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NASA NTRS2016

Aerosol Absorption Retrievals from the PACE Broad Spectrum Ocean Color Instrument (OCI)

The PACE (Pre-Aerosol, Clouds and ocean Ecosystem) mission, anticipated for launch in the early 2020s, is designed to characterize oceanic and atmospheric properties. The primary instrument on-‐board will be a moderate resolution (approximately 1 km nadir) radiometer, called the Ocean Color Instrument (OCI). OCI will provide high spectral resolution (5 nm) from the UV to NIR (350 - 800 nm), with additional spectral bands in the NIR and SWIR. The OCI itself is an excellent instrument for atmospheric objectives, providing measurements across a broad spectral range that in essence combines the capabilities of MODIS and OMI, but with the UV channels from OMI to be available at moderate resolution. (Image credit: PACE Science Definition Team Report). Objective: Can we make use of the UV-SWIR measurements to derive information about aerosol absorption when aerosol loading is high?

aerosols↗

NASA NTRS2016

Spectralon BRDF and DHR Measurements in Support of Satellite Instruments Operating Through Shortwave Infrared

Satellite instruments operating in the reflective solar wavelength region require accurate and precise determination of the Bidirectional Reflectance Distribution Functions (BRDFs) of the laboratory and flight diffusers used in their pre-flight and on-orbit calibrations. This paper advances that initial work and presents a comparison of spectral Bidirectional Reflectance Distribution Function (BRDF) and Directional Hemispherical Reflectance (DHR) of Spectralon*, a common material for laboratory and onorbit flight diffusers. A new measurement setup for BRDF measurements from 900 nm to 2500 nm located at NASA Goddard Space Flight Center (GSFC) is described. The GSFC setup employs an extended indium gallium arsenide detector, bandpass filters, and a supercontinuum light source. Comparisons of the GSFC BRDF measurements in the ShortWave InfraRed (SWIR) with those made by the NIST Spectral Trifunction Automated Reference Reflectometer (STARR) are presented. The Spectralon sample used in this study was 2 inch diameter, 99% white pressed and sintered Polytetrafluoroethylene (PTFE) target. The NASA/NIST BRDF comparison measurements were made at an incident angle of 0 deg and viewing angle of 45 deg. Additional BRDF data not compared to NIST were measured at additional incident and viewing angle geometries and are not presented here The total combined uncertainty for the measurement of BRDF in the SWIR range made by the GSFC scatterometer is less than 1% (k=1). This study is in support of the calibration of the Joint Polar Satellite System (JPSS) Radiation Budget Instrument (RBI) and Visible Infrared Imaging Radiometer Suite (VIIRS) of and other current and future NASA remote sensing missions operating across the reflected solar wavelength region.

Georgiev, Georgi T.↗

NASA NTRS2015

Validation of EO-1 Hyperion and Advanced Land Imager Using the Radiometric Calibration Test Site at Railroad Valley, Nevada

The Earth-Observing One (EO-1) satellite was launched in 2000. Radiometric calibration of Hyperion and the Advanced Land Imager (ALI) has been performed throughout the mission lifetime using various techniques that include ground-based vicarious calibration, pseudo-invariant calibration sites, and also the moon. The EO-1 mission is nearing its useful lifetime, and this work seeks to validate the radiometric calibration of Hyperion and ALI from 2013 until the satellite is decommissioned. Hyperion and ALI have been routinely collecting data at the automated Radiometric Calibration Test Site [RadCaTS/Railroad Valley (RRV)] since launch. In support of this study, the frequency of the acquisitions at RadCaTS has been significantly increased since 2013, which provides an opportunity to analyze the radiometric stability and accuracy during the final stages of the EO-1 mission. The analysis of Hyperion and ALI is performed using a suite of ground instrumentation that measures the atmosphere and surface throughout the day. The final product is an estimate of the top-of-atmosphere (TOA) spectral radiance, which is compared to Hyperion and ALI radiances. The results show that Hyperion agrees with the RadCaTS predictions to within 5% in the visible and near-infrared (VNIR) and to within 10% in the shortwave infrared (SWIR). The 2013-2014 ALI results show agreement to within 6% in the VNIR and 7.5% in the SWIR bands. A cross comparison between ALI and the Operational Land Imager (OLI) using RadCaTS as a transfer source shows agreement of 3%-6% during the period of 2013-2014.

