomass in Alaska at landscape scale using structure-from-motion photogrammetry and lidar

Warming in arctic and boreal regions is increasing shrub cover and biomass. In southcentral Alaska, willow (Salix spp.) and alder (Alnus spp.) shrubs grow taller than many tree species and account for a substantial proportion of aboveground biomass, yet they are not individually measured as part of the operational Forest Inventory and Analysis (FIA) Program. The goal of this research was to test methods for landscape-scale mapping of tall shrub biomass in upper montane and subalpine environments using FIA-type plot measurements (n = 51) and predictor variables from imagery-based structure-from-motion (SfM) and airborne lidar. Specifically, we compared biomass models constructed from imagery acquired by unmanned aerial vehicle (UAV; ~1.7 cm pixels), imagery from the NASA Goddard's Lidar, Hyperspectral, and Thermal Airborne Imager (G-LiHT; ~3.1 cm pixels), and concomitant G-LiHT small-footprint lidar. Tall shrub biomass was most accurately predicted at 5 m resolution (R^2 = 0.81, RMSE = 1.09 kg/sq. m) using G-LiHT SfM color and structure variables. Lidar-only models had lower precision (R^2 = 0.74, RMSE = 1.26 kg/sq. m), possibly due to reduced model information content from variable multicollinearity or lower data density. Separate models for upper montane zones with trees and shrubs and subalpine zones with only shrubs were always chosen over single models based on minimization of Akaike's Information Criterion, indicating the need for variable sets robust to overhanging tree canopy. Decreasing point density from UAV (5000–8000 pts./sq. m) to the G-LiHT SfM point cloud (500–2000 pts./sq. m) had little impact on model fit, suggesting that high-resolution airborne imagery can extend SfM approaches well beyond line-of-sight restrictions for UAV platforms. Overall, our results confirmed that SfM from high-resolution imagery is a viable approach to estimate shrub biomass in the boreal region, especially when an existing lidar terrain model and local field calibration data are available to quantify uncertainty in the SfM point cloud and landscape-scale estimates of shrub biomass.

Michael Alonzo↗
NASA NTRS2013

Thermal Analysis of Unusual Local-scale Features on the Surface of Vesta

At 525 km in mean diameter, Vesta is the second-most massive object in the main asteroid belt of our Solar System. At all scales, pyroxene absorptions are the most prominent spectral features on Vesta and overall, Vesta mineralogy indicates a complex magmatic evolution that led to a differentiated crust and mantle [1]. The thermal behavior of areas of unusual albedo seen on the surface at the local scale can be related to physical properties that can provide information about the origin of those materials. Dawn's Visible and Infrared Mapping Spectrometer (VIR) [2] hyperspectral images are routinely used, by means of temperature-retrieval algorithms, to compute surface temperatures along with spectral emissivities. Here we present temperature maps of several local-scale features of Vesta that were observed by Dawn under different illumination conditions and different local solar times.

Tosi, F.↗
NASA NTRS1996

Algal Accessory Pigment Detection Using AVIRIS Image-Derived Spectral Radiance Data

Visual and derivative analyses of AVIRIS spectral data can be used to detect algal accessory pigments in aquatic communities. This capability extends the use of remote sensing for the study of aquatic ecosystems by allowing detection of taxonomically significant pigment signatures which yield information about the type of algae present. Such information allows remote sensing-based assessment of aquatic ecosystem health, as in the detection of nuisance blooms of cyanobacteria or toxic blooms of dinoflagellates. Remote sensing of aquatic systems has traditionally focused on quantification of chlorophyll a, a photoreactive (and light-harvesting) pigment which is common to all algae as well as cyanobacteria (bluegreen algae). Due to the ubiquitousness of this pigment within algae, chl a is routinely measured to estimate algal biomass both during ground-truthing and using various airborne or satellite based sensors, including AVIRIS. Within the remote sensing and aquatic sciences communities, ongoing research has been performed to detect algal accessory pigments for assessment of algal population composition. This research is based on the fact that many algal accessory pigments are taxonomically significant, and all are spectrally unique. Aquatic scientists have been refining pigment analysis techniques, primarily high performance liquid chromatography, or HPLC, to detect specific pigments as a time-saving alternative to individual algal cell identifications and counts. Remote sensing scientists are investigating the use of pigment signatures to construct pigment libraries analogous to mineral spectral libraries used in geological remote sensing applications. The accessory pigment approach has been used successfully in remote sensing using data from the Thematic Mapper, low-altitude, multiple channel scanners, field spectroradiometers and the AVIRIS hyperspectral scanner. Due to spectral and spatial resolution capabilities, AVIRIS is the sensor of choice for such studies. We present here our results on detection of algal accessory pigments using AVIRIS data.

