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NASA NTRS2020

Global Evaluation of Terrestrial Near-Surface Air Temperature and Specific Humidity Retrievals from the Atmospheric Infrared Sounder (AIRS)

Global observations of near-surface air temperature and specific humidity over land are needed for a variety of applications, including to constrain global estimates of evapotranspiration (ET). Spaceborne hyperspectral observations, such as those from NASA’s Atmospheric Infrared Sounder (AIRS) mission, show promise for meeting this need, yet there are surprisingly few validation studies of AIRS near-surface atmospheric state retrievals. In this study, we use triple collocation to validate AIRS Level 3 retrievals of near-surface atmospheric state over land using twelve years of gridded station observations and two reanalyses. Deseasonalized AIRS retrievals correlate well with deseasonalized ground observations outside the tropics, but correlate less well in the tropics. Lower temporal sensitivity near the surface in the tropics contributes to the lower correlation for near-surface air temperature and is consistent with known physics of the tropical atmosphere, in which temperatures outside the boundary layer (which dominate the AIRS retrieval signal) are poorly correlated with those near the surface. Retrievals in the tropics may also be more susceptible to errors in cloud-clearing algorithms, and to uncertainty in surface emissivity. Since ET is greatest in the tropics, and tropical measurement networks are particularly sparse, this work motivates new approaches for measuring ET in the tropics.

Evapotranspiration↗

NASA NTRS2021

Adaptive Data Screening for Multi-Angle Polarimetric Aerosol and Ocean Color Remote Sensing Accelerated by Automatic Differentiation

Remote sensing measurements from multi-angle polarimeters (MAPs) contain rich aerosol microphysical property information, and these sensors have been used to perform retrievals in optically complex atmosphere and ocean systems. Previous studies have concluded that, generally, five moderately separated viewing angles in each spectral band provide sufficient accuracy for aerosol property retrievals, with performance gradually saturating as angles are added above that threshold. The Hyper-Angular Rainbow Polarimeter (HARP) instruments provide high angular sampling with a total of 90-120 unique angles across four bands, a capability developed mainly for liquid cloud retrievals. In practice, not all view angles are optimal for aerosol retrievals due to impacts of clouds, sun glint, and other impediments. The many viewing angles of HARP can provide resilience to these effects, if the impacted views are screened from the dataset, as the remaining views may be sufficient for successful analysis. In this study, we discuss how the number of available viewing angles impacts aerosol and ocean color retrieval uncertainties, as applied to two versions of the HARP instrument. AirHARP is an airborne prototype that was deployed in the ACEPOL field campaign, while HARP2 is an instrument in development for the upcoming NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. Based on synthetic data, we find that a total of 20-30 angles across all bands (i.e. five to eight viewing angles per band) are sufficient to achieve good retrieval performance. Following from this result, we develop an adaptive multi-angle polarimetric data screening (MAPDS) approach to evaluate data quality by comparing measurements with their best-fitted forward model. The FastMAPOL retrieval algorithm is used to retrieve scene geophysical values, by matching an efficient, deep learning-based, radiative transfer emulator to observations. The data screening method effectively identifies and removes viewing angles affected by thin cirrus clouds and other anomalies, improving retrieval performance. This was tested with AirHARP data, and we found agreement with the High Spectral Resolution Lidar-2 (HSRL-2) aerosol data. The data screening approach can be applied to modern satellite remote sensing missions, such as PACE, where a large amount of multi-angle, hyperspectral, polarimetric measurements will be collected.

multi-angle polarimeter↗

NASA NTRS2017

Atmospheric Correction for Hyperspectral Ocean Color Retrieval with Application to the Hyperspectral Imager for the Coastal Ocean (HICO)

