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DOE OSTI2023

Subnanometer Visualization of Spatially Varying Local Field Resonances that Drive Tip-Enhanced Optical Spectroscopy

Our knowledge of the electromagnetic fields that power modern nanoscale optical measurements, including (non)linear tip-enhanced Raman and photoluminescence, chiefly stems from numerical simulations. Aside from idealized in silico vs heterogeneous (nano)structures in the laboratory, challenges in quantitative descriptions of nanoscale light–matter interactions more generally stem from the very nature of the problem, which lies at the interface of classical and quantum theories. This is particularly the case in ultrahigh spatial resolution measurements that are sensitive to local optical field variations that take place on subnanometer length scales. Here this work approaches this challenge through extinction-based spectral nanoimaging experiments. We demonstrate <1 nm spatial resolution in hyperspectral extinction measurements that track spatially varying plasmon resonances. We describe the principles behind our experiments and highlight more general implications of our observations.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

NASA NTRSDate not supplied

Measurement Techniques for the High-Contrast and in-Field Stray-Light Performance of Oci

Scheduled for launch in January 2024, the PACE mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records [1]. A key feature of PACE is the inclusion of an advanced satellite radiometer known as the Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. A critical requirement for OCI is the high-contrast or spatial cross-talk specification (also referred to as in-field stray-light response). The requirement states that for global top-of-atmosphere radiances based on measured MODIS radiances, the global average residual contamination shall be less than 0.15% for any multispectral band. Accurate resolution of high contrast in TOA radiance images is important to estimate stray light contamination due to clouds, for studying small scale features like ocean fronts and for working in coastal and estuarine areas where the scales are 1km. This occurs in all wavelengths in the spatial direction. Knowledge of high contrast resolution makes up part of the artifact budget. Accurate measurement of the high-contrast performance of OCI requires laboratory Ground Support Equipment (GSE) that projects a scene of sufficient quality that the unwanted stray light of the GSE itself is not confused with the stray light response of the telescope. This paper concerns the development, analyses and test of the GSE to ensure the quality of the projected image is sufficient to verify the OCI requirements. Optical models were developed for both the instrument as well as the GSE and laboratory environment. Simulation of various non-ideal parameters were critical to accurately predict performance. Measurements using COTS cameras and lenses were also made of the projected GSE image to reasonably verify the optical model predictions. Measured and modelled results from OCI are discussed.

OCI↗

NASA NTRSDate not supplied

Measurement Techniques for the High-Contrast and in-Field Stray-Light Performance of OCI

OCI, PACE, LSF, PSF, Stray-light, Contrast, Cross-↗

NASA NTRS2012

Assessment of a Bidirectional Reflectance Distribution Correction of Above-Water and Satellite Water-Leaving Radiance in Coastal Waters

Water-leaving radiances, retrieved from in situ or satellite measurements, need to be corrected for the bidirectional properties of the measured light in order to standardize the data and make them comparable with each other. The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms specifically tuned for typical coastal waters and other case 2 conditions are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function (BRDF) of case 2 waters, a dataset of typical remote sensing reflectances was generated through radiative transfer simulations for a large range of viewing and illumination geometries. Based on this simulated dataset, a case 2 water focused remote sensing reflectance model is proposed to correct above-water and satellite water-leaving radiance data for bidirectional effects. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multispectral and hyperspectral radiometers, which have different viewing geometries installed at the Long Island Sound Coastal Observatory (LISCO). Match-ups and intercomparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths, with average improvement of 2.4% over the spectral range. LISCO's time series data have also been used to evaluate improvements in match-up comparisons of Moderate Resolution Imaging Spectroradiometer satellite data when the proposed BRDF correction is used in lieu of the current algorithm. It is shown that the discrepancies between coincident in-situ sea-based and satellite data decreased by 3.15% with the use of the proposed algorithm.

LISCO(LONG ISLAND SOUND COASTAL OBSERVATORY)↗

NASA NTRS2000

TERA-OPS Processing for ATR

A three-dimensional microelectronic device (3DANN-R) capable of performing general image convolution at the speed of 10***sup12*** operations/second (ops) in a volume of less than 1.5 cubic centimeter has been successfully built under the BMDO/JPL VIGILANTE program.