Czapla-Myers, Jeffrey↗

NASA NTRS2017

Optimization of a Deep Convective Cloud Technique in Evaluating the Long-Term Radiometric Stability of MODIS Reflective Solar Bands

MODIS reflective solar bands are calibrated on-orbit using a solar diffuser and near-monthly lunar observations. To monitor the performance and effectiveness of the on-orbit calibrations, pseudo-invariant targets such as deep convective clouds (DCCs), Libya-4, and Dome-C are used to track the long-term stability of MODIS Level 1B product. However, the current MODIS operational DCC technique (DCCT) simply uses the criteria set for the 0.65- m band. We optimize several critical DCCT parameters including the 11- micrometer IR-band Brightness Temperature (BT11) threshold for DCC identification, DCC core size and uniformity to help locate DCCs at convection centers, data collection time interval, and probability distribution function (PDF) bin increment for each channel. The mode reflectances corresponding to the PDF peaks are utilized as the DCC reflectances. Results show that the BT11 threshold and time interval are most critical for the Short Wave Infrared (SWIR) bands. The Bidirectional Reflectance Distribution Function model is most effective in reducing the DCC anisotropy for the visible channels. The uniformity filters and PDF bin size have minimal impacts on the visible channels and a larger impact on the SWIR bands. The newly optimized DCCT will be used for future evaluation of MODIS on-orbit calibration by MODIS Characterization Support Team.

Mu, Qiaozhen↗

NASA NTRS2018

Remote Sensing of the Ocean Surface Refractive Index via Short-Wave Infrared Polarimetry

The linear polarization of sunlight reflected by ocean surfaces in the shortwave infrared (SWIR), at geometries where specular reflection dominates the signal, is a direct function of the refractive index of the surface microlayer(SML). This simple physical concept is at the base of a novel technique presented in this study. We invert observations obtained by the airborne Research Scanning Polarimeter (RSP) in the sun glint region, where each pixel's radiance is dominated by the signal originating from the wave slopes oriented precisely to cause specular reflection. The SWIR wavelength ensures minimization of aerosol interference when radiance travels through the atmosphere; strong absorption by the water body then limits the penetration depth to the first micrometer or so, effectively probing the SML. The resulting Degree of Linear Polarization (DoLP) is then governed by the refractive index via the Fresnel law for the specfic pixel geometry, independently of the wind speed. The selected dataset concerns several field deployments from both low- and high-altitude aircraft, including total reflectance measurements with the sole purpose of accounting for the residual aerosol effect.Stable retrievals from transects above pure seawater yielded values of refractive index that match the values published in the literature within an accuracy of 5 x 10 [superscript 4]. Flying over the oil spill caused by the explosion of the Deepwater Horizon platform, detected variations were found compatible with the presence of an oil slick. The robustness of the results, guaranteedby the high RSP polarimetric accuracy (less than or equal to 0:2%), opens the possibility for remote-sensing detection of other entities that similarly affect the refractive index including whitecaps, microplastics, biological gels, seaweed and grass mats.

Surface Microlayer↗

NASA NTRS2003

Detecting water hazards for autonomous off-road navigation

Detecting water hazards for autonomous, off-road navigation of unmanned ground vehicles is a largely unexplored problem. In this paper, we catalog environmental variables that affect the difficulty of this problem, including day vs. night operation, whether the water reflects sky or other terrain features, the size of the water body, and other factors. We briefly survey sensors that are applicable to detecting water hazards in each of these conditions. We then present analyses and results for water detection for four specific sensor cases: 1) using color image classification to recognize sky reflections in water during the day, 2) using ladar to detect the presence of water bodies and to measure their depth, 3) using short-wave infrared (SWIR) imagery to detect water bodies, as well as snow and ice, and 4) using mid-wave infrared (MWIR) imagery to recognize water bodies at night. For color imagery, we demonstrate solid results with a classifier that runs at nearly video rate on a 433 MHz processor. For ladar, we present a detailed propagation analysis that shows the limits of water body detection and depth estimation as a function of look ahead distance, water depth, and ladar wavelength. For SWIR and MWIR, we present sample imagery from a variety of data collections that illustrate the potential of these sensors. These results demonstrate significant progress on this problem.