The classical multi-spectral Atmospheric Correction (AC) algorithm is inadequate for the new generation of spaceborne hyperspectral sensors such as NASA's first hyperspectral Ocean Color Instrument (OCI) onboard the anticipated Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission. The AC process must estimate and remove the atmospheric path radiance contribution due to the Rayleigh scattering by air molecules and scattering by aerosols from the measured top-of-atmosphere (TOA) radiance, compensate for the absorption by atmospheric gases, and correct for reflection and refraction of the air-sea interface. In this work, we present and evaluate an improved AC for hyperspectral sensors developed within NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Data Analysis System software package (SeaDAS). The improvement is based on combining the classical AC approach of multi-spectral capabilities to correct for the atmospheric path radiance, extended to hyperspectral, with a gas correction algorithm to compensate for absorbing gases in the atmosphere, including water vapor. The SeaDAS-hyperspectral version is capable of operationally processing the AC of any hyperspectral airborne or spaceborne sensor. The new algorithm development was evaluated and assessed using the Hyperspectral Imager for Coastal Ocean (HICO) scenes collected at the Marine Optical BuoY (MOBY) site, and other SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and AERosol Robotic NETwork - Ocean Color (AERONET-OC) coastal sites. A hyperspectral vicarious calibration was applied to HICO, showing the validity and consistency of HICO's ocean color products. The hyperspectral AC capability is currently available in SeaDAS to the scientific community at https://oceancolor.gsfc.nasa.gov/.

Ocean Color↗

NASA NTRS2023

Development of the Ames Global Hyperspectral Synthetic Data Set: Surface Bidirectional Reflectance Distribution Function

This study introduces the Ames Global Hyperspectral Synthetic Data set (AGHSD), in particular the surface bidirectional reflectance distribution function (BRDF) product, to support the NASA Surface Biology and Geology (SBG) mission development. The data set is generated based on the corresponding multispectral BRDF products from NASA's MODIS satellite sensor. Based on theories of radiative transfer in vegetation canopies, we derive a simple but robust relationship that indicates that the hyperspectral surface BRDF can be accurately approximated as a weighted sum of the soil surface reflectance, the leaf single albedo, and the canopy scattering coefficient, where the weights or coefficients are spectrally invariant and thus readily estimated from the multispectral MODIS products. We validate the algorithm with simulations by a Monte Carlo Ray Tracing model and find the results highly consistent with the theoretic derivation. Using reflectance spectra of soil and vegetation derived from existing spectral libraries, we apply the algorithm to generate the AGHSD BRDF product at 1 km and 8-day resolutions for the year of 2019. The data set is biogeochemically and biogeophysically coherent and consistent, and serves the goal to support the SBG community in developing sciences and applications for the future global imaging spectroscopy mission.

Hyperspectral Remote Sensing↗

NASA NTRS2019

Applicability of Spectral Decomposition by Varimax-Rotated, Principal Component Analysis to the Surface Biology and Geology (SBG) VNIR Mission Concept

Cyanobacterial and Harmful Algal Blooms (CyanoHABs) are a growing concern in coastal and inland waters. But, spectral interference from multiple constituents in optically complex waters can hamper application of remote sensing using traditional image processing methods. The Kent State University (KSU) spectral decomposition method can be applied to multispectral and hyperspectral remote sensing images (e.g. HICO and the NASA Glenn HSI2) to partition and identify signals related to cyanobacteria, algae, pigment degradation products and suspended sediment in each pixel. Fundamental to the use of remote sensing data is the ability to extract independent signals from correlated hyperspectral VNIR data cubes. The Kent State University varimax-rotated, principal component analysis method (VPCA) is important to integrate into the SBG VNIR mission concept because it provides greater specificity, a software-based SNR boost relative to hardware performance, and can assist with Cal/Val, Modeling and Applications. We present examples of the hyperspectral application of the KSU VPCA method with relevance to SBG. The information extracted by VPCA can be validated spectrally or spatially with laboratory and/or in situ sensors, which capture spatial or time series of information at discrete points within remote sensing images. Comparisons show hyperspectral sensors extract more components than multispectral ones, but more independent information can be extracted from multispectral sensors by VPCA than traditional band ratio approaches. The spectral decomposition method is capable of enhancing the signal to noise ratio (SNR) of the NASA Glenn, second-generation hyperspectral imager by a factor of 7x to 20x, with a spectral reproducibility of ±3%. The spectral decomposition method, when compared against existing remote sensing monitoring methods exhibits both greater specificity and a lower detection limit. The method has been validated with multispectral images in Lake Erie to quantify the Microcystis CyanoHAB and from the Indian River Lagoon, Florida to quantify the Brown Tide resulting from A. lagunesnsis. Field operations in the Western Basin of Lake Erie were conducted using a bbe Fluoroprobe to collect vertical profiles and horizontal tows along a transect from the Toledo to the Detroit Lighthouse during coincident satellite overpasses. Extraction of pixel values from the MODIS Aqua sensor yields agreement between in situ field and lab-based measures of cyanobacterial, cryptophyte, diatoms and green algae, suspended sediment and pigment degradation products with R2>0.8.

