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NASA NTRS2017

Monitoring Land Surface Albedo and Vegetation Dynamics Using High Spatial and Temporal Resolution Synthetic Time Series from Landsat and the MODIS BRDF/NBAR/Albedo Product

Seasonal vegetation phenology can significantly alter surface albedo which in turn affects the global energy balance and the albedo warmingcooling feedbacks that impact climate change. To monitor and quantify the surface dynamics of heterogeneous landscapes, high temporal and spatial resolution synthetic time series of albedo and the enhanced vegetation index (EVI) were generated from the 500-meter Moderate Resolution Imaging Spectroradiometer (MODIS) operational Collection V006 daily BRDF (Bidirectional Reflectance Distribution Function) / NBAR (Nadir BRDF-Adjusted Reflectance) / albedo products and 30-meter Landsat 5 albedo and near-nadir reflectance data through the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The traditional Landsat Albedo (Shuai et al., 2011) makes use of the MODIS BRDFAlbedo products (MCD43) by assigning appropriate BRDFs from coincident MODIS products to each Landsat image to generate a 30-meter Landsat albedo product for that acquisition date. The available cloud free Landsat 5 albedos (due to clouds, generated every 16 days at best) were used in conjunction with the daily MODIS albedos to determine the appropriate 30-meter albedos for the intervening daily time steps in this study. These enhanced daily 30-meter spatial resolution synthetic time series were then used to track albedo and vegetation phenology dynamics over three Ameriflux tower sites (Harvard Forest in 2007, Santa Rita in 2011 and Walker Branch in 2005). These Ameriflux sites were chosen as they are all quite nearby new towers coming on line for the National Ecological Observatory Network (NEON), and thus represent locations which will be served by spatially paired albedo measures in the near future. The availability of data from the NEON towers will greatly expand the sources of tower albedometer data available for evaluation of satellite products. At these three Ameriflux tower sites the synthetic time series of broadband shortwave albedos were evaluated using the tower albedo measurements with a Root Mean Square Error (RMSE) less than 0.013 and a bias within the range of 0.006. These synthetic time series provide much greater spatial detail than the 500 meter gridded MODIS data, especially over more heterogeneous surfaces, which improves the efforts to characterize and monitor the spatial variation across species and communities. The mean of the difference between maximum and minimum synthetic time series of albedo within the MODIS pixels over a subset of satellite data of Harvard Forest (16 kilometers by 14 kilometers) was as high as 0.2 during the snow-covered period and reduced to around 0.1 during the snow-free period. Similarly, we have used STARFM to also couple MODIS Nadir BRDF-Adjusted Reflectances (NBAR) values with Landsat 5 reflectances to generate daily synthetic times series of NBAR and thus Enhanced Vegetation Index (NBAR-EVI) at a 30-meter resolution. While normally STARFM is used with directional reflectances, the use of the view angle corrected daily MODIS NBAR values will provide more consistent time series. These synthetic times series of EVI are shown to capture seasonal vegetation dynamics with finer spatial and temporal details, especially over heterogeneous land surfaces.

Vegetation Index↗

NASA NTRS2013

Daily MODIS 500 m Reflectance Anisotropy Direct Broadcast (DB) Products for Monitoring Vegetation Phenology Dynamics

Land surface vegetation phenology is an efficient bio-indicator for monitoring ecosystem variation in response to changes in climatic factors. The primary objective of the current article is to examine the utility of the daily MODIS 500 m reflectance anisotropy direct broadcast (DB) product for monitoring the evolution of vegetation phenological trends over selected crop, orchard, and forest regions. Although numerous model-fitted satellite data have been widely used to assess the spatio-temporal distribution of land surface phenological patterns to understand phenological process and phenomena, current efforts to investigate the details of phenological trends, especially for natural phenological variations that occur on short time scales, are less well served by remote sensing challenges and lack of anisotropy correction in satellite data sources. The daily MODIS 500 m reflectance anisotropy product is employed to retrieve daily vegetation indices (VI) of a 1 year period for an almond orchard in California and for a winter wheat field in northeast China, as well as a 2 year period for a deciduous forest region in New Hampshire, USA. Compared with the ground records from these regions, the VI trajectories derived from the cloud-free and atmospherically corrected MODIS Nadir BRDF (bidirectional reflectance distribution function) adjusted reflectance (NBAR) capture not only the detailed footprint and principal attributes of the phenological events (such as flowering and blooming) but also the substantial inter-annual variability. This study demonstrates the utility of the daily 500 m MODIS reflectance anisotropy DB product to provide daily VI for monitoring and detecting changes of the natural vegetation phenology as exemplified by study regions comprising winter wheat, almond trees, and deciduous forest.

