Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “spectral reflectance”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Retrievals of surface reflectances from AVIRIS data

A method for retrieving surface reflectances from spectral data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is being developed. In this method, the integrated water vapor amount on a pixel by pixel basis is derived from the 0.94- and 1.14-micron water vapor features. The water vapor, carbon dioxide (CO2), oxygen (O2) and methane (CH4) transmission spectrum in the 0.4-2.5 micron region is calculated. The derived water vapor value and the solar and observational geometry are used in the calculation. The AVIRIS spectrum is ratioed against the transmission spectrum to obtain the surface reflectance spectrum. Major mineral absorption features near 2.2 microns in retrieved reflectance spectra can be identified. Different vegetation absorption characteristics are observed. At present, the method is most useful for deriving surface reflectances from AVIRIS data measured on clear days with high visibilities.

Gao, Bo-Cai↗
NASA NTRS1993

Derivation of scaled surface reflectances from AVIRIS data

A method for retrieving 'scaled surface reflectances' assuming horizontal surfaces having Lambertian reflectances from spectral data collected by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is presented here. In this method, the integrated water vapor amount on a pixel by pixel basis is derived from the 0.94 micron and 1.14 micron water vapor absorption features. The transmission spectra of H2O, CO2, O3, N2O, CO, CH4, and O2 in the 0.4-2.5 micron region are simulated. The scattering effect due to atmospheric molecules and aerosols is modeled with the 5S computer code. The AVIRIS radiances are divided by solar irradiances above the atmosphere to obtain the apparent reflectances. The scaled surface reflectances are derived from the apparent reflectances using the simulated atmospheric gaseous transmittances and the simulated molecular and aerosol scattering data. The scaled surface reflectances differ from the real surface reflectances by a multiplicative factor. In order to convert the scaled surface reflectances into real surface reflectances, the slopes and aspects of the surfaces must be known.

Gao, Bo-Cai↗
NASA NTRS2019

First Provisional Land Surface Reflectance Product from Geostationary Satellite Himawari-8 AHI

A provisional surface reflectance (SR) product from the Advanced Himawari Imager (AHI) on-board the new generation geostationary satellite (Himawari-8) covering the period between July 2015 and December 2018 is made available to the scientific community. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is used in conjunction with time series Himawari-8 AHI observations to generate 1-km gridded and tiled land SR every 10 minutes during day time. This Himawari-8 AHI SR product includes retrieved atmospheric properties (e.g., aerosol optical depth at 0.47μm and 0.51μm), spectral surface reflectance (AHI bands 1–6), parameters of the RTLS BRDF model, and quality assurance flags. Product evaluation shows that Himawari-8 AHI data on average yielded 35% more cloud-free, valid pixels in a single day when compared to available data from the low earth orbit (LEO) satellites Terra/Aqua with MODIS sensor. Comparisons of Himawari-8 AHI SR against corresponding MODIS SR products (MCD19A1) over a variety of land cover types with the similar viewing geometry show high consistency between them, with correlation coefficients (r) being 0.94 and 0.99 for red and NIR bands, respectively. The high-frequency geostationary data are expected to facilitate studies of ecosystems on daily to diurnal time scales, complementing observations from networks such as the FLUXNET.

Himawari-8 AHI↗
NASA NTRS1991

Inferring vegetation characteristics using a knowledge-based system

A knowledge-based system for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input is developed. A portion of this system has been developed to discriminate between user-defined vegetation classes using spectral and directional reflectance relationships. This discrimination program was used to classify targets into user-defined ground cover and plant height classes. The program learns class descriptors from samples (both positive and negative) of spectral, directional reflectance data of natural surfaces (bare soils, natural vegetation, and agricultural vegetation). The system is designed to handle any combination of directional view angles. The explicit relationships used in the class descriptions include greater-than relationships between combinations of two view angles and maximum and minimum value relationships. The class descriptions are used to classify an unknown target using the same directional views. The program was tested by learning class descriptions of various categories of percent ground cover and vegetation height.

