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NASA NTRS2017

Generating Land Surface Reflectance for the New Generation of Geostationary Satellite Sensors with the MAIAC Algorithm

The latest generation of geostationary satellite sensors, including the GOES-16/ABI and the Himawari 8/AHI, provide exciting capability to monitor land surface at very high temporal resolutions (5-15 minute intervals) and with spatial and spectral characteristics that mimic the Earth Observing System flagship MODIS. However, geostationary data feature changing sun angles at constant view geometry, which is almost reciprocal to sun-synchronous observations. Such a challenge needs to be carefully addressed before one can exploit the full potential of the new sources of data. Here we take on this challenge with Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, recently developed for accurate and globally robust applications like the MODIS Collection 6 re-processing. MAIAC first grids the top-of- atmosphere measurements to a fixed grid so that the spectral and physical signatures of each grid cell are stacked (“remembered”) over time and used to dramatically improve cloud/shadow/snow detection, which is by far the dominant error source in the remote sensing. It also exploits the changing sun-view geometry of the geostationary sensor to characterize surface BRDF with augmented angular resolution for accurate aerosol retrievals and atmospheric correction. The high temporal resolutions of the geostationary data indeed make the BRDF retrieval much simpler and more robust as compared with sun-synchronous sensors such as MODIS. As a prototype test for the geostationary-data processing pipeline on NASA Earth Exchange (GEONEX), we apply MAIAC to process 18 months of data from Himawari 8/AHI over Australia. We generate a suite of test results, including the input TOA reflectance and the output cloud mask, aerosol optical depth (AOD), and the atmospherically-corrected surface reflectance for a variety of geographic locations, terrain, and land cover types. Comparison with MODIS data indicates a general agreement between the retrieved surface reflectance products. Furthermore, the geostationary results satisfactorily capture the movement of clouds and variations in atmospheric dust/aerosol concentrations, suggesting that high quality land surface and vegetation datasets from the advanced geostationary sensors can help complement and improve the corresponding EOS products.

geostationary satellite sensors↗

NASA NTRS2019

MODIS Aqua Reflective Solar Bands Calibration for NASA's R2018 Ocean Color Products

Remote sensing ocean color products have stringent requirements on radiometric calibration stability. To address a calibration deficiency in MODIS Aqua in recent years, the NASA Ocean Biological Processing Group (OBPG) developed a new calibration for the reflective solar bands. Prior to the reprocessing of NASA's ocean color products for 2018 (R2018), the OBPG MODIS products had been based on calibration provided by the MODIS Calibration Support Team (MCST). Several modifications were made to the MCST calibration approach to improve the calibration accuracy for ocean color products. These include: 1) apply 936nm detector normalization to solar diffuser stability monitor (SDSM) data to reduce coherent noise; 2) modeling solar diffuser (SD) degradation wavelength dependency to determine SD degradation in near-infrared and shortwave infrared wavelength; 3) detector gains are computed using SD screen-closed data to better match ocean radiance levels in all bands; 4) a simple atmospheric correction is performed to reduce bidirectional reflectance distribution function (BRDF) effects in desert trends; 5) modulated relative spectral response (RSR) impact on ocean data is estimated and used to adjust the calibration coefficients. 6) smoothing is used to characterize the temporal change in calibration, and response versus scan angle (RVS) changes are characterized using 2nd order polynomials to improve spatial/temporal calibration stability. Relative to the previous R2014 ocean color products, the R2018 calibration removed the suspect late-mission global trends in blue-band water-leaving reflectance, and some anomalously large short-term variability (spikes) in the temporal trend of chlorophyll concentration. This paper will describe the OBPG calibration with a focus on the differences between the MCST and OBPG approaches.

