Results for “Bidirectional Reflectance Distribution Function” — Page 9

NASA NTRS2018

Toward Landsat and Sentinel-2 BRDF Normalization and Albedo Estimation: A Case Study in the Peruvian Amazon Forest

The Amazon forest has been the focus of study by the science community during the last few decades. Remote sensing data analysis is the only way to study such a large geographical extent during an extended period of time. Since the launch in 2015 of Sentinel 2 and its increase in temporal resolution through the combination with Landsat sensors, a strong emphasis has been put on exploiting these data. Though these satellites provide near nadir observations, surface reflectance time series are affected by illumination variability throughout the year. These effects can be corrected using a Bidirectional Reflectance Distribution Function (BRDF) model. Franch et al. (2014a) developed a methodology to derive Landsat surface albedo and BRDF. It is based on the BRDF parameters from the MODerate Resolution Imaging Spectroradiometer (MODIS) which are disaggregated at Landsat spatial resolution (30 m). In this work, we apply the Franch et al. (2014a) method to normalize the surface reflectance for BRDF effects using the NASA's Harmonized Landsat Sentinel-2 (HLS) product. We apply this method to the Tambopata region in Peru from 2013 to 2017 and validate it using ground-based albedometer measurements. The results show that the near infrared reflectance can increase up to 0.06 (20%) for low solar angles while the impact on the red range and the NDVI is minor (<0.01). The evaluation of the surface albedo against field measurements shows an error of 0.01.

Landsat 8↗

NASA NTRS2018

JPSS-1 VIIRS Solar Diffuser Witness Sample BRF Calibration Using a Table-Top Goniometer at NASA GSFC

In support of the prelaunch calibration of the Joint Polar Satellite System-1 (JPSS-1) Visible Infrared Imaging Radiometer Suite (VIIRS), the Bidirectional Reflectance Factor (BRF) and Bidirectional Reflectance Distribution Function (BRDF) of a VIIRS solar diffuser (SD) witness sample were determined using the table-top goniometer (TTG) located in the NASA GSFC Diffuser Calibration Laboratory (DCL). The BRF of the sample was measured for VIIRS bands in the reflected solar wavelength region from 410 nm to 2250 nm. The new TTG was developed to extend the laboratory’s BRF and BRDF measurement capability to wavelengths from 1600 to 2250 nm and specifically for the VIIRS M11 band centered at 2250 nm. We show the new features and capabilities of the new scatterometer and present the BRF and BRDF results for the incident/scatter test configuration of 0°/45° and for a set of angles representing of the VIIRS on-orbit solar diffuser calibration. The BRF and BRDF results of the SD witness were used to assist in finalizing the set of BRF values of J1 VIIRS SD to be used on-orbit. Comparison of the BRF results between the JPSS-1 VIIRS SD witness sample and the flight SD panel was made by varying different sample clocking orientations and by analyzing the ratio of BRF to total hemispherical reflectance in effort to minimize the uncertainty of the extrapolated flight BRF value at 2250 nm. Furthermore, differences between the prelaunch BRF results and those used in the VIIRS on-orbit BRF lookup table were examined to improve the VIIRS BRF calibration for future missions.

Zeng, Jinan↗

NASA NTRS2018

JPSS-1 VIIRS Solar Diffuser Witness Sample BRF Calibration Using a Table-Top Goniometer at NASA GSFC