Kimes, D. S.↗
NASA NTRS1997

Determination of Aerosol Optical Depth and Land Surface Directional Reflectances Using Multiangle Imagery

Spectral aerosol optical depths, surface hemispherical-directional reflectance factors, and bihemispherical reflectances (albedos) are retrieved for an area of Glacier National Park using spectral, multiangle imagery obtained with the airborne advanced solid state array spectroradiometer (ASAS). The retrieval algorithms are described and are identical in principle to those being devised for use by the multiangle imaging spectroradiometer (MISR) which will fly on the EOS-AMI spacecraft in 1998. As part of its science mission, MISR will produce global coverage of both aerosol amounts an an surface reflection properties. The results in this paper represent the initial effort in applying the MISR algorithms to real data. These algorithms will undergo additional testing and validation as more multiangle data become available.

Martonchik, John V.↗
DOE OSTI2020

A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra

Changes in vegetation distribution, structure, and function can modify the canopy properties of terrestrial ecosystems, with potential consequences for regional and global climate feedbacks. In the Arctic, climate is warming twice as fast as compared to the global average (known as ‘Arctic amplification’), likely having stronger impacts on arctic tundra vegetation. In order to quantify these changes and assess their impacts on ecosystem structure and function, methods are needed to accurately characterize the canopy properties of tundra vegetation types. However, commonly used ground-based measurements are limited in spatial and temporal coverage, and differentiating low-lying tundra plant species is challenging with coarse-resolution satellite remote sensing. The collection and processing of multi-sensor data from unoccupied aerial systems (UASs) has the potential to fill the gap between ground-based and satellite observations. To address the critical need for such data in the Arctic, we developed a cost-effective multi-sensor UAS (the ‘Osprey’) using off-the-shelf instrumentation. The Osprey simultaneously produces high-resolution optical, thermal, and structural images, as well as collecting point-based hyperspectral measurements, over vegetation canopies. In this paper, we describe the setup and deployment of the Osprey system in the Arctic to a tundra study site located in the Seward Peninsula, Alaska. We present a case study demonstrating the processing and application of Osprey data products for characterizing the key biophysical properties of tundra vegetation canopies. In this study, plant functional types (PFTs) representative of arctic tundra ecosystems were mapped with an overall accuracy of 87.4%. The Osprey image products identified significant differences in canopy-scale greenness, canopy height, and surface temperature among PFTs, with deciduous low to tall shrubs having the lowest canopy temperatures while non-vascular lichens had the warmest. The analysis of our hyperspectral data showed that variation in the fractional cover of deciduous low to tall shrubs was effectively characterized by Osprey reflectance measurements across the range of visible to near-infrared wavelengths. Therefore, the development and deployment of the Osprey UAS, as a state-of-the-art methodology, has the potential to be widely used for characterizing tundra vegetation composition and canopy properties to improve our understanding of ecosystem dynamics in the Arctic, and to address scale issues between ground-based and airborne/satellite observations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Global Space-Based Inter-Calibration System Reflective Solar Calibration Reference: From Aqua MODIS to S-NPP VIIRS

The MODIS has successfully operated on-board the NASA's EOS Terra and Aqua spacecraft for more than 16 and 14 years, respectively. MODIS instrument was designed with stringent calibration requirements and comprehensive on-board calibration capability. In the reflective solar spectral region, Aqua MODIS has performed better than Terra MODIS and, therefore, has been chosen by the Global Space-based Inter-Calibration System (GSICS) operational community as the calibration reference sensor in cross-sensor calibration and calibration inter-comparisons. For the same reason, it has also been used by a number of earth observing sensors as their calibration reference. Considering that Aqua MODIS has already operated for nearly 14 years, it is essential to transfer its calibration to a follow-on reference sensor with a similar calibration capability and stable performance. The VIIRS is a follow-on instrument to MODIS and has many similar design features as MODIS, including their on-board calibrators (OBC). As a result, VIIRS is an ideal candidate to replace MODIS to serve as the future GSICS reference sensor. Since launch, the S-NPP VIIRS has already operated for more than 4 years and its overall performance has been extensively characterized and demonstrated to meet its overall design requirements. This paper provides an overview of Aqua MODIS and S-NPP VIIRS reflective solar bands (RSB) calibration methodologies and strategies, traceability, and their on-orbit performance. It describes and illustrates different methods and approaches that can be used to facilitate the calibration reference transfer, including the use of desert and Antarctic sites, deep convective clouds (DCC), and the lunar observations.