Richardson, Laurie L.↗
NASA NTRS2009

Absolute Calibration Accuracy for Hyperspectral Imagers in the Solar Reflective

The characterization and calibration of hyperspectral imagers is a challenging one that is expected to become even more challenging as needs increase for highly-accurate radiometric data from such systems. The preflight calibration of the Advanced Responsive Tactically Effective Military Imaging Spectrometer (ARTEMIS) is used as an example of the difficulties to calibrate hyperspectrally. Results from a preflight solar radiation-based calibration are presented with a discussion of the uncertainties in such a method including the NISI-traceable and SItraceable aspects. Expansion on the concept of solar-based calibration is given with descriptions of methods that view the solar disk directly, illuminate a solar diffuser that is part of the sensor's inflight calibration, and illuminate an external diffuser that is imaged by the sensor. The results of error analysis show that it is feasible to achieve preflight calibration using the sun as a source at the same level of uncertainty as those of lamp-based approaches. The error analysis is evaluated and verified through the solar-radiation-based calibration of several of laboratory grade radiometers. Application of these approaches to NASA's upcoming CLARREO mission are discussed including proposed methods for significantly reducing the uncertainties to allow CLARREO data to be used for climate data records.

Thome, Kurtis↗
NASA NTRS2012

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

Climate change in tundra regions may alter vegetation species composition and ecosystem carbon balance. Remote sensing provides critical tools for monitoring these changes as optical signals provide a way to scale from plot measurements to regional patterns. Gas exchange measurements of pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow AK, show three significantly different values of light use efficiency (LUE) with values of 0.013+/-0.001, 0.0018+/-0.0002, and 0.0012 0.0001 mol C/mol absorbed quanta for vascular plants, mosses and lichens, respectively. Further, discriminant analysis of patch reflectance identifies five spectral bands that can separate each vegetation functional type as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. Patch-level statistical discriminant functions applied to in situ hyperspectral reflectance successfully unmixed cover fractions of the vegetation functional types. These functions, developed from the tram data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine regional variability in distribution of the vegetation functional types and from those distributions, the variability of LUE. Across the landscape, there was a fivefold variation in tundra LUE that was correlated to a spectral vegetation index developed to detect vegetation chlorophyll content.

Huemmrich, Karl F.↗
NASA NTRS1993

Spectral variations in a collection of AVIRIS imagery

The advent of AVIRIS presents to the scientific community the first opportunity to examine high quality hyperspectral data over areas of interest, while recent developments promise even better data in the future. With these data we may address questions such as: (1) Is such high spectral resolution (0.01 micron) necessary?; and (2) How can we take advantage of the AVIRIS experience in specifying an improved future Landsat satellite? In this paper we describe the use of relatively broadband measurements (20-50 nm) to represent spectral variability. The problem of generality is addressed through consideration of 28 AVIRIS scenes, although analysis of additional areas is clearly desirable. Section 2 defines the expansion of spectra in terms of basis functions, section 3 describes the application to AVIRIS data, and the conclusion, section 4, relates these preliminary results to possible future remote sensing instrumentation such as the planned Landsat 8.