Automatic↗

NASA NTRS2000

Remotely-Sensed Geology from Lander-Based to Orbital Perspectives: Results for FIDO Rover Field Tests

Tests of the FIDO (Field Integration Design and Operations) rover and Athena-like operational scenarios were conducted May 7-16, 2000. A group located at the Jet Propulsion Lab, Pasadena, CA, formed the Core Operations Team (COT) that designed experiments and command sequences while another team tracked, maintained, and secured the rover in the field. The COT had no knowledge of the specific field location, thus the tests were done "blind." In addition to FIDO rover instrumentation, the COT had access to LANDSAT 7, TIMS, and AVIRIS regional coverage and color descent images. Using data from the FIDO instruments, primarily a color microscopic imager (CMI), infrared point spectrometer (IPS; 1.5-2.4 microns), and a three-color stereo panoramic camera (Pancam), the COT correlated lithologic features (mineralogy, rock types) from the simulated landing site to a regional scale. The May test results provide an example of how to relate site geology from landed rover investigations to the regional geology using remote sensing. The capability to relate mineralogic signatures using the point IR spectrometer to remotely sensed, multispectral or hyperspectral data proved to be key to integration of the in-situ and remote data. This exercise demonstrated the potential synergy between lander-based and orbital data, and highlighted the need to investigate a landing site in detail and at multiple scales.

Jolliff, B.↗

DOE OSTI2021

MULTI-MODAL global surveillance methodology for predictive and on-demand characterization of localized processes using cube satellite platforms and deep learning techniques

This paper presents the work completed towards the development of a multi-modal global surveillance methodology using cube satellite (CubeSat) platforms and novel data analysis techniques. A CubeSat system equipped with adequate sensors and data analytics capabilities can autonomously characterize various phenomena of interest on the Earth’s surface. CubeSats are advantageous over conventional satellites in certain remote monitoring applications because of their reduced construction costs (due to the availability of commercially-off-the-shelf components) and are easier to launch. The CubeSat surveillance system developed in this paper focused on phenomena of interest surrounding the nuclear fuel cycle in support of nuclear non-proliferation and emergency response. To observe the phenomena, a constellation of 3U and 6U CubeSats deployed from the ISS with adequate components was chosen. Four different sensor configurations were identified for remote sensing: panchromatic/multispectral in the visible and near-infrared spectrum, multispectral in infrared spectrum, hyperspectral in infrared spectrum, and multispectral in ultraviolet spectrum. While a panchromatic/multispectral sensor configuration has CubeSat flight heritage at the required spatial resolutions, the other three sensor types need future 3 development to meet signature and system requirements. Once each sensor onboard the CubeSat system collects data on a target of interest, the onboard computers would then apply the deep learning-based characterization methodology developed in this paper to identify phenomena. Four surrogate datasets containing representative simplified “images” were created for each sensor type to train the characterization methodology. A convolutional neural network was applied to each dataset and produced recall rates for the phenomena between 89.7% - 99.3% and precision rates between 92.3% - 99.9%. Each phenomenon’s presence probability from each network is then combined into a final characterization solution for a target area. This paper covers multiple interdisciplinary areas to develop the foundation for a CubeSat surveillance system focused on phenomena surrounding the nuclear fuel cycle.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

NASA NTRSDate not supplied

Spectral Gap Filling Method Using the Spectral Information from CLARREO-Pathfinder Measured Earth-Reflected Solar Spectra to Support CPF-CERES Intercalibration

The high-accuracy Earth-reflected solar spectral radiances from CLARREO Pathfinder (CPF) will serve as in-orbit benchmark measurements for intercalibrating other satellite imagers. The CPF team is developing a state-of-the-art intercalibration method to calibrate the shortwave channel (300-5000 nm) of the CERES instrument against the CPF reference with an uncertainty of 0.3%. Because the CPF instrument only covers spectral range from 350 nm to 2300 nm, the team has developed a spectral extension method to fill in the gaps between the spectral domains of CPF and the CERES shortwave channel. The method solely relies on using the hyperspectral information from the CPF wavelengths to predict the radiances below 350 nm and above 2300 nm. To quantify the relationship between the CPF spectrum and the non-overlapping portions of the spectrum between CPF and CERES, the team has simulated a large ensemble of spectra that cover the spectral range for both CPF and CERES. A hyperspectral bidirectional reflectance model for land surface based on thousands of measured land surface reflectance has been developed. This land surface model as well as the Cox-Munk model for ocean surface are used in the spectral gap filling. Various water/ice clouds, aerosols, atmosphere profiles and surfaces were used to simulate Earth-reflected radiances from 200 nm to 15 um under different solar and sensor geometries. The targeted uncertainty for the CPF-extended broadband CERES radiances is less than 0.1%. The previously derived training spectra were updated to replace the Kurucz solar irradiance model with the TSIS-1 Hybrid Solar Reference Spectrum. The influence of the scalar assumption in radiative transfer model equations on the uncertainty in estimating the broadband radiances was also investigated.

