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NASA NTRS2021

Positional Dependence of SNPP VIIRS Solar Diffuser BRDF Change Factor: An Empirical Approach

The Earth-observing Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership satellite regularly performs on-orbit radiometric calibration of its reflective solar bands (RSBs), primarily through observations of an onboard sunlit solar diffuser (SD). The on-orbit change of the SD bidirectional reflectance distribution function (BRDF) value, quantified by a numerical factor called the H-factor, is determined by the onboard SD stability monitor. Our previous study showed that the H-factor is solar angle and view direction dependent. In this study, we determine the dependence of the H-factor on the detector SD view footprint location. We fit an empirical model to the NASA Collection 1 SNPP VIIRS Level 1B (L1B) spectral reflectance difference across the detectors in an RSB over uniform Earth scenes of the Libya 4 desert and deep convective clouds. We apply the model predicted SD positional dependent H-factor to calibrate the RSBs. Under this new calibration scheme, the original unreal striping is removed from the homogeneous Libya 4 desert and the deep convective cloud images, as well as the original unreal striping from the Dunhuang desert image. The SD positional dependent H-factor has been used to calculate the SNPP VIIRS RSB radiometric correction factor for the NASA Collection 2.0 SNPP VIIRS L1B products.

SNPP VIIRS↗

NASA NTRS2020

N20 VIIRS RSB Calibration Algorithms and Results: Collection 2.0

The NOAA-20 (N20) satellite, previously the Joint Polar Satellite System-1 satellite, was launched on November 18, 2017. One of the five major scientific instruments aboard the satellite is the Visible Infrared Imaging Radiometer Suite (VIIRS). VIIRS scans the Earth’s surface in 22 spectral bands, 14 of which are the reflective solar bands (RSBs) with band center wavelengths from 0.412 to 2.25μm. VIIRS regularly performs on-orbit radiometric calibration of its RSBs, primarily through the observations of the onboard solar diffuser (SD). The on-orbit change of the SD’s bidirectional reflectance distribution function, known as the H-factor, is determined by the onboard SD stability monitor (SDSM). Since the H-factor exhibits angular dependence, obtaining the H-factor along the SD to the telescope direction is a challenge for the NOAA-20 VIIRS. Recently, Collection 2.0 of the NASA Land Science Investigator-led Processing Systems (SIPS) products were released. As a part of this reprocessing effort, we made two major improvements in the N20 VIIRS RSB radiometric calibration. One is the improved SD and SDSM attenuation screen transmittance functions, obtained by using calibration data collected during both the yaw maneuver and a small portion of regular orbits, resulting in a higher quality H-factor for the SDSM view. Another is the use of the H-factor for the telescope view, derived from the H-factor for the SDSM view, by using the results for the SNPP VIIRS. In June 2019, we delivered a set of mission-long N20 VIIRS Collection 2.0 RSB radiometric calibration look-up-tables. These tables have been employed by the NASA Land SIPS group to reprocess the entire time series of the NOAA-20 VIIRS products. In this paper, we discuss the Collection 2.0 NOAA-20 VIIRS RSB calibration algorithms and results.

N20 VIIRS↗

NASA NTRS2016

Impacts of the Angular Dependence of the Solar Diffuser BRDF Degradation Factor on the SNPP VIIRS Reflective Solar Band On-Orbit Radiometric Calibration

Using an onboard sunlit solar diffuser (SD) as the primary radiance source, the visible infrared imaging radiometer suite (VIIRS) on the Suomi National Polar-orbiting Partnership satellite regularly performs radiometric calibration of its reflective solar bands (RSBs). The SD bidirectional reflectance distribution function (BRDF) value decreases over time. A numerical degradation factor is used to quantify the degradation and is determined by an onboard SD stability monitor (SDSM), which observes the sun and the sunlit SD at almost the same time. We had shown previously that the BRDF degradation factor was angle-dependent. Consequently, due to that the SDSM and the RSB view the SD at very different angles relative to both the solar and the SD surface normal vectors, directly applying the BRDF degradation factor determined by the SDSM to the VIIRS RSB calibration can result in large systematic errors. We develop a phenomenological model to calculate the BRDF degradation factor for the RSB SD view from the degradation factor for the SDSM SD view. Using the yearly undulations observed in the VIIRS detector gains for the M1-M4 bands calculated with the SD BRDF degradation factor for the SDSM SD view and the difference between the VIIRS detector gains calculated from the SD and the lunar observations, we obtain the model parameter values and thus establish the relation between the BRDF degradation factors for the RSB and the SDSM SD view directions.