Xiong, Xiaoxiong↗
DOE OSTI2023

Quantifying optical loss of high-voltage degradation modes in photovoltaic modules using spectral analysis

The direct current bias for photovoltaic (PV) modules interconnected in series-strings may include both high voltage negative (“HV-”) and positive (“HV+”) polarity with respect to the electrical ground. Multiple degradation modes, resulting in quantifiable optical loss, were found to occur during HV-/HV+ sequential stress, including corrosion of the external glass surface, encapsulant delamination (at its interfaces with the glass and the PV cell), internal haze formation (resulting from a chemical interaction between the glass and the encapsulant), corrosion and migration of the gridlines, and corrosion of the silicon nitride (Si x N y ) antireflective coating on the cell. The effects of these separate modes were examined using monolithic (e.g., glass or PV cell) and laminated-coupon (glass/encapsulant/glass or glass/encapsulant/cell/encapsulant/backsheet) specimens. Characterizations during and after unbiased accelerated testing at 85°C/85% relative humidity included spectrophotometry, optical microscopy, electron microscopy, and ellipsometry. For some module components (i.e., the glass and the Si x N y coating), the optical performance was determined through iterative analysis of empirical measurements. Concentrating on just their spectral effect, a novel model was then developed to estimate the transfer of light to the PV cell and the return of light from the PV module with simultaneous degradation mechanisms, which was compared with a mini-module previously subjected to HV-/HV+ stress. Here the model suggests that one third of the current loss observed for the mini-module can be attributed to the optical degradation of the packaging materials. The dominant degradation modes include encapsulant delamination and corrosion of the Si x N y coating. Recommendations are given so that the optical model may be improved relative to accelerated testing and validated relative to field aging.

14 SOLAR ENERGY↗
DOE OSTI2023

Quantifying Optical Loss of High-Voltage Degradation Modes in PV Modules Using Spectral Analysis [Slides]

The direct current bias for photovoltaic (PV) modules interconnected in series-strings may include both high voltage negative ("HV-") and positive ("HV+") polarity with respect to the electrical ground. Multiple degradation modes, resulting in quantifiable optical loss, were found to occur during HV-/HV+ sequential stress, including: corrosion of the external glass surface, encapsulant delamination (at its interfaces with the glass and the PV cell), internal haze formation (resulting from a chemical interaction between the glass and the encapsulant), corrosion and migration of the gridlines, and corrosion of the silicon nitride (SixNy) antireflective coating on the cell. The effects of these separate modes were examined using monolithic (e.g., glass or PV cell) and laminated-coupon (glass/encapsulant/glass or glass/encapsulant/cell/encapsulant/backsheet) specimens. Characterizations during and after unbiased accelerated testing at 85 degrees C/85% relative humidity included: spectrophotometry, optical microscopy, electron microscopy, and ellipsometry. For some module components (i.e., the glass and the SixNy coating), the optical performance was determined through iterative analysis of empirical measurements. Concentrating on just their spectral effect, a novel model was then developed to estimate the transfer of light to the PV cell and the return of light from the PV module with simultaneous degradation mechanisms, which was compared to a mini-module previously subjected to HV-/HV+ stress. The model suggests one-third of the current loss observed for the mini-module can be attributed to the optical degradation of the packaging materials. The dominant degradation modes include encapsulant delamination and corrosion of the SixNy coating. Recommendations are given so that the optical model may be improved relative to accelerated testing and validated relative to field aging.