hyperspectral↗

NASA NTRS2015

Coastal and Inland Aquatic Data Products for the Hyperspectral Infrared Imager (HyspIRI)

The HyspIRI Aquatic Studies Group (HASG) has developed a conceptual list of data products for the HyspIRI mission to support aquatic remote sensing of coastal and inland waters. These data products were based on mission capabilities, characteristics, and expected performance. The topic of coastal and inland water remote sensing is very broad. Thus, this report focuses on aquatic data products to keep the scope of this document manageable. The HyspIRI mission requirements already include the global production of surface reflectance and temperature. Atmospheric correction and surface temperature algorithms, which are critical to aquatic remote sensing, are covered in other mission documents. Hence, these algorithms and their products were not evaluated in this report. In addition, terrestrial products (e.g., land use land cover, dune vegetation, and beach replenishment) were not considered. It is recognized that coastal studies are inherently interdisciplinary across aquatic and terrestrial disciplines. However, products supporting the latter are expected to already be evaluated by other components of the mission. The coastal and inland water data products that were identified by the HASG, covered six major environmental and ecological areas for scientific research and applications: wetlands, shoreline processes, the water surface, the water column, bathymetry and benthic cover types. Accordingly, each candidate product was evaluated for feasibility based on the HyspIRI mission characteristics and whether it was unique and relevant to the HyspIRI science objectives.

Infrared↗

NASA NTRS2011

The Hyperspectral Thermal Emission Spectrometer (HyTES): Preliminary Results

The Hyperspectral Thermal Emission Spectrometer (HyTES) is being developed as part of the risk reduction activities associated with the Hyperspectral Infrared Imager (HyspIRI). HyspIRI is one of the Tier 2 Decadal Survey Missions. HyTES will provide information on how to place the filters on the HyspIRI Thermal Infrared Instrument (TIR) as well as provide antecedent science data. The pushbroom design has 512 spatial pixels over a 50-degree field of view and 256 spectral channels between 7.5 micrometers to 12 micrometers. HyTES includes many key enabling state-of-the-art technologies including a high performance convex diffraction grating, a quantum well infrared photodetector (QWIP) focal plane array, and a compact Dyson-inspired optical design. The Dyson optical design allows for a very compact and optically fast system (F/1.6). It also minimizes cooling requirements due to the fact it has a single monolithic prism-like grating design which allows baffling for stray light suppression. The monolithic configuration eases mechanical tolerancing requirements which are a concern since the complete optical assembly is operated at cryogenic temperatures ((is) approximately 100K). The QWIP allows for optimum spatial and spectral uniformity and provides adequate responsivity or D-star to allow 200mK noise equivalent temperature difference (NEDT) operation across the LWIR passband. Assembly of the system is nearly complete. After completion, alignment results will be presented which show low keystone and smile distortion. This is required to minimize spatial-spectral mixing between adjacent spectral channels and spatial positions. Predictions show the system will have adequate signal to noise for laboratory calibration targets.