McHenry, Mike↗

NASA NTRS2021

S-NPP VIIRS Solar Diffuser Degradation at the View Direction of the Rotating Telescope Assembly

S-NPP VIIRS has been on-orbit for more than nine years since it was launched on October28th,2011. The VIIRS reflective solar bands (RSBs) are calibrated on-orbit primarily by an onboard solar diffuser (SD). The SD on-orbit degradation is tracked by an onboard SD stability monitor(SDSM). The VIIRS RSBs view the SD through a rotating telescope assembly (RTA). The RTA views the SD from a direction that is quite different from that of the SDSM. It has been shown that the SD degrades non-uniformly with respect to the incident and outgoing directions, especially at the short wavelengths. Thus, the SDSM calibration cannot provide an accurate SD degradation estimation for the view direction of the RTA, resulting in long-term drifts in the calibration coefficients derived from the SD and SDSM calibration. S-NPP VIIRS has been scheduled to view the Moon approximately monthly since its launch. The lunar observations can provide accurate long-term trends for the RSB calibration coefficients since the lunar surface reflectance is quite stable. By comparing the SD and lunar calibration results, we can obtain the SD degradation differences at the view directions of the SDSM and RTA and derive the SD degradation at the view direction of the RTA. Moreover, we can also derive the SD degradation in the short-wave infrared (SWIR) spectral range, wherein the SDSM cannot track the SD degradation. In this paper, we will derive the SD degradation for the view direction of the RTA from the SD, SDSM, and lunar calibrations from the visible to SWIR spectral range. We will also simulate the SD degradation with analytical models and compare their performances.

SNPP VIIRS↗

NASA NTRSDate not supplied

Assimilation of CrIS Shortwave Infrared Channels into the GEOS Atmospheric Data Assimilation System

In recent years, there has been a renewed interest in using the 4.3 μmshortwave infrared (SWIR) band for temperature sounding. This is in part brought on by proposed cubesat missions sensing the 4.3 μmband such as MiSTIC and CIRAS. Jones et al. has shown that shortwave infrared channels on CrIScan be used effectively in NOAA's Global Forecast and Data Assimilation System (GDAS). In this work a similar study is presented using the Goddard Earth Observing System - Atmospheric Data Assimilation System (GEOS-ADAS). Results from Observing System Experiments (OSEs) utilizing SWIR CrISare presented using standard community accepted forecast metrics including Forecast Sensitivity to Observation Impact (FSOI), and an assessment of vertical sensitivity using Jacobians from the Community Radiative Transfer Model (CRTM). The implications and utility within the GEOS-ADAS for future NASA GMAO products are discussed.

Bryan M Karpowicz↗

NASA NTRSDate not supplied

PACE OCI Short-Wave Infrared Detection Assembly frequency-dependent linearity characterization and uncertainty analysis

The Ocean Color Instrument (OCI), the primary payload of the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE)observatory, will collect data to monitor the health of Earth’s oceans and atmosphere. The Short-Wave Infrared(SWIR) Detection Assembly (SDA) was built and characterized by the Utah State University Space DynamicsLaboratory (SDL) and is a subsystem of OCI. The SDA measures seven bands centered at 940, 1038, 1250, 1378,1615, 2130, and 2260 nm, with standard- and high-gain varieties for the 1250 and 1615 nm bands, resulting in nine total detection configurations in the SWIR. The delivery of high-quality science data is critically dependent upon accurately characterizing the linearity of the SDA. Two metrology techniques were employed to measure the linearity and characterize the frequency-dependent linearity uncertainty of the system. The first technique used superposition linearity measurements to determine the DC linearity, and the second technique involved an oscillating small-signal response at seven frequencies to determine the frequency-dependent linearity. Discrepancies between the DC and frequency-dependent linearities constrain the uncertainty between the two. Examining the difference between these two methods for all SDA channels, we find most channels experience an uncertainty below0.2% with a worst-case measurement uncertainty of 0.31%. Averaging SDA channels with similar detectors, optical filters, and electronics to simulate the flight-like data products yields a worst-case frequency-dependence linearity uncertainty of 0.12%, demonstrating minimal frequency dependence, implying an excellent linearity knowledge.Detailed performance knowledge, including linearity performance, verifies data quality and builds confidence in the success of the PACE mission.