Vegetation↗

NASA NTRS1999

Quantifying BRDF Effects in Comparing Landsat-7 and AVIRIS Near-Simultaneous Acquisitions for Studies of High Plains Vegetation Cover

Approximately 100,000 sq. km of the High Plains of the central United States are covered by sand dunes and sand sheets deposited during the Holocene. Soil-dating evidence shows that there were at least four periods of dune reactivation during major droughts in the last 10,000 years. The dunes in this region are anchored by vegetation. We have undertaken a study of land-use change in the High Plains from 1985 to the present using Landsat 5 TM and Landsat 7 ETM+ images to map variation in vegetation cover during wet and dry years. Mapping vegetation cover of less than 20% is important in modeling potential surface reactivation since at this level the vegetation no longer sufficiently shields sandy surfaces from movement by wind. Landsat TM data have both the spatial resolution and temporal coverage to facilitate vegetation cover analysis for model development and verification. However, there is still the question of how accurate TM data are for the measurement of both growing and senescent vegetation in and and semi-arid regions. AVIRIS provides both high spectral resolution as well as high signal-to-noise ratio and can be used to test the accuracy of Landsat TM and ETM+ data. We have analyzed data from AVIRIS flown nearly concurrently with a Landsat 7 overpass. The comparison between an AVIRIS image swath of 11 km width subtending a 30 deg. angle and the same area covered by a 0.8 deg. angle from Landsat required accounting for the BRDF. A normalization technique using the ratio of the reflectances from registered AVIRIS and Landsat data proved superior to the techniques of column averaging on AVIRIS data alone published previously by Kennedy et al. This technique can be applied to aircraft data covering a wider swath angle than AVIRIS to develop BRDF responses for a wide variety of surfaces more efficiently than from ground measurements.

Goetz, A. F. H.↗

NASA NTRS2012

Initial On-Orbit Radiometric Calibration of the Suomi NPP VIIRS Reflective Solar Bands

The on-orbit radiometric response calibration of the VISible/Near InfraRed (VISNIR) and the Short-Wave InfraRed (SWIR) bands of the Visible/Infrared Imager/Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (NPP) satellite is carried out through a Solar Diffuser (SD). The transmittance of the SD screen and the SD's Bidirectional Reflectance Distribution Function (BRDF) are measured before launch and tabulated, allowing the VIIRS sensor aperture spectral radiance to be accurately determined. The radiometric response of a detector is described by a quadratic polynomial of the detector?s digital number (dn). The coefficients were determined before launch. Once on orbit, the coefficients are assumed to change by a common factor: the F-factor. The radiance scattered from the SD allows the determination of the F-factor. In this Proceeding, we describe the methodology and the associated algorithms in the determination of the F-factors and discuss the results.

Lei, Ning↗

NASA NTRSDate not supplied

Development of the GeoNEX Level 2G Products: Exploiting the Diurnal Variability of TOA Reflectance in Atmospheric Correction