Moon Mineralogical Mapper (M3).↗

NASA NTRS2021

Mapping Boreal Forest Spruce Beetle Health Status at the Individual Crown Scale Using Fused Spectral and Structural Data

The frequency and severity of spruce bark beetle outbreaks are increasing in boreal forests leading to widespread tree mortality and fuel conditions promoting extreme wildfire. Detection of beetle infestation is a forest health monitoring (FHM) priority but is hampered by the challenges of detecting early stage (“green”) attack from the air. There is indication that green stage might be detected from vertical gradients of spectral data or from shortwave infrared information distributed within a single crown. To evaluate the efficacy of discriminating “non-infested”, “green”, and “dead” health statuses at the landscape scale in Alaska, USA, this study conducted spectral and structural fusion of data from: (1) Unoccupied aerial vehicle (UAV) multispectral (6 cm) + structure from motion point clouds (~700 pts per sq. m); and (2) Goddard Lidar Hyperspectral Thermal (G-LiHT) hyperspectral (400 to 1000 nm, 0.5 m) + SWIR-band lidar (~32 pts per sq.m). We achieved 78% accuracy for all three health statuses using spectral + structural fusion from either UAV or G-LiHT and 97% accuracy for non-infested/dead using G-LiHT. We confirm that UAV 3D spectral (e.g., greenness above versus below median height in crown) and lidar apparent reflectance metrics (e.g., mean reflectance at 99th percentile height in crown), are of high value, perhaps capturing the vertical gradient of needle degradation. In most classification exercises, UAV accuracy was lower than G-LiHT indicating that collecting ultra-high spatial resolution data might be less important than high spectral resolution information. While the value of passive optical spectral information was largely confined to the discrimination of non-infested versus dead crowns, G-LiHT hyperspectral band selection (~400, 675, 755, and 940 nm) could inform future FHM mission planning regarding optimal wavelengths for this task. Interestingly, the selected regions mostly did not align with the band designations for our UAV multispectral data but do correspond to, e.g., Sentinel-2 red edge bands, suggesting a path forward for moderate scale bark beetle detection when paired with suitable structural data.

Janice Cessna↗

NASA NTRSDate not supplied

PACE OCI Polarization Sensitivity Based on Pre-launch Testing

The Ocean Color Instrument (OCI) is a sensor on the upcoming Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, scheduled for launch in early 2024. OCI is a grating spectrometer with hyperspectral coverage from the ultraviolet (about 310 nm) to near-infrared (about 900 nm), with additional filtered channels in the short-wave infrared (940 nm – 2260 nm). This instrument will provide ocean color science data to continue the data sets collected by heritage sensors MODIS, SeaWiFs, and VIIRS, but with increased spectral coverage and improved accuracy. In order to achieve the high levels of accuracy demanded by the science community, a rigorous ground test program was conducted to calibrate the instrument and ensure that the calibration can be transferred to on-orbit operations. Some calibration parameters can only be measured during pre-launch testing; one such parameter is the polarization sensitivity. Polarization testing measured the Mueller matrix components needed to determine the polarization sensitivity for all spectral bands for a series of telescope scan angles covering the expected on-orbit scan range. Results indicate that the sensitivity is below 0.6 % except at the shortest wavelengths (less than 340 nm) and was characterized to better than 0.1 % above 340 nm. This indicates that any polarized scenes measured on orbit can be corrected for with a high degree of confidence.

PACE↗

NASA NTRSDate not supplied

PACE OCI Polarization Sensitivity Based on Pre-launch Testing

PACE↗

DOE OSTI2023

Exploring Mission Design for Imaging Spectroscopy Retrievals for Land and Aquatic Ecosystems

The retrieval algorithms used for optical remote sensing satellite data to estimate Earth's geophysical properties have specific requirements for spatial resolution, temporal revisit, spectral range and resolution, and instrument signal-to-noise ratio (SNR) performance to meet biogeoscience objectives. Studies to estimate surface properties from hyperspectral data use a range of algorithms sensitive to various sources of spectroscopic uncertainty, which are in turn influenced by mission architecture choices. Retrieval algorithms vary across scientific fields and may be more or less sensitive to mission architecture choices that affect spectral, spatial, or temporal resolutions and spectrometer SNR. We used representative remote sensing algorithms across terrestrial and aquatic study domains to inform aspects of mission design that are most important for impacting accuracy in each scientific area. We simulated the propagation of uncertainties in the retrieval process including the effects of different instrument configuration choices. We found that retrieval accuracy and information content degrade consistently at >10 nm spectral resolution, >30 m spatial resolution, and >8-day revisit. In these studies, the noise reduction associated with lower spatial resolution improved accuracy vis à vis high spatial resolution measurements. The interplay between spatial resolution, temporal revisit, and SNR can be quantitatively assessed for imaging spectroscopy missions and used to identify key components of algorithm performance and mission observing criteria.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2023