PACE↗

NASA NTRSDate not supplied

Machine Learning Application for Improving Cloud Detection and Phase Determination Over Sunglint Regions for Geostationary Satellites

Cloud detection and phase determination over sunglint regions has been a challenge, especially for geostationary (GEO) satellites. Sunglint is observed when the sunlight specular reflection is at the same viewing angle of the satellite sensor. This intense reflection in the visible channels (VIS) is often comparable to that from optically thick clouds. It also contaminates the shortwave infrared channels (SWIR). Consequently, VIS and SWIR channels become less useful - or not useful- when they are saturated, hampering the detection of cloudy and clear-sky pixels. Sunglint contamination happens frequently and exists nearly in every daytime GEO full disk satellite images. However, sunglint intensity and region are difficult to model due to variable viewing geometry and ocean surface conditions. Moreover, existing physical models do not meet the accuracy required for operational GEO satellite cloud detection. We developed a machine learning algorithm to improve cloud detection in sunglint conditions for the NASA Langley’s Satellite ClOud and radiation Property retrieval System (SatCORPS). This poster presents our recent progress in the algorithm development, validation and applications. The algorithm is validated using collocated SatCORPS GOES-East and GOES-West cloud products. We demonstrate that the machine learning cloud detection in sunglint regions is superior to the traditional approach by improving temporal consistency between sunglint and non-sunglint conditions.

Machine Learning, Cloud detection, Sunglint, SatCO↗

NASA NTRS2022

Infrared Spectral Responses of the Ocean Color Instrument (OCI) Pre-assembly and Integration

Spectral characterizations were made of the Ocean Color Instrument (OCI) short-wave infrared (SWIR) Detection Subassembly (SDS) responses (940–2260 nm) prior to their integration. Using modulated output light from a Fourier transform spectrometer, the in-band relative spectral responses of the nine different configurations of SDSs were found along with out-of-band (OOB) sensitivity. From these spectral responses, the center wavelengths (λ0), full widths at half of the maximum, full widths at 1% of the maximum, and OOB rejection ratios were determined. All spectral parameters are within requirements. There are 2–8 repeats of each configuration, and the 1 σ spread among repeats is largest for the 1250 nm and 1615 nm high-gain configurations and is greater than 1 nm. The engineering requirement is for these values to be within ±4 nm and ±10 nm, respectively, of 19 the nominal λ0. There is also a λ0 temperature dependence, which is expected. This temperature dependence is nearly a linear function of wavelength with a 9.5 × 10−3 nm K−1 relationship on average.

PACE↗

NASA NTRS2022

Spectral Responses of the PACE OCI Short-Wave Infrared Detection Assembly

The Ocean Color Instrument (OCI) to go on the Plankton, Aerosol, Cloud, ocean Ecology (PACE) Earth-observing satellite has a Short-wave infrared (SWIR) Detection Assembly (SDA). This SDA is used to measure upwelling radiation in seven discrete bands from 940 to 2260 nm. There are redundant measurements of each band for a total of 32 physical channels, which includes optical components through to detection. The relative spectral response (RSR) is measured for each channel, which is needed when accounting for the spectral distribution of sensed radiance. From the RSR, single-value performance metrics are computed including the center wavelength, the full width at half of the maximum (FWHM), and the full width at 1% of the maximum (FW1P). Besides in-band responses, the out-of-band rejection ratio (OOBRR) is also calculated for each of the channels, which is a measure of the sensitivity outside the band of interest. We find that all 32 SDA detection channels meet the spectral response requirements at the qualification temperatures at which tests were conducted.

PACE↗

NASA NTRSDate not supplied

Space Qualification Studies of AOTF Devices Under the MISSE-11 Mission

The acousto-optic tunable filter (AOTF) devices are used in a variety of applications including hyperspectral and spectrapolarimetric based imaging. The AOTF devices provide several advantages including speed and random access to desired spectral bands and enable all-solid-state operation that are attractive for space applications. In this paper, the performance of Tellurium Dioxide (TeO 2 ) and Mercurous Bromide (Hg 2 Br 2 ) AOTF devices in space environment carried out under the NASA’s Materials International Space Station Experiments 11 (MISSE-11) mission is discussed. The purpose of the MISSE-11 mission was to study materials and devices subjected to space conditions for long term while attached to the International Space station (ISS). The TeO 2 AOTF was developed for short wavelength IR (SWIR) operation while the Hg 2 Br 2 AOTF device was developed for long wavelength IR (LWIR) operation. These devices were attached to the ISS platform for more than a year. Pre-flight and post-flight performance characterization were performed on these devices. In the case of TeO 2 AOTF, the preflight efficiency was around 87% with a center frequency at 68MHz while the post-flight efficiency was around 83%. However, the optical transmission of Hg 2 Br 2 AOTF had deteriorated considerably. The details of performance testing and analysis of both AOTF devices are discussed.