This study develops a new atmospheric correction algorithm to generate the Level 2G products, in particular the gap-filled Surface Reflectance at 10-minute time steps, for the Geostationary-NASA Earth Exchange (GeoNEX) project. The algorithm is based on the MODIS MAIAC (Multi-Angle Implementation of Atmospheric Correction) framework but with significant modifications to exploit angular/temporal information from the diurnal variability of the GeoNEX L1G TOA (Top-of-Atmosphere) reflectance. The algorithm starts by evaluating the roughness/smoothness of the diurnal time series of the TOA reflectance. Because rapid changes in TOA reflectance are generally caused by passing clouds or shadows, rough segments of the time series are automatically filtered out while the smooth segments are further tested for brightness and temperature to identify clear-sky and snow-free observations. Next the algorithm runs the MAIAC RTM (Radiative Transfer Model) to retrieve the Ross-Thick-Li-Sparse (RTLS) BRDF model parameters and the daily-mean atmospheric optical depth (AOD) that allow the RTM to optimally simulate the observed diurnal variability of clear-sky TOA reflectance. Once the initial RTLS parameters are retrieved after the algorithm’s burn-in period, they are used as the prior information to predict the AOD level for the next days, while the subsequent clear-sky observations are used to make necessary adjustments to the RTLS parameters in an continuous fashion. This “prediction-analysis” cycle is then iterated to process the full time series of the L1G data, skipping only total-cloudy days or when surface snow is detected. We tested the algorithm over a list of selected AERONET sites. The retrieved results (the daily mean AOD and the RTLS parameters) reasonably agree with the ground-based measurements. Importantly, the results indicate that the diurnal cycles of surface reflectance are continuous functions of the illumination-view geometry. Thus we can use the retrieved RTLS model to accurately fill in data gaps on partial cloudy days. Also, our algorithm is totally independent from the traditional approaches based on the use of spectral band ratios between the shortwave infrared (e.g., 2.2µm) and the visible (e.g., 0.47µm and 0.64µm) bands. Our results thus demonstrate that the high-frequent diurnal geostationary observations contain unique information that helps us improve atmospheric correction of remote sensing data.

GeoNEX↗

NASA NTRS1988

The spectral bidirectional reflectance of snow

A radiative transfer model for the bidirectional reflectance-distribution function (BRDF) shows that snow is moderately anisotropic in the near-infrared wavelengths. Although the directional-hemispherical albedo of snow decreases as the grains become larger, the forward scattering also increases, with the result that the illumination and viewing geometry must be considered when interpreting physical properties of the surface layer of the snow pack from remote sensing data. Measurements of the BRDF for a variety of snow conditions were made throughout the winter and spring seasons with a spectroradiometer, for wavelengths from 0.38 to 1.11 microns. Coincident with these the surface grain properties were analyzed by stereological methods. The data show that Mie scattering calculations using an equivalent spherical radius match the directional-hemispherical reflectance, but the BRDF usually shows a small peak in the backscattered direction that would not occur from spherical grains. The sphere with the same surface-to-volume ratio as the ice grains is used as the equivalent sphere.

Dozier, J.↗

NASA NTRS2024

Assessing Mechanical Properties of Spacecraft Materials under Simulated Low Earth Orbit Atomic Oxygen Conditions

During a space mission, spacecraft surface materials are exposed to various damaging environmental factors including high-energy photons, electrons, atomic oxygen (AO) neutrals and ions, micrometeoroids and orbital debris, vacuum, and large temperature fluctuations. The resulting change in spacecraft material properties can significantly impact the performance and durability of spacecraft systems. Even though all aspects of the space environment can lead to the deterioration of spacecraft components, in low Earth orbit (LEO), the threat posed by AO is especially severe in terms of structural and optical damage, particularly to exterior spacecraft components that are susceptible to oxidation. A comprehensive understanding of material AO-induced weathering is essential for mission planning in the LEO environment. The presented work aims to evaluate the alterations in mechanical properties of selected innovative spacecraft materials and surface electronic system designs, such as Kapton® CR film coated front and back-side with polyimide coating containing AO-resistant filler, Kevlar EXO, and Bendable Electrodynamic Dust Shield (BEDS) architecture, under simulated AO exposure, utilizing the photoelasticity phenomenon in which birefringence is induced in a material when it is subjected to mechanical stress. Changes in stress patterns during the deformation of AO-exposed polymers were assessed using a large-field polariscope under varied deformation types. Patterns of colors were used for qualitative evaluations of residual stress. The stress patterns of the AO-exposed polymers were compared to those of the unexposed ones. Also, these patterns were correlated with data from Bidirectional Reflectance Distribution Function (BRDF) and surface morphology studies.