14 SOLAR ENERGY↗
DOE OSTI2020

Plot-level rapid screening for photosynthetic parameters using proximal hyperspectral imaging

Abstract Photosynthesis is currently measured using time-laborious and/or destructive methods which slows research and breeding efforts to identify crop germplasm with higher photosynthetic capacities. We present a plot-level screening tool for quantification of photosynthetic parameters and pigment contents that utilizes hyperspectral reflectance from sunlit leaf pixels collected from a plot (~2 m×2 m) in <1 min. Using field-grown Nicotiana tabacum with genetically altered photosynthetic pathways over two growing seasons (2017 and 2018), we built predictive models for eight photosynthetic parameters and pigment traits. Using partial least squares regression (PLSR) analysis of plot-level sunlit vegetative reflectance pixels from a single visible near infra-red (VNIR) (400–900 nm) hyperspectral camera, we predict maximum carboxylation rate of Rubisco (Vc,max, R2=0.79) maximum electron transport rate in given conditions (J1800, R2=0.59), maximal light-saturated photosynthesis (Pmax, R2=0.54), chlorophyll content (R2=0.87), the Chl a/b ratio (R2=0.63), carbon content (R2=0.47), and nitrogen content (R2=0.49). Model predictions did not improve when using two cameras spanning 400–1800 nm, suggesting a robust, widely applicable and more ‘cost-effective’ pipeline requiring only a single VNIR camera. The analysis pipeline and methods can be used in any cropping system with modified species-specific PLSR analysis to offer a high-throughput field phenotyping screening for germplasm with improved photosynthetic performance in field trials.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1978

Asteroid surface materials - Mineralogical characterizations from reflectance spectra

The use of general and specific diagnostic spectral features and parameters to interpret most of the published high-quality reflectance spectra of asteroids is discussed. Such diagnostics are shown to provide the most complete and sophisticated mineralogically and petrologically based interpretation of the asteroid surface materials. Previous investigations of asteroid surface materials are exhaustively reviewed, emphasizing the general approaches employed, sources of information, previous characterizations of asteroid surface materials, and asteroid spectral groups. The interpretive methodology is then applied to spectral reflectance data for many individual members of the various spectral groups. A range of mineral assemblages similar to certain meteorite classes is identified, and evidence is presented for a selective high-temperature event that melted certain asteroid parent bodies and permitted their differentiation as some function of distance from the sun or the protosun and of the size of the protoasteroid. Possible candidates are proposed for the source bodies of different meteorite groups.

Gaffey, M. J.↗
DOE OSTI2025

The Global Spectra-Trait Initiative: A database of paired leaf spectroscopy and functional traits associated with leaf photosynthetic capacity (v1.0.0)

The Global Spectra-Trait Initiative (GSTI) aims to generate generalizable spectra trait models using reflectance data to predict leaf traits associated with the photosynthesis capacity of leaves. It comprises a synthesized dataset of leaf trait data, input datasets and code. Leaf traits include the maximum carboxylation rate of rubisco (Vcmax), the maximum electron transport rate (Jmax), the dark respiration, as well as the prediction of leaf nitrogen, leaf mass per area (LMA), and leaf water content (LWC). The dataset comprises >7500 paired observations from around 400 species from a broad range of biomes. This dataset comprises a zip file of the GSTI GitHub repository (https://github.com/plantphys/gsti), the synthesized database (.csv) and database metadata files. This dataset was updated on 2025-12-12 with minor edits to mirror the accepted manuscript version and GitHub release (Version 1.0.0 (ESSD accepted version)). Edits included minor changes to the project documentation on GitHub and removal of 12 duplicate entries from the database.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Complete field-induced spectral response of the spin-1/2 triangular-lattice antiferromagnet CsYbSe 2