calibration↗

NASA NTRS2019

Surface Reflectance Product from Geostationary Satellite

We have generated provisional Himawari-8 AHI surface reflectance (SR) product for land and vegetation monitoring. The Himawari-8 AHI surface reflectance product is part of our GeoNEX land products, which integrate level 2 and higher remote sensing data from a set of geostationary satellite sensors (i.e. GOES-16, -17 ABI, Himawari-8 AHI, FY4-A AGRI, and MTG-I). Adapted Multiangle Implementation of Atmospheric Correction (MAIAC) algorithm is used to process time series Himawari-8 AHI observations. Himawari-8 AHI SR provides gridded and tiled land SR in 1-km resolution with high frequency (every 10 minutes during daylight time). There are three subdatasets: 1) retrieved atmospheric properties (e.g. column water vapor at 0.86 m, aerosol optical depth at 0.47m and 0.51m); 2) spectral (AHI bands 1-6) surface reflectance, kernels of RTLS BRDF model; 3)spectral BRDF kernel weights, and extensive quality assurance flags. The evaluation results show that Himawari-8 AHI data yield much more valid pixels in a single day in the characterization of land surface, when compare to NASA flagship satellite MODIS Terra/Aqua. This observation frequency and resolution of geostationary data should allow for using continuous ecosystem monitoring in diurnal studies at continental scale. Initial evaluations indicate a stable Himawari-8 AHI land SR product.

Li, Shuang↗

NASA NTRSDate not supplied

Reflecting on Planning Models: A Challenge for Verification and Validation of Planning Systems

We discuss the opportunities for autonomous sys- tems to perform reflection on their planners by adapting the models used to build plans. We first describe model-based planning systems, a form of automated planning system driven by declarative models of the planning domain. These models include descriptions of the conditions and effects of actions on the state of the world. When planning the activities of cyber-physical systems, the command and data representation of the system must be formally abstracted to the actions and states described in the planning system model. When the execution of a plan either fails or produces unexpected outcomes, the execution trace can be abstracted and compared to the predicted state according to the planning model, producing a list of discrepancies; these discrepancies can then be used to fix the model. This provides part of a reflection capability, namely, a set of well-formed problems with the domain model, the abstractions, or both. The challenge lies in the rest of the reflection capability, namely, a set of techniques for changing the models or the abstractions. We discuss these challenges and describe some of the options for addressing them

Mission Planning↗

NASA NTRS2020

SCoBi Multilayer: A Signals of Opportunity Reflectometry Model for Multilayer Dielectric Reflections

A multilayer module is incorporated into the Signals of Opportunity (SoOp) Coherent Bistatic Scattering model (SCoBi) for determining the reflections and propagation of electric fields within a series of multilayer dielectric slabs. This module can be used in conjunction with other SCoBi components to simulate complex, bistatic simulation schemes that include features such as surface roughness, vegetation, antenna effects, and multilayer soil moisture interactions on reflected signals. This paper introduces the physics underlying the multilayer module and utilizes it to perform a simulation study of the response of SoOp-R measurements with respect to subsurface soil moisture parameters. For a frequency range of 100–2400 MHz, it is seen that the SoOp-R response to a single dielectric slab is mostly frequency insensitive; however, the SoOp-R response to multilayer dielectric slabs will vary between frequencies. The relationship between SoOp-R reflectivity and the contributing depth is visualized, and the results show that SoOp-R measurements can display sensitivity to soil moisture below the penetration depth. By simulation of simple soil moisture profiles with different wetting and drying gradients, the dielectric contrast between layers is shown to be the greatest contributing factor to subsurface soil moisture sensitivity. Overall, it is observed that different frequencies can sense different areas of a soil moisture profile, and this behavior can enable subsurface soil moisture data products from SoOp-R observations.

Dylan Boyd↗

NASA NTRS2020

Variations in color and reflectance on the surface of asteroid (101955) Bennu

Visible-wavelength color and reflectance provide information about the geologic history of planetary surfaces. Here we present multispectral images (0.44 to 0.89 micrometers) of near-Earth asteroid (101955) Bennu. The surface has variable colors overlain on a moderately blue global terrain. Two primary boulder types are distinguishable by their reflectance and texture. Space weathering of Bennu surface materials does not simply progress from red to blue (or vice versa). Instead, freshly exposed, redder surfaces initially brighten in the near-ultraviolet region (i.e., become bluer at shorter wavelengths), then brighten in the visible to near-infrared region, leading to Bennu’s moderately blue average color. Craters indicate that the time scale of these color changes is ~105 years. We attribute the reflectance and color variation to a combination of primordial heterogeneity and varying exposure ages.