Yuliya Kuznetsova↗

NASA NTRS1993

Volume 14: The first SeaWiFS intercalibration round-robin experiment, SIRREX-1, July 1992

The results of the first Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Intercalibration Round-Robin Experiment (SIRREX-1), which was held at the Center for Hydro-Optics and Remote Sensing (CHORS) at San Diego State University (SDSU) on 27-31 July 1992 are presetend. Oceanographic radiometers to be used in the SeaWiFS Calibration and Validation Program will be calibrated by individuals from the National Aeronautics and Space Administration's (NASA's) Goddard Space Flight Center (GSFC), CHORS, and seven other laboratories. The purpose of the SIRREX experiments is to assure the radiometric standards used in all of these laboratories are referenced to the same scales of spectral irradiance and radiance, which will be maintained by GSFC and periodically recalibrated by the National Institute of Standards and Technology (NIST). The spectral irradiance scale of GSFC's FEL lamp number F269 (recalibrated by NIST in October 1992) was transferred to lamps belonging to the 9 participating laboratories; l set of lamp transfer measurements (involving 4 of the lamps) was precise to within less than 1 percent and meets SeaWiFS goals, but a second set (involving another 14 lamps) did not. The spectral radiance scale of the GSFC 40-inch integrating sphere source was transferred to integrating sphere radiance sources belonging to four of the other laboratories. Reflectance plaques, used for irradiance-to-radiance transfer by five of the laboratories, were compared, but spectral bidirectional reflectance distribution functions (BRDF's) were not determined quantitatively. Also reported are results of similar comparisons (in October 1992) between the GSFC scales of spectral irradiance and radiance and those used by the Hughes/Santa Barbara Research Center (SBRC) to calibrate and characterize the SeaWiFS instrument. This first set of intercalibration round-robin experiments was a valuable learning experience for all participants, and led to several important procedural changes, which will be implemented in the second SIRREX, to be held at CHORS in June 1993.

Mueller, James L.↗

NASA NTRS2016

Consistency of Vegetation Index Seasonality Across the Amazon Rainforest

Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in VIs seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between VIs, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing.

MAIAC↗

NASA NTRS2021

Quantifying Uncertainties in Nighttime Light Retrievals From Suomi-NPP and NOAA-20 VIIRS Day/Night Band Data

Satellite observations of nighttime lights (NTL) from Suomi-NPP and NOAA-20 VIIRS Day/Night Band data have been widely used to estimate human activities. Long-term changes such as urban development and abrupt short-term changes such as power outages have been monitored from temporal NTL acquired by satellites. While high temporal NTL variation has been found across NTL data of varying temporal scale (e.g., daily, monthly, and annual composites), the sources of measurement error and uncertainty are poorly understood. This paper quantifies the sources of VIIRS-derived NTL uncertainty due to view-illumination geometry, surface Bidirectional Reflectance Distribution Function (BRDF)/albedo, and the effects of snow cover, lunar irradiance, aerosol loading, cloud mask, vegetation, geometry, and ephemeral artifacts (e.g., the Aurora Borealis). Based on this current assessment of NASA Black Marble retrievals (VNP46, Collection V001), we found that angular and atmospheric effects dominate retrieval uncertainty. Errors introduced by upstream data inputs (e.g., a coarser nighttime snow cover flag and misclassification errors in the existing VIIRS nighttime cloud mask) were also found to impact retrieval quality. Despite these challenges, a consistent daily NTL time series record can be routinely generated from top-of-atmosphere VNP46 radiances. Key recommendations include: (1) the use of lunar-BRDF adjusted and atmospherically corrected NTL (i.e., as identified as high-quality retrievals in the VNP46 QA fields), (2) development and improvement to the VIIRS snow cover and cloud masks algorithms to accurately reflect NTL retrieval conditions, (3) characterizing seasonal variations in NTL due to vegetation and snow, (4) reducing geometric effects due to the spatial mismatch of gridded pixel and observation footprint, (5) employing angularly-consistent NTL observations from multiple VIIRS instruments (i.e., Suomi-NPP and NOAA-20) to reduce pixel-based uncertainties and address persistent data gaps, and (6) being mindful of surface-reflected radiance from aurora events at mid-to-high latitudes.

Zhuosen Wang↗

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 NTRS2011

Clouds and Earth Radiant Energy System (CERES), a Review: Past, Present and Future