Fifty years after Anderson’s resonating valence-bond proposal, the spin-1/2 triangular-lattice Heisenberg antiferromagnet (TLHAF) remains the ultimate platform to explore highly entangled quantum spin states in proximity to magnetic order. Yb-based delafossites are ideal candidate TLHAF materials, which allow experimental access to the full range of applied in-plane magnetic fields. We perform a systematic neutron scattering study of CsYbSe 2 , first proving the Heisenberg character of the interactions and quantifying the second-neighbor coupling. We then measure the complex evolution of the excitation spectrum, finding extensive continuum features near the 120°-ordered state, throughout the 1/3-magnetization plateau and beyond this up to saturation. We perform cylinder matrix-product-state (MPS) calculations to obtain an unbiased numerical benchmark for the TLHAF and spectacular agreement with the experimental spectra. The measured and calculated longitudinal spectral functions reflect the role of multi-magnon bound and scattering states. These results provide valuable insight into unconventional field-induced spin excitations in frustrated quantum materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

AI-Assisted Conceptual Development of a Pre-Geometric Cosmological Model - An Exercise in AI-Assisted Conceptual Framework Generation, Paper III: Cosmological Structure and Predictions

This paper develops the cosmological consequences of the replication-driven cosmogenesis framework introduced in Paper I and the emergent geometric structure established in Paper II. After the replication epoch freezes out, the coherent sector occupies a finite spectral band and contains a population of excited states. The relaxation of these excited coherent configurations does not produce coherent radiation; instead, all released energy flows into the incoherent substrate, where the randomizer acts as a rapid phase-scrambling mechanism. This process generates an effectively thermal radiation bath, providing a natural reheating mechanism that requires neither inflaton oscillations nor scalar-field potentials, and can be contrasted with standard scenarios of nonperturbative reheating dynamics. Subsequent symmetry-breaking transitions in the coherent vacuum inject additional radiation, yielding a multi-stage thermal history with well-defined energy transfers. We derive the effective equations of state for each component—the cosmological vacuum, the coherent vacuum, and the radiation bath—and show how their interplay produces an FRW-like expansion. The discrete sequence of coherent-state relaxations imprints a distinctive multi-peaked stochastic gravitational-wave background, whose spectral structure reflects the underlying hierarchy of coherent frequencies. Potential observational signatures in the LISA and mid-band frequency ranges are highlighted, providing concrete avenues to test this replication-based cosmological framework in the context of standard cosmological gravitational-wave backgrounds and LISA-oriented forecasts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Maps of Arctic vegetation leaf nitrogen concentration, albedo and plant functional type (PFT) derived from imaging spectroscopy data, Council watershed, Seward Peninsula, Alaska, 2019

Remote sensing maps of surface albedo, leaf nitrogen content, and plant functional types (PFTs) derived from NASA's Airborne Visible / Infrared Imaging Spectrometer Next Generation (AVIRIS-NG) by the Terrestrial Ecosystem Science & Technology (TEST) group at Brookhaven National Laboratory. The AVIRIS-NG imaging spectroscopy data (380 ~ 2510 nm) was collected as a part of the collaboration between NASA's Arctic-Boreal Vulnerability Experiment (ABoVE; Miller et al., 2019) and DOE's Next Generation Ecosystem Experiment in the Arctic (NGEE-Arctic). This package includes maps for the NGEE-Arctic Council watershed created using AVIRIS-NG imagery collected on July 9th, 2019. The map data and metadata are provided as image (ENVI, *.png) and text (*.txt, *hdr) formats. Additional supporting map quicklooks are provided as *.png files and GIS *.kml files. Detailed description of the methods for each map are provided in this document. These datasets are provided in support of Figure 6 in Nelson et al., (2022), "Remote Sensing of Tundra Ecosystems using High Spectral Resolution Reflectance: Opportunities and Challenges". The full citation can be found within the references section. Note that the AVIRIS-NG leaf nitrogen product included in this dataset is a preliminary product and is provided for demonstration purposes only. It is not recommended that the map be used for scientific applications. For future updates on these products, please contact the authors.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