Hyperspectral↗

NASA NTRS2017

High-Resolution NO2 Observations from the Airborne Compact Atmospheric Mapper: Retrieval and Validation

Nitrogen dioxide (NO2) is a short-lived atmospheric pollutant that serves as an air quality indicator and is itself a health concern. The Airborne Compact Atmospheric Mapper (ACAM) was flown on board the NASA UC-12 aircraft during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality Maryland field campaign in July 2011. The instrument collected hyperspectral remote sensing measurements in the 304-910 nm range, allowing daytime observations of several tropospheric pollutants, including nitrogen dioxide (NO2), at an unprecedented spatial resolution of 1.5 × 1.1 sq. km. Retrievals of slant column abundance are based on the differential optical absorption spectroscopy method. For the air mass factor computations needed to convert these retrievals to vertical column abundance, we include high-resolution information for the surface reflectivity by using bidirectional reflectance distribution function data from the Moderate Resolution Imaging Spectroradiometer. We use high-resolution simulated vertical distributions of NO2 from the Community Multiscale Air Quality and Global Modeling Initiative models to account for the temporal variation in atmospheric NO2 to retrieve middle and lower tropospheric NO2 columns (NO2 below the aircraft). We compare NO2 derived from ACAM measurements with in situ observations from NASA's P-3B research aircraft, total column observations from the ground-based Pandora spectrometers, and tropospheric column observations from the space-based Ozone Monitoring Instrument. The high-resolution ACAM measurements not only give new insights into our understanding of atmospheric composition and chemistry through observation of subsampling variability in typical satellite and model resolutions, but they also provide opportunities for testing algorithm improvements for forthcoming geostationary air quality missions.

Lamsal, L. N.↗

NASA NTRS2017

Ultra-Stable Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (5STAR)

The Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) combines airborne sun tracking and sky scanning with diffraction spectroscopy to improve knowledge of atmospheric constituents and their links to airpollution and climate. Direct beam hyperspectral measurement of optical depth improves retrievals of gas constituentsand determination of aerosol properties. Sky scanning enhances retrievals of aerosol type and size distribution.Hyperspectral cloud-transmitted radiance measurements enable the retrieval of cloud properties from below clouds.These measurements tighten the closure between satellite and ground-based measurements. 4STAR incorporates amodular sun-tracking sky-scanning optical head with optical fiber signal transmission to rack mounted spectrometers,permitting miniaturization of the external optical tracking head, and future detector evolution.4STAR has supported a broad range of flight experiments since it was first flown in 2010. This experience provides thebasis for a series of improvements directed toward reducing measurement uncertainty and calibration complexity, andexpanding future measurement capabilities, to be incorporated into a new 5STAR instrument. A 9-channel photodioderadiometer with AERONET-matched bandpass filters will be incorporated to improve calibration stability. A wide dynamic range tracking camera will provide a high precision solar position tracking signal as well as an image of sky conditions around the solar axis. An ultrasonic window cleaning system design will be tested. A UV spectrometer tailored for formaldehyde and SO2 gas retrievals will be added to the spectrometer enclosure. Finally, expansion capability for a 4 channel polarized radiometer to measure the Stokes polarization vector of sky light will be incorporated. This paper presents initial progress on this next-generation 5STAR instrument.

atmosphere↗

NASA NTRS2016

New Methods for Retrieval of Chlorophyll Red Fluorescence from Hyperspectral Satellite Instruments: Simulations and Application to GOME-2 and SCIAMACHY