The Clouds and Earth Radiant Energy System (CERES) project s objectives are to measure the reflected solar radiance (shortwave) and Earth-emitted (longwave) radiances and from these measurements to compute the shortwave and longwave radiation fluxes at the top of the atmosphere (TOA) and the surface and radiation divergence within the atmosphere. The fluxes at TOA are to be retrieved to an accuracy of 2%. Improved bidirectional reflectance distribution functions (BRDFs) have been developed to compute the fluxes at TOA from the measured radiances with errors reduced from ERBE by a factor of two or more. Instruments aboard the Terra and Aqua spacecraft provide sampling at four local times. In order to further reduce temporal sampling errors, data are used from the geostationary meteorological satellites to account for changes of scenes between observations by the CERES radiometers. A validation protocol including in-flight calibrations and comparisons of measurements has reduced the instrument errors to less than 1%. The data are processed through three editions. The first edition provides a timely flow of data to investigators and the third edition provides data products as accurate as possible with resources available. A suite of cloud properties retrieved from the MODerate-resolution Imaging Spectroradiometer (MODIS) by the CERES team is used to identify the cloud properties for each pixel in order to select the BRDF for each pixel so as to compute radiation fluxes from radiances. Also, the cloud information is used to compute radiation at the surface and through the atmosphere and to facilitate study of the relationship between clouds and the radiation budget. The data products from CERES include, in addition to the reflected solar radiation and Earth emitted radiation fluxes at TOA, the upward and downward shortwave and longwave radiation fluxes at the surface and at various levels in the atmosphere. Also at the surface the photosynthetically active radiation and ultraviolet radiation (total, UVA and UVB) are computed. The CERES instruments aboard the Terra and Aqua spacecraft have served well past their design life times. A CERES instrument has been integrated onto the NPP platform and is ready for launch in 2011. Another CERES instrument is being built for launch in 2014, and plans are being made for a series of follow-on missions.

Smith, G. L.↗

NASA NTRS2009

Enhancement of the MODIS Daily Snow Albedo Product

The MODIS daily snow albedo product is a data layer in the MOD10A1 snow-cover product that includes snow-covered area and fractional snow cover as well as quality information and other metadata. It was developed to augment the MODIS BRDF/Albedo algorithm (MCD43) that provides 16-day maps of albedo globally at 500-m resolution. But many modelers require daily snow albedo, especially during the snowmelt season when the snow albedo is changing rapidly. Many models have an unrealistic snow albedo feedback in both estimated albedo and change in albedo over the seasonal cycle context, Rapid changes in snow cover extent or brightness challenge the MCD43 algorithm; over a 16-day period, MCD43 determines whether the majority of clear observations was snow-covered or snow-free then only calculates albedo for the majority condition. Thus changes in snow albedo and snow cover are not portrayed accurately during times of rapid change, therefore the current MCD43 product is not ideal for snow work. The MODIS daily snow albedo from the MOD10 product provides more frequent, though less robust maps for pixels defined as "snow" by the MODIS snow-cover algorithm. Though useful, the daily snow albedo product can be improved using a daily version of the MCD43 product as described in this paper. There are important limitations to the MOD10A1 daily snow albedo product, some of which can be mitigated. Utilizing the appropriate per-pixel Bidirectional Reflectance Distribution Functions (BRDFs) can be problematic, and correction for anisotropic scattering must be included. The BRDF describes how the reflectance varies with view and illumination geometry. Also, narrow-to-broadband conversion specific for snow on different surfaces must be calculated and this can be difficult. In consideration of these limitations of MOD10A1, we are planning to improve the daily snow albedo algorithm by coupling the periodic per-pixel snow albedo from MCD43, with daily surface ref|outanoom, In this paper, we compare a daily version of MCD43B3 with the daily albedo from MOD10A1. and MCD43B3 with a 16-day average of MOD10A1, over Greenland. We also discuss some near-future planned enhancements to MOD10A1.