Exploring Mission Design for Imaging Spectroscopy Retrievals for Land and Aquatic Ecosystems

A. M. Raiho↗

NASA NTRS2003

EOS-Aura's Ozone Monitoring Instrument (OMI): Validation Requirements

OMI is an advanced hyperspectral instrument that measures backscattered radiation in the UV and visible. It will be flown as part of the EOS Aura mission and provide data on atmospheric chemistry that is highly synergistic with other Aura instruments HIRDLS, MLS, and TES. OMI is designed to measure total ozone, aerosols, cloud information, and UV irradiances, continuing the TOMS series of global mapped products but with higher spatial resolution. In addition its hyperspectral capability enables measurements of trace gases such as SO2, NO2, HCHO, BrO, and OClO. A plan for validation of the various OM1 products is now being formulated. Validation of the total column and UVB products will rely heavily on existing networks of instruments, like NDSC. NASA and its European partners are planning aircraft missions for the validation of Aura instruments. New instruments and techniques (DOAS systems for example) will need to be developed, both ground and aircraft based. Lidar systems are needed for validation of the vertical distributions of ozone, aerosols, NO2 and possibly SO2. The validation emphasis will be on the retrieval of these products under polluted conditions. This is challenging because they often depend on the tropospheric profiles of the product in question, and because of large spatial variations in the troposphere. Most existing ground stations are located in, and equipped for, pristine environments. This is also true for almost all NDSC stations. OMI validation will need ground based sites in polluted environments and specially developed instruments, complementing the existing instrumentation.

Brinksma, E. J.↗

NASA NTRS2014

Aerosol, Cloud and Trace Gas Observations Derived from Airborne Hyperspectral Radiance and Direct Beam Measurements in Recent Field Campaigns

The AERONET (AErosol RObotic NETwork) ground-based suite of sunphotometers provides measurements of spectral aerosol optical depth (AOD), precipitable water and spectral sky radiance, which can be inverted to retrieve aerosol microphysical properties that are critical to assessments of aerosol-climate interactions. Because of data quality criteria and sampling constraints, there are significant limitations to the temporal and spatial coverage of AERONET data and their representativeness for global aerosol conditions. The 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) instrument, jointly developed by NASA Ames and PNNL with NASA Goddard collaboration, combines airborne sun tracking and AERONET-like sky scanning with spectroscopic detection. Being an airborne instrument, 4STAR has the potential to fill gaps in the AERONET data set. Dunagan et al. [2013] present results establishing the performance of the instrument, along with calibration, engineering flight test, and preliminary scientific field data. The 4STAR instrument operated successfully in the SEAC4RS [Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys] experiment in Aug./Sep. 2013 aboard the NASA DC-8 and in the DoE [Department of Energy]-sponsored TCAP [Two Column Aerosol Project, July 2012 & Feb. 2013] experiment aboard the DoE G-1 aircraft (Shinozuka et al., 2013), and acquired a wealth of data in support of mission objectives on all SEAC4RS and TCAP research flights. 4STAR provided direct beam measurements of hyperspectral AOD, columnar trace gas retrievals (H2O, O3, NO2; Segal-Rosenheimer et al., 2014), and the first ever airborne hyperspectral sky radiance scans, which can be inverted to yield the same products as AERONET ground-based observations. In addition, 4STAR measured zenith radiances underneath cloud decks for retrievals of cloud optical depth and effective diameter. In this presentation, we provide an overview of the new 4STAR capabilities for airborne field campaigns, with an emphasis on comparisons between 4STAR and AERONET sky radiances, and retrievals of aerosol microphysical properties based on sky radiance measurements, column trace gas amounts from spectral direct beam measurements and cloud property retrievals from zenith mode observations for a few select case studies in the SEAC4RS and TCAP experiments. We summarize the aerosol, trace gas, cloud and airmass characterization studies made possible by the combined 4STAR direct beam, and sky/zenith radiance observations.