D. N. DellaGiustina↗

NASA NTRSDate not supplied

MODIS Reflective Solar Band Calibration Improvements using Pseudo-Invariant Desert Targets

To provide the best science data quality, an accurate characterization of the response versus scan angle (RVS) function is critical for the MODIS reflective solar bands (RSB) on-orbit calibration. In every MODIS operational scan, the Earth’s surface, referred to here as Earth view (EV), the space view (SV) port, and the onboard calibrators are viewed via a two-sided scan mirror. The RVS is defined as the sensor’s relative response as a function the angle of incidence (AOI) to the scan mirror. Many different approaches have been developed to derive the time-dependent RVS and its look-up table (LUT) applied to MODIS Level 1B (L1B) products since calibration Collection 4. For most MODIS RSB, the on-board calibrators can reasonably track the RVS change with time. In practice, their RVS is derived using data from on-board calibrators and the EV mirror side ratio (for mirror side 2). For Terra bands 1-4, 8-10 and Aqua bands 1-4, 8-9, an enhancement has been employed in Collections 6 and 6.1 (C6/C6.1) by using Earth scene response trending from pseudo-invariant desert sites in addition to the onboard calibrators. The current C6/C6/1 RVS algorithm is focused on fitting the EV data at each AOI over time and then deriving the relative change at different AOI. The EV response trending is currently fitted with multiple segments over time. Alternatively, the EV responses can be fit first as a function of AOI before fitting temporally in order to reduce the dependence on the stability of the desert site. These pre-treatment methods on the EV data provide improvement in the derived calibration coefficients. However, evidence of insufficient calibration is still observed in the MODIS L1B reflectance data, especially in the form of differences between the mirror sides. In this paper, we review the current methodologies that utilize the EV response trends from the pseudo-invariant Libyan desert targets to supplement the gain derived from the onboard calibrators. An improvement is then proposed and investigated such that a sliding window average (SWA) is used to pre-process the raw EV data. The SWA parameters are carefully selected using trade-off studies to accurately track the Earth scene response trending in multiple cases to overcome the reflectance differences between two mirror sides. Calibration results show improvements for both Aqua and Terra MODIS RSB L1B data products. This new adjustment has been included in the recently delivered Collection 7 LUT that will be evident in the L1B products expected to be released in late 2021.

MODIS↗

NASA NTRS2021

Reflectivity, Emissivity, and Brightness from Multilayered Soil with Linearly Varying Permittivity at P- and L- bands

Passive sensing of root zone soil moisture is theoretically investigated using P and L band frequencies. The soil is considered to be a stratified medium. The reflectivity from the soil surface is found by considering the soil to be composed of a finely layered structure with layer widths that are small compared to a wavelength. A well-known transmission line algorithm is then used to compute the reflectivity at the surface. Emissivity is obtained as (1 – reflectivity). It assumed that the soil is at a constant temperature of 300o K when determining the brightness temperature. A soil moisture profile consisting of two homogeneous layers separated by a layer of linearly varying soil moisture is investigated. The study is made at an incident angle of 40O for horizontal polarization at 0.8 and 1.4 GHz. Two variations of the basic profile are considered: a transition from a layer of lesser moisture to a layer of greater moisture and the opposite. In both cases the P band signal shows greater penetration than the L band case. There is greater penetration in the transition to drier soils. In both cases the L band signals show sensitivity to only the upper surface of the soil as expected.

Ming Li↗

NASA NTRS2022

Intercalibration of the reflective solar bands of MODIS and MISR instruments on the Terra platform

As a part of NASA’s Earth Observing System (EOS), the Terra spacecraft was launched on December 18, 1999, with the goal of understanding the changes of the Earth, by examining the Earth’s hydrological, geophysical, and climatic processes. The MODIS and MISR instruments on the Terra platform, combined with their continuous operation, broad spectral coverage, and different spatial resolutions, have played an important role to achieve the goals of the EOS. Over two decades of successful operations, these multispectral imaging instruments have benefited a variety of scientific applications. Being on the same platform, the two sensors complement each other in terms of spatial coverage (and target viewing geometry) and facilitate synergistic applications using multispectral data. A consistent radiometric calibration between these sensors is a prerequisite for creating high quality science products from their observations. Both instruments underwent intensive prelaunch characterization and their on-orbit calibrations are monitored using their onboard calibrators. In this paper, we perform a calibration inter-comparison of the spectrally matching bands of the two instruments using vicarious techniques. These techniques include multiyear simultaneous views of the North African desert, North Atlantic Ocean, and Dome Concordia, therefore covering different reflectance regimes. Also included in this work are the near-simultaneous top-of-atmosphere (TOA) reflectance measurements from Railroad Valley, USA, as provided by the RadCalNet (converted to TOA), that are used as a calibration reference to compare the on-orbit observations between MODIS and MISR. Simultaneous overpasses from desert, ocean, Dome C, and RadCalNet over Railroad Valley reveal that the agreement between the four spectrally matching bands is within 3% for the time-period between 2014 and 2020. Also, observed are some long-term drifts in the TOA reflectance time-series from MISR for the red and NIR band that are expected to be corrected in a future calibration reprocess.