Lei, Ning↗

NASA NTRS2018

Initial Investigation of the Angular Dependence of the NOAA-20 VIIRS Solar Diffuser BRDF Change Factor

The NOAA-20 (formerly the Joint Polar Satellite System-1) satellite was launched on November 18, 2017. One of the five scientific instruments aboard the NOAA-20 satellite (N20) is the Visible Infrared Imaging Radiometer Suite (VIIRS). The VIIRS scans the earth surface in 22 spectral bands, of which 14 are denoted as the reflective solar bands (RSBs) with design band central wavelengths from 412 to 2250 nm. The VIIRS regularly performs on-orbit radiometric calibration of its RSBs, primarily through observations of an onboard sunlit solar diffuser (SD). The on-orbit change of the SD bidirectional reflectance distribution function (BRDF) value, denoted as the H-factor, is determined by an onboard solar diffuser stability monitor (SDSM). We have shown that the H-factor for the SD on the VIIRS instrument on the Suomi National Polar-orbiting Partnership (SNPP) satellite is both incident and outgoing sunlight direction dependent. This angular dependence profoundly affects the on-orbit radiometric calibration process and results. Here, we give preliminary results for the angular dependence for the N20 VIIRS SD H-factor, and compare the dependence with that for the SNPP VIIRS.

radiometric calibration↗

NASA NTRS2018

Initial Determination of the NOAA-20 VIIRS Screen Transmittances with Both Yaw Maneuver and Regular on Orbit Data

One of the scientific instruments aboard the NOAA-20 satellite is the Visible Infrared Imaging Radiometer Suite (VIIRS). The VIIRS regularly performs on-orbit radiometric calibration of its reflective solar bands, primarily through observations of an onboard sunlit solar diffuser (SD). The incident sunlight passes through an attenuation screen (the SD screen) and scatters off the SD to provide a radiance source for the calibration. The on-orbit change of the SD bidirectional reflectance distribution function (BRDF), denoted as the H-factor, is determined by an onboard solar diffuser stability monitor (SDSM). The eight SDSM detectors observe the sun through another attenuation screen (the SDSM screen) and the sunlit SD almost at the same time to measures the SD BRDF change. The products of the SD screen transmittance and the BRDF at t=0 and the SDSM screen transmittance were measured prelaunch. Large undulations in the H-factor were seen when using the prelaunch screen transmittances. Fifteen on-orbit yaw maneuvers were performed to validate and to further characterize the screens. Although significantly improved, the H-factor from the yaw maneuver data determined screen transmittance still has undulations as large as about 0.7-0.8%, revealing that the angular step size of the yaw maneuvers is too large. In this paper, we add regular on-orbit data to the yaw maneuver data to further improve the relative products and the relative SDSM screen transmittance. The H-factor time series derived from the newly determined screen transmittance is much smoother than that derived from using only the yaw maneuver data and thus improves considerably the radiometric calibration accuracy.

Lei, Ning↗

NASA NTRS2019

Determination of the solar angular dependence of the NOAA-20 VIIRS solar diffuser BRDF change factor

When fully illuminated by the Sun, the solar diffuser (SD) onboard of the NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) instrument provides a radiance source to allow for radiometric calibration of the VIIRS’s reflective solar bands (RSBs). Once on-orbit, due to solar bombardment and the space environment, the SD’s bidirectional reflectance distribution function (BRDF) changes its value. The change is denoted by a factor, known as the H-factor, that is time and wavelength dependent, as well as both incident and out-going angle dependent. Here, we use regular on-orbit solar diffuser stability monitor (SDSM) data to determine the solar angular dependence for the H-factor along the SD-to-SDSM direction. We compare the dependence with that for the VIIRS on the Suomi National Polar-orbiting Partnership satellite and apply the dependence ratio to obtain the N20 VIIRS SD H-factor along the SD-telescope direction.