Aerosol-Climate↗

NASA NTRS2026

Hyperspectral Detail Meets Radiometric Accuracy: A Foundational Reflected Solar Capability for the Coming Decade

Hyperspectral Earth-reflected solar measurements contain rich, detailed information about clouds, aerosols, and the atmosphere. This information compounds when paired with high, SI-traceable radiometric accuracy. Unlike spectral resolution, which can be resampled to coarser spectral resolutions, radiometric accuracy cannot be recovered once a measurement is made, making the choice to invest in this capability now a decision with lasting consequences for the climate record. CLARREO Pathfinder is demonstrating that this combination of hyperspectral sampling and benchmark-quality accuracy is achievable today, but no follow-on mission is currently planned within NASA's Earth Science Division portfolio, and the recent cancellation of the European Space Agency TRUTHS mission has heightened the urgency of sustaining this capability. We recommend prioritizing investment in a follow-on to CLARREO Pathfinder, along with dedicated support for the science community to fully exploit these measurements. This capability would reduce long-standing uncertainties in cloud feedback, aerosol forcing, and global energy imbalance, while providing a degradation-resistant, gap-resilient calibration foundation for the broader Earth observing system. Building on flight-proven technology and an engaged science community, this is a near-term, fiscally realistic opportunity to secure a foundational Earth observation capability for the coming decade.

satellite↗

NASA NTRS2016

Ultraviolet Satellite Measurements of Volcanic Ash

Ultraviolet (UV) remote sensing of volcanic ash and other absorbing aerosols from space began with the launch of the first Total Ozone Mapping Spectrometer (TOMS) instrument in 1978. Subsequent UV satellite missions (TOMS, GOME, SCIAMACHY, OMI, GOME-2, OMPS) have extended UV ash measurements to the present, generating a unique multidecadal record. A UV Aerosol Index (UVAI) based on two near-UV wavelengths, equally applicable to multispectral (TOMS, DSCOVR) or hyperspectral (GOME, SCIAMACHY, OMI, GOME-2, OMPS) instruments, has been used to derive a unique absorbing aerosol climatology across multiple UV satellite missions. Advantages of UV ash measurements relative to infrared (IR) techniques include the ability to detect ash at any altitude (assuming no clouds), above clouds, and over bright surfaces, where visible and IR techniques may fail. Disadvantages include the daytime-only restriction and nonspecificity to silicate ash, since UV measurements are sensitive to any UV-absorbing aerosol, including smoke, desert dust, and pollution. However, simultaneous retrieval of sulfur dioxide (SO2) abundance and UVAI provides robust discrimination of volcanic clouds. Although the UVAI is only semiquantitative, it has proved successful at detecting and tracking volcanic ash clouds from many volcanic eruptions since 1978. NASA A-Train measurements since 2006 (eg, CALIOP) have provided much improved constraints on volcanic ash altitude, and also permit identification of aerosol type through sensor synergy. Quantitative UV retrievals of ash optical depth, effective particle size, and ash column mass are possible and require assumptions of ash refractive index, particle size distribution, and ash layer altitude. The lack of extensive ash refractive index data in the UV-visible and the effects of ash particle shape on retrievals introduce significant uncertainty in the retrieved parameters, although limited validation against IR ash retrievals has been successful. In this contribution, we review UV ash detection and retrieval techniques and provide examples of volcanic eruptions detected in the approx. 37 year data record.