MODIS↗

NASA NTRSDate not supplied

Infrared Reflection Removal in Wind Tunnels using Polarization Theory

Infrared radiometry with infrared cameras allows for high spatial resolution, noncontact measurements in wind tunnel experiments and has been increasingly used to visualize flow features. Reflections from test section walls present a major challenge in collecting these measurements as it is difficult or impossible to separate them from the true model emission signal. This paper implements a method to quantitatively separate the reflections from the emission using polarization theory. Samples with a range of emissivities were tested, and in all samples the reflections were significantly reduced. This method will lead to more accurate radiometric and thermographic measurements in wind tunnel experiments.

Infrared↗

NASA NTRS2022

Southern Ocean Solar Reflection Biases in Cmip6 Models Linked to Cloud Phase and Vertical Structure Representations

Over the Southern Ocean (SO, 40˚S-70˚S), climate models have consistently underestimated solar reflection. Here we evaluate the relationship between cloud profiles, cloud phase and radiation over the SO in Coupled Model Intercomparison Project Phase 6 (CMIP6) models against Clouds and the Earth's Radiant Energy System (CERES) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). We find that the lack of solar reflection is slightly improved in CMIP6 models compared to CMIP5’s, attributable to a better representation of cloud fraction and phase. We show that clouds have a different vertical structure and radiative effect south and north of where the 0˚C isotherm meets the surface (~55˚S). Although the models capture the greater vertical extent of clouds south of 55˚S, they fail to reproduce the observed increase in solar reflection, which we pinpoint to cloud phase biases. Increasing CMIP6 supercooled liquid cloud opacity should help reduce their persistent SW biases.

Southern Ocean↗

NASA NTRSDate not supplied

Infrared Reflection Removal in Wind Tunnels using Polarization Theory

Infrared↗

NASA NTRSDate not supplied

Shortwave Reflected Energy From NISTAR and EPIC Onboard the DSCOVR Spacecraft

We produce a one-year record of Shortwave reflected energy from the Earth Polychromatic Imaging Camera. Additional hyperspectral information is provided by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the SCIAMACHY instrument. We spatially integrate our SW reflected energy for an entire EPIC disk and compare with the reflected energy from the SW Band B filtered NISTAR instrument (Electrical substitution radiometer). We also compare with the Single Scanner Footprint CERES observations.

Clark Weaver↗

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 NTRS2024

Parameterizing Spectral Surface Reflectance Relationships for the Dark Target Aerosol Algorithm Applied to A Geostationary Imager

Originally developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) in polar, sun-synchronous low-earth orbit (LEO), the Dark Target (DT) aerosol retrieval algorithm relies on the assumption of a Surface Reflectance Parameterization (SRP) over land surfaces. Specifically for vegetated and dark-soiled surfaces, values of surface reflectance in blue and red visible-wavelength bands are assumed to be nearly linearly related to each other and to the value in a shortwave infrared (SWIR) wavelength band. This SRP also includes dependencies on scattering angle and a normalized difference vegetation index computed from two SWIR bands (NDVISWIR). As the DT retrieval algorithm is being ported to new sensors to continue and expand the aerosol data record, we assess whether the MODIS-assumed SRP can be used for these sensors. Here, we specifically assess SRP for the Advanced Baseline Imager (ABI) aboard, the Geostationary Operational Environmental Satellite (GOES)-16/East (ABIE). First, we find that using MODIS-based SRP leads to higher biases and artificial diurnal signatures in aerosol optical depth (AOD)retrievals from ABIE. The primary reason appears to be that geostationary orbit (GEO) encounters an entirely different set of observation geometry than does LEO, primarily with regards to solar angles coupled with fixed view angles. Therefore, we have developed a new SRP for GEO that draws the angular shape of the surface bidirectional reflectance. We also introduce modifications to the parametrization of both red-SWIR and blue-red spectral relationships to include additional information.The revised Red-SWIR SRP includes solar zenith angle, NDVISWIR, and land-type percentage from an ancillary database. The blue-red SRP adds dependencies on the scattering angle and NDVISWIR. The new SRPs improve the AOD retrieval of ABIE in terms of overall less bias and mitigation of the overestimation around local noon. The average bias of DT AOD compared to AERONET AOD shows a reduction from 0.08 to 0.03, while the bias of local solar noon decreases from 0.12 to 0.03.The agreement between DT and AERONET AOD is established through regression slope of 1.06 and y-intercept of 0.01with correlation coefficient is0.74. By using the new SRP, the percentage of data falling within the expected error range (±0.05 + 15%) is notably risen from 54% to 78%.