Global satellite measurements of solar-induced fluorescence (SIF) from chlorophyll over land and ocean have proven useful for a number of different applications related to physiology, phenology, and productivity of plants and phytoplankton. Terrestrial chlorophyll fluorescence is emitted throughout the red and far-red spectrum, producing two broad peaks near 683 and 736nm. From ocean surfaces, phytoplankton fluorescence emissions are entirely from the red region (683nm peak). Studies using satellite-derived SIF over land have focused almost exclusively on measurements in the far red (wavelengths greater than 712nm), since those are the most easily obtained with existing instrumentation. Here, we examine new ways to use existing hyperspectral satellite data sets to retrieve red SIF (wavelengths less than 712nm) over both land and ocean. Red SIF is thought to provide complementary information to that from the far red for terrestrial vegetation. The satellite instruments that we use were designed to make atmospheric trace-gas measurements and are therefore not optimal for observing SIF; they have coarse spatial resolution and only moderate spectral resolution (0.5nm). Nevertheless, these instruments, the Global Ozone Monitoring Instrument 2 (GOME-2) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), offer a unique opportunity to compare red and far-red terrestrial SIF at regional spatial scales. Terrestrial SIF has been estimated with ground-, aircraft-, or satellite-based instruments by measuring the filling-in of atmospheric andor solar absorption spectral features by SIF. Our approach makes use of the oxygen (O2) gamma band that is not affected by SIF. The SIF-free O2 gamma band helps to estimate absorption within the spectrally variable O2 B band, which is filled in by red SIF. SIF also fills in the spectrally stable solar Fraunhofer lines (SFLs) at wavelengths both inside and just outside the O2 B band, which further helps to estimate red SIF emission. Our approach is then an extension of previous approaches applied to satellite data that utilized only the filling-in of SFLs by red SIF. We conducted retrievals of red SIF using an extensive database of simulated radiances covering a wide range of conditions. Our new algorithm produces good agreement between the simulated truth and retrievals and shows the potential of the O2 bands for noise reduction in red SIF retrievals as compared with approaches that rely solely on SFL filling. Biases seen with existing satellite data, most likely due to instrumental artifacts that vary in time, space, and with instrument, must be addressed in order to obtain reasonable results. Our 8-year record of red SIF observations over land with the GOME-2 allows for the first time reliable global mapping of monthly anomalies. These anomalies are shown to have similar spatiotemporal structure as those in the far red, particularly for drought-prone regions. There is a somewhat larger percentage response in the red as compared with the far red for these areas that are drought sensitive. We also demonstrate that good-quality ocean fluorescence line height retrievals can be achieved with GOME-2, SCIAMACHY, and similar instruments by utilizing the full complement of radiance measurements that span the red SIF emission feature.

spatiotemporal structure↗

NASA NTRS2022

Evaluating Approaches Relating Ecosystem Productivity with Desis Spectral Information

Data from the DLR Earth Sensing Imaging Spectrometer (DESIS), mounted on the International Space Station (ISS), were used to develop and test algorithms for remotely retrieving ecosystem productivity. Twenty DESIS images were used from three widely separated forested study sites representing deciduous and conifer forests. Gross primary production (GPP) values from eddy covariance flux towers at the sites were matched with DESIS spectral reflectances collected on the same days. Multiple algorithms were successful relating spectral reflectance with GPP, including: spectral vegetation indices (SVI) sensitive to chlorophyll content, SVI used in a photosynthetic light-use efficiency model framework, spectral shape characteristics through spectral derivatives and absorption feature analysis, and statistical models leading to multiband hyperspectral indices from partial least squares regression. Successful algorithms were able to achieve R2 better than 0.7 using a diverse set of observations combining data from different sites from multiple years and at multiple times during the year. The demonstrated robustness of the algorithms provides some confidence in using DESIS imagery to map spatial patterns of GPP.

K F Huemmrich↗

NASA NTRS2022

Evaluating Approaches Relating Ecosystem Productivity with DESIS Spectral Information

Gross Primary Productivity (GPP)↗

NASA NTRS2007

Radiometric Calibration of the AWiFS Sensor and a Cross-calibration Enhanced Vicarious Calibration Technique

Using vicarious calibration validation of moderate resolution sensors such as AWiFS is complicated by requiring more land area to ensure proper registration and sufficient pixel numbers. A trial AWiFS calibration was performed on a grass site that consisted of two dramatically different grass heights. Ground truth data was collected over relatively small areas representing only a few pixels. The radiometric gain results for each of these areas will be reported. To enhance this analysis, since a near coincidence high resolution image was collected, the high resolution data was effectively resized to produce pixels comparable to AWiFS and the atmospheric model was used to produce a top of canopy radiance map. Multiple uniform vegetated areas of several radiances were then identified and subsequently propagated to the top of atmosphere viewpoint of the moderate resolution (AWiFS) satellite. The radiometric gain was then calculated based on the vendor high resolution satellite gains (for the 3 bands with comparable wavelengths). Band-to-band conversion was performed assuming a hyperspectral reflectance based on the standard vegetated site. The initial comparison produces AWiFS radiometric gain values that agree to better than 10% of the values measured using the standard vicarious gain technique.