Hall, Dorothy K.↗

NASA NTRS2016

Using Ground Targets to Validate S-NPP VIIRS Day-Night Band Calibration

In this study, the observations from S-NPP VIIRS Day-Night band (DNB) and Moderate resolution bands (M bands) of Libya 4 and Dome C over the first four years of the mission are used to assess the DNB low gain calibration stability. The Sensor Data Records produced by NASA Land Product Evaluation and Algorithm Testing Element (PEATE) are acquired from nearly nadir overpasses for Libya 4 desert and Dome C snow surfaces. A kernel-driven bidirectional reflectance distribution function (BRDF) correction model is used for both Libya 4 and Dome C sites to correct the surface BRDF influence. At both sites, the simulated top-of-atmosphere (TOA) DNB reflectances based on SCIAMACHY spectral data are compared with Land PEATE TOA reflectances based on modulated Relative Spectral Response (RSR). In the Libya 4 site, the results indicate a decrease of 1.03% in Land PEATE TOA reflectance and a decrease of 1.01% in SCIAMACHY derived TOA reflectance over the period from April 2012 to January 2016. In the Dome C site, the decreases are 0.29% and 0.14%, respectively. The consistency between SCIAMACHY and Land PEATE data trends is good. The small difference between SCIAMACHY and Land PEATE derived TOA reflectances could be caused by changes in the surface targets, atmosphere status, and on-orbit calibration. The reflectances and radiances of Land PEATE DNB are also compared with matching M bands and the integral M bands based on M4, M5, and M7. The fitting trends of the DNB to integral M bands ratios indicate a 0.75% decrease at the Libya 4 site and a 1.89% decrease at the Dome C site. Part of the difference is due to an insufficient number of sampled bands available within the DNB wavelength range. The above results indicate that the Land PEATE VIIRS DNB product is accurate and stable. The methods used in this study can be used on other satellite instruments to provide quantitative assessments for calibration stability.

Chen, Xuexia↗

NASA NTRS2002

Airborne Spectral Measurements of Ocean Anisotropy during CLAMS

The Cloud Absorption Radiometer (CAR) aboard the University of Washington Convair CV-580 research aircraft obtained bidirectional reflectance-distribution function (BRDF) of Atlantic Ocean and Dismal Swamp between July 10 and August 2, 2001. The BRDF measurements (15 in total, 8 uncontaminated by clouds) obtained under a variety of sun angles and wind conditions, will be used to characterize ocean anisotropy in support of Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) science objectives principally to validate products from NASA's EOS satellites, and to parameterize and validate BRDF models of the ocean. In this paper we present results of BRDF of the Ocean under different sun angles and wind conditions. The CAR is capable of measuring scattered light in fourteen spectral bands. The scan mirror, rotating at 100 rpm, directs the light into a Dall-Kirkham telescope where the beam is split into nine paths. Eight light beams pass through beam splitters, dichroics, and lenses to individual detectors (0.34-1.27 micron), and finally are registered by eight data channels. They are sampled simultaneously and continuously. The ninth beam passes through a spinning filter wheel to an InSb detector cooled by a Stirling cycle cooler. Signals registered by the ninth data channel are selected from among six spectral channels (1.55-2.30 micron). The filter wheel can either cycle through all six spectral bands at a prescribed interval (usually changing filter every fifth scan line), or lock onto any one of the six spectral bands and sample it continuously. To measure the BRF of the surface-atmosphere system, the University of Washington CV-580 had to fly in a circle about 3 km in diameter above the surface for roughly two minutes. Replicated observations (multiple circular orbits) were acquired over selected surfaces so that average BRF smooth out small-scale surface and atmospheric inhomogeneities. At an altitude of 600 m above the targeted surface area and with a 1 degree IFOV, the pixel resolution is about 10 m at nadir and about 270 m at an 80 deg. viewing angle from the CAR.

Gatebe, C. K.↗

NASA NTRSDate not supplied

Ground Testing of the MISSE-16 Materials

The harsh space environment imposes very stringent requirements upon spacecraft materials, especially those located on exterior surfaces of space objects in low Earth orbit (LEO). As humankind moves from space exploration to space commercialization, these materials may have to last for 15–20 years without considerable degradation of their optical, electrical, mechanical, and thermal properties. Operational requirements dictate that these materials continue to function according to expectations. Hence, we must understand the effects of the space environment on materials currently in use as well as on untested materials. For the years, the Materials International Space Station Experiment Flight Facility (MISSE-FF) have flown many different materials to investigate the effect of LEO space weather exposure on the performance and durability of materials and devices. The MISSE-16 scientific team members plan to launch fifteen different novel and well-characterized spacecraft-relevant materials to the LEO environment for a duration of six months during the MISSE-16 mission. Changes in spectral reflectivity will be measured throughout the mission as the samples are exposed to the space environment. The same chemical damage the produces changes in optical reflectance also causes changes in numerous other physical properties such as electrical conductivity, mechanical strength, and chemical reactivity. Correlation of the changes in each of these properties as a function of radiation type, flux, and fluence allows various material properties to be inferred from one experimentally tractable measurement: color change. Flying identical test fixtures on the ram, zenith, and wake positions of the MISSE-FF, collecting spectrally resolved images of the materials, and concomitantly measuring the ambient space environment allows deconvolution of the material effects which occur as a result of exposure to neutral atomic oxygen (AO), unfiltered solar ultraviolet (UV) radiation, and electrons. The flight experiment will function as a ground truth reference for our team’s ongoing laboratory-based space weather-material interactions experiments. Comparison of the MISSE-16 data with extensive testing of “flight-duplicate” samples under simulated space weather conditions will enable development of chemical models for prediction of material degradation. This paper discusses preliminary results from the ground test campaign including measurements of UV/VIS/IR reflectance spectra, bidirectional reflectance distribution function (BRDF), surface potential decay, and surface morphology under electron and AO exposure.