In support of the prelaunch calibration of the Joint Polar Satellite System-1 (JPSS-1) Visible Infrared Imaging Radiometer Suite (VIIRS), the Bidirectional Reflectance Factor (BRF) and Bidirectional Reflectance Distribution Function (BRDF) of a VIIRS solar diffuser (SD) witness sample were determined using the table-top goniometer (TTG) located in the NASA GSFC Diffuser Calibration Laboratory (DCL). The BRF of the sample was measured for VIIRS bands in the reflected solar wavelength region from 410 nm to 2250 nm. The new TTG was developed to extend the laboratory’s BRF and BRDF measurement capability to wavelengths from 1600 to 2250 nm and specifically for the VIIRS M11 band centered at 2250 nm. We show the new features and capabilities of the new scatterometer and present the BRF and BRDF results for the incident/scatter test configuration of 0°/45° and for a set of angles representing of the VIIRS on-orbit solar diffuser calibration. The BRF and BRDF results of the SD witness were used to assist in finalizing the set of BRF values of J1 VIIRS SD to be used on-orbit. Comparison of the BRF results between the JPSS-1 VIIRS SD witness sample and the flight SD panel was made by varying different sample clocking orientations and by analyzing the ratio of BRF to total hemispherical reflectance in effort to minimize the uncertainty of the extrapolated flight BRF value at 2250 nm. Furthermore, differences between the prelaunch BRF results and those used in the VIIRS on-orbit BRF lookup table were examined to improve the VIIRS BRF calibration for future missions.

Zeng, Jinan↗

NASA NTRS2018

Harmonized Landsat/Sentinel-2 Products for Land Monitoring

The Harmonized Landsat-8 and Sentinel-2 (HLS) project is a NASA initiative aiming to produce a seamless, harmonized surface reflectance record from the Operational Land Imager (OLI) and Multi-Spectral Instrument (MSI) aboard Landsat-8 and Sentinel-2 remote sensing satellites, respectively. The HLS products are based on a set of algorithms to obtain seamless products from both sensors (OLI and MSI): atmospheric correction, cloud and cloud-shadow masking, geographic co-registration and common gridding, bidirectional reflectance distribution function normalization and bandpass adjustment. As of version 1.3, the HLS v1.3 data set covers 9.12 million km2 and spans from first Landsat-8 data (2013) to present. HLS products provide near-daily surface reflectance information with a common geometric framework, and are suitable for a variety of agricultural and vegetation monitoring tasks, including analysis of crop type, condition, and phenology.

Masek, Jeffrey↗

NASA NTRS2019

Improving the AVHRR Long Term Data Record BRDF Correction

The Long Term Data Record (LTDR) project has the goal of developing a quality and consistent surface reflectance product from coarse resolution optical sensors. This paper focuses on the Advanced Very High Resolution Radiometer (AVHRR) part of the record, using the Moderate Resolution Imaging Spectrometer (MODIS) instrument as a reference. When a surface reflectance time series is acquired from satellites with variable observation geometry, the directional variation generates an apparent noise which can be corrected by modeling the bidirectional reflectance distribution function (BRDF). The VJB (Vermote, Justice and Bréon, 2009) method estimates a target’s BRDF shape using 5 years of observation and corrects for directional effects maintaining the high temporal resolution of the measurement using the instantaneous Normalized Difference Vegetation Index (NDVI). The method was originally established on MODIS data but its viability and optimization for AVHRR data have not been fully explored. In this study we analyze different approaches to find the most robust way of applying the VJB correction to AVHRR data, considering that high noise in the red band (B1) caused by atmospheric effect makes the VJB method unstable. Firstly, our results show that for coarse spatial resolution, where the vegetation dynamics of the target don’t change significantly, deriving BRDF parameters from 15+ years of observations reduces the average noise by up to 7% in the Near Infrared (NIR) band and 6% in the NDVI, in comparison to using 3-year windows. Secondly, we find that the VJB method can be modified for AVHRR data to improve the robustness of the correction parameters and decrease the noise by an extra 8% and 9% in the red and NIR bands with respect to using the classical VJB inversion. We do this by using the Stable method, which obtains the volumetric BRDF parameter (V) based on its NDVI dependency, and then obtains the geometric BRDF parameter (R) through the inversion of just one parameter.