N20 VIIRS↗

NASA NTRS2020

Determination of the NOAA-20 VIIRS screen transmittance functions with both the yaw maneuver and regular on-orbit calibration data

The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard theNOAA-20 satellite regularly performs on-orbit radiometric calibration of its reflective solar bands (RSBs) through observations of an onboard sunlit solar diffuser (SD). The incident sunlight passes through an attenuation screen (the SD screen) and then scatters off the SD to provide a radiance source for the calibration. The on-orbit change of the SD’s bidirectional reflectance distribution function (BRDF), referred to as the H-factor, is determined by an onboard solar diffuser stability monitor (SDSM) whose eight detectors alternately observe the Sun through another attenuation screen (the SDSM screen) and the sunlit SD. The products of the SD screen transmittance and the BRDF at the mission start for both the SDSM and RSBs and the SDSM screen effective transmittance were measured prelaunch. Large unrealistic undulations in the retrieved H-factor were seen when using the prelaunch screen functions. To improve the accuracy of the retrieved H-factor, shortly after the satellite launch, 15 yaw maneuvers were performed to further characterize the screens. Although significantly improved, the H-factor derived using the screen functions determined fromthe yaw maneuver data still has large unrealistic undulations, revealing that the solar azimuth angular step size of the yaw maneuvers is too large. In this paper,we add high-quality regular on-orbitSDcalibration data to the yaw maneuver data to further improve the relative product of the SD screen effective transmittance and the BRDF at the mission start for the SDSM and the SDSM screen relative effective transmittance. The H-factor time series derived from the newly determined screen transmittance functions is much smoother than that derived from using only the yaw maneuver data and thus considerably improves the radiometric calibration accuracy.

Ning Lei↗

NASA NTRS2017

Using Neural Networks to Improve the Performance of Radiative Transfer Modeling Used for Geometry Dependent Surface Lambertian-Equivalent Reflectivity Calculations

Surface Lambertian-equivalent reflectivity (LER) is important for trace gas retrievals in the direct calculation of cloud fractions and indirect calculation of the air mass factor. Current trace gas retrievals use climatological surface LER's. Surface properties that impact the bidirectional reflectance distribution function (BRDF) as well as varying satellite viewing geometry can be important for retrieval of trace gases. Geometry Dependent LER (GLER) captures these effects with its calculation of sun normalized radiances (I/F) and can be used in current LER algorithms (Vasilkov et al. 2016). Pixel by pixel radiative transfer calculations are computationally expensive for large datasets. Modern satellite missions such as the Tropospheric Monitoring Instrument (TROPOMI) produce very large datasets as they take measurements at much higher spatial and spectral resolutions. Look up table (LUT) interpolation improves the speed of radiative transfer calculations but complexity increases for non-linear functions. Neural networks perform fast calculations and can accurately predict both non-linear and linear functions with little effort.

Geometry Dependent LER (GLER) capture↗

NASA NTRS1973

Bidirectional reflectance of zinc oxide

This investigation was undertaken to determine original and useful information about the bidirection reflectance of zinc oxide. The bidirectional reflectance will be studied for the spectra between .25-2.5 microns and the hemisphere above the specimen. The following factors will be considered: (1) surface conditions; (2) specimen preparation; (3) specimen substrate, (4) polarization; (5) depolarization; (6) wavelength; and (7) angles of incident and reflection. The bidirectional reflectance will be checked by experimentally determined angular hemispherical measurements or hemispherical measurements will be used to obtain absolute bidirectional reflectance.

Scott, R.↗

NASA NTRS1999

Constraining the Global, Cloud-Free Reflected Solar Radiation Flux (RSRF) with Earth Observing System (EOS) Instruments

Variations in the top-of-atmosphere reflected solar radiation flux, and in the factors that determine its value, are among the most important diagnostic indicators of changes in Earth's energy balance. Data from the MISR (Multi-angle Imaging SpectroRadiometer), MODIS (Moderate-resolution Imaging Spectroradiometer), SAGE-3 (Stratospheric Aerosol and Gas Experiment), and CERES (Clouds and Earth's Radiant Energy System), all of which are spacecraft instruments scheduled for launch in 1999, will each constrain pieces of the RSRF budget. Prior to launch, we are performing studies to determine the sensitivity of these instruments to key factors that influence the cloud-free RSRF: aerosol optical depth, aerosol scattering properties, and surface visible bidirectional reflectance distribution function (BRDF). We are also assessing the ability of the aggregate of instruments to constrain the overall RSRF budget under natural conditions over the globe. Consider the MISR retrieval of aerosols: according to simulations over cloud-free, calm ocean, for pure particles with natural ranges of optical depth, particle size, and indices of refraction, MISR can retrieve column aerosol optical depth for all but the darkest particles, to an uncertainty of at most 0.05 or 20%, whichever is larger, even if the particle properties are poorly known. For one common particle type, soot, constraints on the optical depth over dark ocean are very poor. The simulated measurements also allow us to distinguish spherical from non-spherical particles, to separate two to four compositional groups based on indices of refraction, and to identify three to four distinct size groups between 0. 1 and 2.0 microns characteristic radius at most latitudes. Based on these results, we expect to distinguish air masses containing different aerosol types, routinely and globally, with multiangle remote sensing data. Such results far exceed current satellite aerosol retrieval capabilities, which provide only total optical depth for assumed particle properties; the new information will complement in situ data, which give details about aerosol size and composition locally. In addition, our team is using climatologies that reflect the constraints each instrument is expected to provide, along with ERBE (Earth Radiation Budget Experiment) data and a radiative transfer code, to study overall sensitivity to RSRF, helping us prepare for similar studies with new data from the EOS-era instruments.