Price, John C.↗
NASA NTRSDate not supplied

Progressive TDI Measurements with the PACE OCI ETU

The Plankton Aerosol Cloud ocean Ecosystem (PACE) Ocean Color Instrument (OCI) has completed the ground test program for its engineering unit (ETU) and testing of the flight unit will begin in the near future. OCIis a grating spectrometer with hyperspectral coverage from about 340 nm to 885 nm with 9 additional filtered channels in the SWIR. Two CCDs are used as detectors for the hyperspectral channels. One important operating mode of the CCDs on OCI is progressive time delay integration (or PTDI). In this mode, the charge in the CCD can be held for multiples of the nominal integration times. A series of these measurements can be made with progressively increasing multiples of the nominal integration time as the instrument scans across a uniform source. Ground testing with this operating mode on OCI ETU has shown promising results. This work will present measurements taken with the PTDI mode and the analysis of OCI ETU linearity and dynamic range

PACE↗
NASA NTRS2011

NASA Tech Briefs, March 2011

Topics covered include: Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation; Airborne Radar Interferometric Repeat-Pass Processing; Plug-and-Play Environmental Monitoring Spacecraft Subsystem; Power-Combined GaN Amplifier with 2.28-W Output Power at 87 GHz; Wallops Ship Surveillance System; Source Lines Counter (SLiC) Version 4.0; Guidance, Navigation, and Control Program; Single-Frame Terrain Mapping Software for Robotic Vehicles; Auto Draw from Excel Input Files; Observation Scheduling System; CFDP for Interplanetary Overlay Network; X-Windows Widget for Image Display; Binary-Signal Recovery; Volumetric 3D Display System with Static Screen; MMIC Replacement for Gunn Diode Oscillators; Feature Acquisition with Imbalanced Training Data; Mount Protects Thin-Walled Glass or Ceramic Tubes from Large Thermal and Vibration Loads; Carbon Nanotube-Based Structural Health Monitoring Sensors; Wireless Inductive Power Device Suppresses Blade Vibrations; Safe, Advanced, Adaptable Isolation System Eliminates the Need for Critical Lifts; Anti-Rotation Device Releasable by Insertion of a Tool; A Magnetically Coupled Cryogenic Pump; Single Piezo-Actuator Rotary-Hammering Drill; Fire-Retardant Polymeric Additives; Catalytic Generation of Lift Gases for Balloons; Ionic Liquids to Replace Hydrazine; Variable Emittance Electrochromics Using Ionic Electrolytes and Low Solar Absorptance Coatings; Spacecraft Radiator Freeze Protection Using a Regenerative Heat Exchanger; Multi-Mission Power Analysis Tool; Correction for Self-Heating When Using Thermometers as Heaters in Precision Control Applications; Gravitational Wave Detection with Single-Laser Atom Interferometers; Titanium Alloy Strong Back for IXO Mirror Segments; Improved Ambient Pressure Pyroelectric Ion Source; Multi-Modal Image Registration and Matching for Localization of a Balloon on Titan; Entanglement in Quantum-Classical Hybrid; Algorithm for Autonomous Landing; Quantum-Classical Hybrid for Information Processing; Small-Scale Dissipation in Binary-Species Transitional Mixing Layers; Superpixel-Augmented Endmember Detection for Hyperspectral Images; Coding for Parallel Links to Maximize the Expected Value of Decodable Messages; and Microwave Tissue Soldering for Immediate Wound Closure.

Source record↗
NASA NTRS2013

Texturecam: A Smart Camera for Microscale, Mesoscale, and Deep Space Applications

The TextureCam project is developing a 'smart camera' that can classify geologic surfaces in planetary images. This would allow autonomous spacecraft to collect data opportunisitcally during intervals between communications with Earth, such as during long traverses. Its surface classifications can identify new targets that were not anticipated in advance. The spacecraft might use this information to target these features with high-resolution instruments such as spectrometers nd narrow-field cameras. Classifications could also inform data 'triage' decisions, identifying high value images for prioritized downlink. Finally, the surface classification can serve as compressed maps of image content. Each of these strategies can improve the science data returned at each command cycle and speed reconnaissance during site survey and astrobiology investigation. Our first year of development has completed the image analysis algorithms and validated them in software tests. Here we survey these initial results and explore several application areas relevant to Mars and beyond.

Hyperspectral imagery↗