Space Qualification↗

NASA NTRS1980

An airborne short wave infrared /SWIR/ pushbroom imaging system using a 64-element PbS detector array

Research evidence indicates that data in the short wave infrared (SWIR) spectral region will greatly improve the information content of remotely sensed data. Bands are required in the 1.55-1.75 micron and 2.08-2.35 micron spectral regions for a variety of agricultural and geological investigations. It is anticipated that future Landsat sensors will use pushbroom linear array technology to obtain high resolution, improved sensitivity and increased system reliability. To obtain early laboratory and field data, an airborne pushbroom image system has been designed for operation in the short wave infrared spectral region. The system uses a 64-element staggered PbS array and is operated at 195 K; the instrument has been designed to operate in an aircraft and will view a 19 degree swath width with a 5.8 mrad IFOV. The spectral bandwidth of each channel is .05 micron and the noise equivalent reflectivity in the order of .2% is provided. The requirements for more advanced detector arrays for use in future NASA spacecraft remote sensing instruments are also discussed.

Husain-Abidi, A. S.↗

NASA NTRS1982

Image science team

A substantial technology base of solid state pushbroom sensors exists and is in the process of further evolution at both GSFC and JPL. Technologies being developed relate to short wave infrared (SWIR) detector arrays; HgCdTe hybrid detector arrays; InSb linear and area arrays; passive coolers; spectral beam splitters; the deposition of spectral filters on detector arrays; and the functional design of the shuttle/space platform imaging spectrometer (SIS) system. Spatial and spectral characteristics of field, aircraft and space multispectral sensors are summaried. The status, field of view, and resolution of foreign land observing systems are included.

Ando, K.↗

NASA NTRS1982

Multispectral Linear Array (MLA) science and technology program

A Goddard Space Flight Center program of science studies and technology development to provide the basis for future earth observation sensors employing multispectral linear array (MLA) technology is described. Establishment of MLA performance parameters and performance modeling make up the primary science activities. Critical technologies being developed include: short-wave infrared (SWIR) detector arrays, visible/and near infrared detector arrays, and passive cryogenic coolers. Supporting activities include: test and field instrument development, focal plane research and assessment laboratory, system simulation laboratory, calibration sources and techniques, optics, and thermal infrared arrays.

Barnes, W. L.↗

NASA NTRS1983

Regolith breccia Allan Hills A81005 - Evidence of lunar origin, and petrography of pristine and nonpristine clasts

It is shown that the ratios of MnO/FeO in pyroxene, texture (abundant brown and swirly glass, which are typical of lunar regolith breccias) and overall composition (approximately 75 percent plagioclase) indicate a lunar origin for the regolith breccia Allan Hills A81005, presumably from an unsampled region of the moon. The rock is found to differ in detail from other regolith samples; for example, it has exceptionally low contents of Na and KREEP. In addition, a pristine clast is found to contain exceptionally coarse augite in comparison with similar Apollo samples. It is found that ALHA81005 is not perceptibly more shocked than typical Apollo regolith breccias. It is concluded that the discovery of this rock on earth strengthens the suggestion that SNC achondrites were derived by impact ejection from Mars.

Warren, P. H.↗

NASA NTRS1982

Imaging Science Panel. Multispectral Imaging Science Working Group joint meeting with Information Science Panel: Introduction

The state-of-the-art of multispectral sensing is reviewed and recommendations for future research and development are proposed. specifically, two generic sensor concepts were discussed. One is the multispectral pushbroom sensor utilizing linear array technology which operates in six spectral bands including two in the SWIR region and incorporates capabilities for stereo and crosstrack pointing. The second concept is the imaging spectrometer (IS) which incorporates a dispersive element and area arrays to provide both spectral and spatial information simultaneously. Other key technology areas included very large scale integration and the computer aided design of these devices.

Source record↗