Kahn, Ralph↗

NASA NTRS1985

Spectral estimation of green leaf area index of oats

Green leaf area index (LAI) is a measure of vegetative growth and development and is frequently used as an input parameter in yield estimation and evapotranspiration models. Extensive destructive sampling is usually required to achieve accurate estimates of green LAI in natural situations. In this investigation, a statistical modeling approach was used to predict the green LAI of oats from bidirectional reflectance data collected with multiband radiometers. Stepwise multiple regression models based on two sets of spectral reflectance factors accounted for 73 percent and 65 percent of the variance in green LAI of oats. Exponential models of spectral data transformations of greenness, normalized difference, and near-infrared/red ratio accounted for more of the variance in green LAI than the multiple regression models.

Best, R. G.↗

NASA NTRS1985

Atmospheric and Science Complexity Effects on Surface Bidirectional Reflectance

Among the tools used in passive remote sensing of Earth resources in the visible and near-infrared spectral regions are measurements of spectral signature and bidirectional reflectance functions (BDRFs). Determination of surface properties using these observables is complicated by a number of factors, including: (1) mixing of surface components, such as soil and vegetation, (2) multiple reflections of radiation due to complex geometry, such as in crop canopies, and (3) atmospheric effects. In order to bridge the diversity in these different approaches, there is a need for a fundamental physical understanding of the influence of the various effects and a quantiative measure of their relative importance. In particular, we consider scene complexity effects using the example of reflection by vegetative surfaces. The interaction of sunlight with a crop canopy and interpretation of the spectral and angular dependence of the emergent radiation is basically a multidimensional radiative transfer problem. The complex canopy geometry, underlying soil cover, and presence of diffuse as well as collimated illumination will modify the reflectance characteristics of the canopy relative to those of the individual elements.

Diner, D. J.↗

NASA NTRS1999

Comparison Analysis Between Nevada and TSS Using a Jet Engine Exhaust Nozzle Test Rig

Thermal analysis in both simple and complex models can require calculating the propagation of radiant energy to and from multiple surfaces. This can be accomplished through simple estimation techniques or complex computationally intense computer modeling simulations. Currently there are a variety of computer analysis techniques used to simulate the propagation of radiant energy, each having advantages and disadvantages. The major objective of this effort was to compare two ray tracing radiation propagation analysis programs (NEVADA and TSS) Net Energy Verification and Determination Analyzer and Thermal Synthesizer System with experimental data. Results from a non-flowing, electrically heated test rig was used to verify the calculated radiant energy propagation from a nozzle geometry that represents an aircraft propulsion nozzle system. In general the programs produced comparable overall results, and results slightly higher then the experimental data. Upon inspection of individual radiation interchange factors, differences were evident and would have been magnified if a more radical model temperature profile was analyzed. Bidirectional reflectivity data (BRDF) was not used do to modeling limitations in TSS. For code comparison purposes, this nozzle geometry represents only one case for one set of analysis conditions. Since each computer code has advantages and disadvantages bases on scope, requirements, and desired accuracy, the usefulness of this single case study may be limiting.