Elena A. Plis↗

NASA NTRS2019

Assessment of VIIRS on-orbit polarization sensitivity and its impact on CLARREO pathfinder inter-calibration

The primary objective of the CLARREO Pathfinder (CPF) mission is to demonstrate essential measurement technologies to enable highly accurate decadal change observations traceable on-orbit to SI standards. Another important objective of the CPF is to demonstrate inter-calibration with the VIIRS sensor and to show that such high-accuracy reference inter-calibration is achievable. To satisfy this requirement, it is important to understand and quantify uncertainties in VIIRS sensor measurements. Based on prelaunch test results, the reflective solar bands of both SNPP and NOAA-20 VIIRS have exhibited polarization sensitivities in the shortest wavelength bands, with an unexpectedly larger sensitivity observed for NOAA-20 VIIRS, particularly in bands M1 to M4. In this study, we use VIIRS Level-1B reflectance data collected over the Pseudo-Invariant Calibration Sites over North African desert region to examine the polarization associated uncertainty for these four bands. Impact due to BRDF on the reflectance data is considered by comparing baseline results obtained from the same viewing and solar zenith angles under relatively low polarization sensitivity. Impact due to detector relative difference in polarization sensitivity is examined by normalizing reflectances by the value of the middle detector. Results of this study provide useful information on VIIRS uncertainty contribution due to polarization when conducting CPF and VIIRS inter-calibration.

VIIRS↗

NASA NTRS2018

MODIS Collection 6 MAIAC Algorithm

This paper describes the latest version of the algorithm MAIAC (Multi-Angle Implementation of Atmospheric Correction) used for processing the MODIS (Moderate-resolution Imaging Spectroradiometer) Collection6 data record. Since initial publication in 2011-2012, MAIAC has changed considerably to adapt to global processing and improve cloud/snow detection, aerosol retrievals and atmospheric correction of MODIS data. The main changes include (1) transition from a 25 to 1 km scale for retrieval of the spectral regression coefficient (SRC) which helped to remove occasional blockiness at 25 km scale in the aerosol optical depth (AOD) and in the surface reflectance, (2) continuous improvements of cloud detection, (3) introduction of smoke and dust tests to discriminate absorbing fine- and coarse mode aerosols, (4) adding over-water processing, (5) general optimization of the LUT (LookUp-Table)-based radiative transfer for the global processing, and others. MAIAC provides an interdisciplinary suite of atmospheric and land products, including cloud mask (CM), column water vapor (CWV), AOD at 0.47 and 0.55 m, aerosol type (background, smoke or dust) and fine-mode fraction over water; spectral bidirectional reflectance factors (BRF), parameters of Ross-thick Lisparse (RTLS) bidirectional reflectance distribution function (BRDF) model and instantaneous albedo. For snow-covered surfaces, we provide subpixel snow fraction and snow grain size. All products come in standard HDF4 (software library) format at 1 km resolution, except for BRF, which is also provided at 500 m resolution on a sinusoidal grid adopted by the MODIS Land team. All products are provided on per-observation basis in daily files except for the BRDF/Albedo product, which is reported every 8 days. Because MAIAC uses a time series approach, BRDF/Albedo is naturally gap-filled over land where missing values are filled-in with results from the previous retrieval. While the BRDF model is reported for MODIS Land bands 1-7 and ocean band 8, BRF is reported for both land and ocean bands 1-12. This paper focuses on MAIAC cloud detection, aerosol retrievals and atmospheric correction and describes MCD19 data products and quality assurance (QA) flags.

MAIAC Algorithm↗