Mijin Kim↗

NASA NTRS2024

Advanced Libya-4 radiometric and atmospheric characterization utilizing MODIS and VIIRS full-scan reflective solar band measurements

The NASA Clouds and the Earth's Radiant Energy System (CERES) project provides observed flux and cloud products to the climate science community. The CERES instruments, along with the MODIS and VIIRS imagers, are onboard the Terra, Aqua, NPP, and NOAA20 satellites. In order to produce seamless multi-platform integrated products, long-term sensor stability and inter-calibration are required. Inter-calibration between sensors within the same sun-synchronous orbit relies on Earth invariant targets because simultaneous nadir overpasses are not possible. To facilitate inter-calibration efforts, the CERES Imager and Geostationary Calibration Group (IGCG) has improved the Libya-4 target characterization. Improvements include full scan angle characterization to enable daily observations, clear-sky identification using individual scan angle dynamic spatial homogeneity thresholds, and atmospheric corrections. The water vapor correction was found to be effective across the full scan, whereas the ozone and aerosol corrections were less effective. The atmospheric-corrected normalized radiance temporal fluctuations are similar across scan angles, spectral bands, and between the MODIS and VIIRS imagers, suggesting that the fluctuations are a result of the natural variability of the Libya-4 surface reflectance. The Libya-4 surface variability is more than likely caused by changes in the prevailing winds that alter sand dune orientation and resulting shadows. The full-scan-imager atmosphere and angle corrected reflected solar band radiance trend standard errors are between 0.6% and 1.0%, and for near-nadir observations, are between 0.5% and 0.8%. The advanced characterization suggests that the Libya-4 short-term surface reflectance anomalies may need to be considered for imager stability monitoring and inter-calibration efforts.

Libya-4 Pseudo-invariant Calibration Site↗

NASA NTRS2023

Reflection and Timing Study of the Transient Black Hole X-Ray Binary MAXI J1803-298 with NuSTAR

The transient black hole X-ray binary MAXI J1803−298 was discovered on 2021 May 1, as it went into outburst from a quiescent state. As the source rose in flux it showed periodic absorption dips and fit the timing and spectral characteristics of a hard-state accreting black hole. We report on the results of a Target-of-Opportunity observation with NuSTAR obtained near the peak outburst flux beginning on 2021 May 13, after the source had transitioned into an intermediate state. MAXI J1803−298 is variable across the observation, which we investigate by extracting spectral and timing products separately for different levels of flux throughout the observation. Our timing analysis reveals two distinct potential quasiperiodic oscillations (QPOs) which are not harmonically related at 5.4 ± 0.2 Hz and 9.4 ± 0.3 Hz, present only during periods of lower flux. With clear relativistic reflection signatures detected in the source spectrum, we applied several different reflection models to the spectra of MAXI J1803−298. Here we report our results, utilizing high-density reflection models to constrain the disk geometry, and assess changes in the spectrum dependent on the source flux. With a standard broken power-law emissivity, we find a near-maximal spin for the black hole, and we are able to constrain the inclination of the accretion disk at 75° ± 2°, which is expected for a source that has shown periodic absorption dips. We also significantly detect a narrow absorption feature at 6.91 ± 0.06 keV with an equivalent width between 4 and 9 eV, which we interpret as the signature of a disk wind.

Benjamin M. Coughenour↗

NASA NTRS2014

Is There Spectral Variation in the Polarized Reflectance of Leaves?

The light scattered by plant canopies depends in part on the light scattering/absorbing properties of the leaves and is key to understanding the remote sensing process in the optical domain. Here we specifically looked for evidence of fine spectral detail in the polarized portion of the light reflected from the individual leaves of five species of plants measured at Brewsters angle over the wavelength range 450 to 2300nm. Our results show no strong, unambiguous evidence of narrow band spectral variation of the polarized portion of the reflectance factor.

quasi specular reflection↗