Baumeister, Joseph F.↗

NASA NTRS2016

Product of the SNPP VIIRS SD Screen Transmittance and the SD BRDF (RSB) From Both Yaw Maneuver and Regular On-Orbit Data

To assure data quality, the Earth-observing Visible Infrared Imaging Radiometer Suite (VIIRS) regularly performs on-orbit radiometric calibrations of its 22 spectral bands. The primary calibration radiance source for the reflective solar bands (RSBs) is a sunlit solar diffuser (SD). During the calibration process, sunlight goes through a perforated plate (the SD screen) and then strikes the SD. The SD scattered sunlight is used for the calibration, with the spectral radiance proportional to the product of the SD screen transmittance and the SD bidirectional reflectance distribution function (BRDF). The BRDF is decomposed to the product of its value at launch and a numerical factor quantifying its change since launch. Therefore, the RSB calibration requires accurate knowledge of the product of the SD screen transmittance and the BRDF (RSB; launch time). Previously, we calculated the product with yaw maneuver data and found that the product had improved accuracy over the prelaunch one. With both yaw maneuver and regular on orbit data, we were able to improve the accuracy of the SDSM screen transmittance and the product for the solar diffuser stability monitor SD view. In this study, we use both yaw maneuver and a small portion of regular on-orbit data to determine the product for the RSB SD view.

Lei, Ning↗

NASA NTRS1975

Bidirectional plant canopy reflection models derived from the radiation transfer equation

A collection of bidirectional canopy reflection models was obtained from the solution of the radiation transfer equation for a horizontally homogeneous canopy. A phase function is derived for a collection of bidirectionally reflecting and transmitting planar elements characterized geometrically by slope and azimuth density functions. Two approaches to solving the radiation transfer equation for the canopy are presented. One approach factors the radiation transfer equation into a solvable set of three first-order linear differential equations by assuming that the radiation field within the canopy can be initially approximated by three components: uniformly diffuse downwelling, uniformly diffuse upwelling, and attenuated specular. The solution to these equations, which can be iterated to any degree of accuracy, was used to obtain overall canopy reflection from the formal solution to the radiation transfer equation. A programable solution to canopy overall bidirectional reflection is given for this approach. The special example of Lambertian leaves with constant leaf bidirectional reflection and scattering functions is considered, and a programmable solution for this example is given. The other approach to solving the radiation transfer equation, a generalized Chandrasekhar technique, is presented in the appendix.

Beeth, D. R.↗

NASA NTRS2004

Land Surface Albedo from MERIS Reflectances Using MODIS Directional Factors

MERIS Level 2 surface reflectance products are now available to the scientific community. This paper demonstrates the production of MERIS-derived surface albedo and Nadir Bidirectional Reflectance Distribution Function (BRDF) adjusted reflectances by coupling the MERIS data with MODIS BRDF products. Initial efforts rely on the specification of surface anisotropy as provided by the global MODIS BRDF product for a first guess of the shape of the BRDF and then make use all of the coincidently available, partially atmospherically corrected, cloud cleared, MERIS observations to generate MERIS-derived BRDF and surface albedo quantities for each location. Comparisons between MODIS (aerosol-corrected) and MERIS (not-yet aerosol-corrected) surface values from April and May 2003 are also presented for case studies in Spain and California as well as preliminary comparisons with field data from the Devil's Rock Surfrad/BSRN site.

Schaaf, Crystal L. B.↗

NASA NTRS1992

An overview of surface radiance and biology studies in FIFE

The use of satellite data to study and to understand energy and mass exchanges between the land surface and the atmosphere requires information about various biological processes and how various reflected or emitted spectral radiances are influenced by or manifested in these processes. To obtain such information, studies were conducted by the First ISLSCP Field Experiment (FIFE) surface radiances and biology (SRB) group using surface, near-surface, helicopter, and aircraft measurements. The two primary objectives of this group were to relate radiative fluxes to biophysical parameters and physiological processes and to assess how various management treatments affect important biological processes. This overview paper summarizes the results obtained by various SRB teams working in nine different areas: (1) measurements of bidirectional reflectance and estimation of hemispherical albedo; (2) evaluation of spatial and seasonal variability reflectance and vegetation indices; (3) determination of surface and radiational factors and their effects on vegetation indices and photosynthetically active radiation relationships; (4) use of surface temperatures to estimate sensible heat flux; (5) controls over photosynthesis and respiration at small scales; (6) soil surface CO2 fluxes and grassland carbon budget; (7) landscape variations in controls over gas exchange and energy partitioning; (8) radiometric response of prairie to management and topography; and (9) determination of nitrogen gas exchanges in a tallgrass prairie.

Blad, B. L.↗

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.↗