Aaron, David↗

NASA NTRS2014

Obtaining Remote-Sensing Reflectance from Multiple Instrument Systems

Obtaining accurate in situ measurements of Apparent Optical Properties (AOPs) is critical to maintaining satellite data quality. One approach to ensure accuracy is to deploy several independent instruments to measure the same phenomenon. During a cruise in June 2012, off the lee coast of the island of Hawaii, repeated profiles were made with two separate radiometric systems, one from Satlantic, Inc. (Hyperpro) and the other from Biospherical Instruments, Inc. (C-Ops). The C-Ops is multispectral, while the Hyperpro is hyperspectral. Both measure above-water solar irradiance (E(sub s)), downwelling in-water irradiance (E(sub d)), and upwelling in-water radiance (L(sub u)). From these measurements remotely-sensed reflectance (R(sub rs))can be calculated and compared with satellite data. All instruments were calibrated shortly before use, and while differences are to be expected due to temporal changes and spectral weighting differences, these should be consistent and minimal. We explore these differences, and compare to data retrieved from the NASA Moderate Resolution Imaging Spectroradiometer onboard Aqua (MODIS Aqua) when available. We also examine data collection and processing protocols for these systems.

Carbon↗

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↗

NASA NTRS2013

A Web-Based Search Service to Support Imaging Spectrometer Instrument Operations

Imaging spectrometers yield rich and informative data products, but interpreting them demands time and expertise. There is a continual need for new algorithms and methods for rapid first-draft analyses to assist analysts during instrument opera-tions. Intelligent data analyses can summarize scenes to draft geologic maps, searching images to direct op-erator attention to key features. This validates data quality while facilitating rapid tactical decision making to select followup targets. Ideally these algorithms would operate in seconds, never grow bored, and be free from observation bias about the kinds of mineral-ogy that will be found.

hyperspectral imagery↗

NASA NTRS2019

Approach for Propagating Radiometric Data Uncertainties Through NASA Ocean Color Algorithms

Spectroradiometric satellite observations of the ocean are commonly referred to as “ocean color” remote sensing. NASA has continuously collected, processed, and distributed ocean color datasets since the launch of the Sea-viewing Wide-field-of-view Sensor (SeaWiFS) in 1997. While numerous ocean color algorithms have been developed in the past two decades that derive geophysical data products from sensor-observed radiometry, few papers have clearly demonstrated how to estimate measurement uncertainty in derived data products. As the uptake of ocean color data products continues to grow with the launch of new and advanced sensors, it is critical that pixel-by-pixel data product uncertainties are estimated during routine data processing. Knowledge of uncertainties can be used when studying long-term climate records, or to assist in the development and performance appraisal of bio-optical algorithms. In this method paper we provide a comprehensive overview of how to formulate first-order first-moment (FOFM) calculus for propagating radiometric uncertainties through a selection of bio-optical models. We demonstrate FOFM uncertainty formulations for the following NASA ocean color data products: chlorophyll-a pigment concentration (Chl), the diffuse attenuation coefficient at 490 nm (K(sub d,490)), particulate organic carbon (POC), normalized fluorescent line height (nflh), and inherent optical properties (IOPs). Using a quality-controlled in situ hyperspectral remote sensing reflectance (R(sub rs,i)) dataset, we show how computationally inexpensive, yet algebraically complex, FOFM calculations may be evaluated for correctness using the more computationally expensive Monte Carlo approach. We compare bio-optical product uncertainties derived using our test R(sub rs) dataset assuming spectrally-flat, uncorrelated relative uncertainties of 1, 5, and 10%. We also consider spectrally dependent, uncorrelated relative uncertainties in R(sub rs). The importance of considering spectral covariances in R(sub rs), where practicable, in the FOFM methodology is highlighted with an example SeaWiFS image. We also present a brief case study of two POC algorithms to illustrate how FOFM formulations may be used to construct measurement uncertainty budgets for ecologically-relevant data products. Such knowledge, even if rudimentary, may provide useful information to end-users when selecting data products or when developing their own algorithms.

Bio-optics↗