Multidecadal record↗

NASA NTRS2012

The HYSPIRI Decadal Survey Mission: Update on the Mission Concept and Science Objectives for Global Imaging Spectroscopy and Multi-Spectral Thermal Measurements

The NASA HyspIRI mission is planned to provide global solar reflected energy spectroscopic measurement of the terrestrial and shallow water regions of the Earth every 19 days will all measurements downlinked. In addition, HyspIRI will provide multi-spectral thermal measurements with a single band in the 4 micron region and seven bands in the 8 to 12 micron region with 5 day day/night coverage. A direct broadcast capability for measurement subsets is also planned. This HyspIRI mission is one of those designated in the 2007 National Research Council (NRC) Decadal Survey: Earth Science and Applications from Space. In the Decadal Survey, HyspIRI was recognized as relevant to a range of Earth science and science applications, including climate: "A hyperspectral sensor (e.g., FLORA) combined with a multispectral thermal sensor (e.g., SAVII) in low Earth orbit (LEO) is part of an integrated mission concept [described in Parts I and II] that is relevant to several panels, especially the climate variability panel." The HyspIRI science study group was formed in 2008 to evaluate and refine the mission concept. This group has developed a series of HyspIRI science objectives: (1) Climate: Ecosystem biochemistry, condition & feedback; spectral albedo; carbon/dust on snow/ice; biomass burning; evapotranspiration (2) Ecosystems: Global plant functional types, physiological condition, and biochemistry including agricultural lands (3) Fires: Fuel status, fire frequency, severity, emissions, and patterns of recovery globally (4) Coral reef and coastal habitats: Global composition and status (5) Volcanoes: Eruptions, emissions, regional and global impact (6) Geology and resources: Global distributions of surface mineral resources and improved understanding of geology and related hazards These objectives are achieved with the following measurement capabilities. The HyspIRI imaging spectrometer provides: full spectral coverage from 380 to 2500 at 10 nm sampling; 60 m spatial sampling with a 150 km swath; and fully downlinked coverage of the Earth's terrestrial and shallow water regions every 19 days to provide seasonal cloud-free coverage of the terrestrial surface. The HyspIRI Multi-Spectral Thermal instrument provides: 8 spectral bands from 4 to 12 microns; 60 m spatial sampling with a 600 km swath; and fully downlinked coverage of the Earth's terrestrial shallow water regions every 5 days (day/night) to provide nominally cloud-free monthly coverage. The HyspIRI mission also includes an on-board processing and direct broadcast capability, referred to as the Intelligent Payload Module (IPM), which will allow users with the appropriate antenna to download a subset of the HyspIRI data stream to a local ground station. These science and science application objectives are critical today and uniquely addressed by the combined imaging spectroscopy, thermal infrared measurements, and IPM direct broadcast capability of HyspIRI. Two key objectives are: (1) The global HyspIRI spectroscopic measurements of the terrestrial biosphere including vegetation composition and function to constrain and reduce the uncertainty in climate-carbon interactions and terrestrial biosphere feedback. (2) The global 8 band thermal measurements to provide improved constraint of fire related emissions. In this paper the current HyspIRI mission concept that has been reviewed and refined to its current level of maturity with a Data Products Symposium, Science Workshop and NASA HWorkshop is presented including traceability between the measurements and the science and science application objectives.

Green, Robert O.↗

NASA NTRS2018

Commercial Off-The-Shelf GPU Qualification for Space Applications

With increased sensor data rates, and limited downlink capability, NASA missions have increased demands for onboard processing for applications ranging from synthetic aperture radar (SAR) data reduction to hyperspectral image processing and recognition, and even artificial intelligence (AI). Graphics Processor Units (GPUs) offer an attractive processing architecture for many of the applications due to their massive parallelism. As no radiation hardened GPU devices currently exist, any near term GPU-based onboard processors must use commercially available devices. To address this need NASA GSFC is collaborating with Cubic Aerospace Incorporated to, (a) characterize the capability of GPUs to meet the demands of a candidate onboard processing application, thereby demonstrating their ability to improve mission performance, reduce spacecraft SWaP, and potentially enable new missions, and (b) evaluate the radiation tolerance of capable COTS GPU devices to determine their suitability for spaceflight applications and understand any mitigations that are needed. A candidate onboard processing image has been prototyped and evaluated on a commercial GPU board and has demonstrated significantly increased processing throughput. Radiation tests for commercial GPU devices are planned for early fiscal year 2019.

Onboard processing↗