LTDR↗

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 NTRS2018

Directional Reflectance Studies in Support of the Radiometric Calibration Test Site (RadCaTS) at Railroad Valley

The Radiometric Calibration Test Site (RadCaTS) is a suite of commercial and custom instruments used to make measurements of the surface reflectance and atmosphere throughout the day at Railroad Valley, Nevada. It was developed in response to the need for daily radiometric calibration data for the vast array of Earth-observing sensors on orbit, which is continuously increasing as more nations and private companies launch individual environmental satellites as well as large constellations. The current suite of instruments at RadCaTS includes five ground-viewing radiometers (GVRs), four of which view the surface in a nadir-viewing configuration. Many sensors such as those on Landsat-7 and Landsat-8 view Railroad Valley within 3° of nadir, while others such as those on Sentinel-2A and -2B, RapidEye, Aqua, Suomi NPP, and Terra can view Railroad Valley at off-nadir angles. Past efforts have shown that the surface bidirectional reflectance distribution function (BRDF) has minimal impact on vicarious calibration uncertainties for views <10°, but the desire to use larger view angles has prompted the effort to develop a BRDF correction for data from RadCaTS. The current work investigates the application of Railroad Valley BRDF data derived from a BRF camera developed at the University of Arizona in the 1990s (but is no longer in use) to the current RadCaTS surface reflectance measurements. Also investigated are early results from directional reflectance studies using a mobile spectro-goniometer system during a round-robin field campaign in 2018. This work describes the preliminary results, the effects on current measurements, and the approach for future measurements.

RadCalNet↗

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

Spectroscopic Behavior of Composite, Black Thermal Paint, Solar Cell, and Multi-Layered Insulation Materials in a GEO Simulated Environment

The population of objects orbiting Earth is dominated by orbital debris. The following study presents reflectance spectroscopic measurements and bidirectional reflectance distribution function (BRDF) evaluations taken on common spacecraft materials (Table 1), some of which are likely candidates in the orbital debris population. Their optical properties were assessed in their pristine conditions, as well as after exposure in a space environmental chamber used to simulate space weathering. The materials studied will prove that they have excellent properties in resisting the effects of damage that are common in both low Earth orbit and geosynchronous Earth orbit (GEO) based on the research discussed in this work.

Reyes, Jacqueline A.↗

NASA NTRSDate not supplied

TPSAS-NF1676L-16988-DND

There has been renewed interest to uniformly recalibrate historical geostationary (GEO) data records to aid in climate monitoring. GEO sensors have annual repeatable angular sampling over a given location. The view angle is fixed and the imaging schedule is usually constant through its lifetime. Given the fact that colocated GEOs are always share the same sub-satellite point and maintain their imaging schedules provides repeatable angular sampling over decades. One of the biggest challenges in transferring a reference sensor calibration using invariant desert targets to another sensor is the accuracy of the bidirectional reflectance distribution function (BDRF). A well-calibrated GEO can be used to predict the daily exoatmospheric radiance model (DERM) over a desert target for a given GMT that is valid for any GEO sensor at the same location. The advantage of this method is that a BRDF is not needed. Another challenge of invariant target calibration is the unique spectra signature of the desert. However, since most GEOs are built in batches, the spectral response functions (SRF) are very similar for most historical GEOs, the spectral band adjustment factor (SBAF) between GEO sensors is much smaller than for MODIS and GEO sensors. Since the water vapor burden over the desert is seasonal, both the TOA and desert surface can be considered invariant for a given day of the year. The reference GEO can be inter-calibrated with MODIS or VIIRS, which have onboard visible calibration using solar diffusers, using other methods, such as ray-matching or deep convective clouds. Also the next generation GEOs will have onboard visible calibration, which will increase the accuracy of this method. Three Meteosats over the Libyan desert will be used to illustrate the DERM method. The reference Meteosat will be inter-calibrated against Aqua-MODIS. The reference GEO DERM will be constructed and used to calibrate the remaining Meteosats. The DERM calibration will be validated by comparing the calibration using Aqua-MODIS ray-matching. Similarly, two GOES sensors using the Sonoran desert will also be highlighted. An uncertainty analysis will also be performed with emphasis on the SBAF, derived over the desert targets using both SCIAMACHY and Hyperion hyper-spectral radiances.

David Doelling↗

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 NTRS2020

Assessments of S-NPP and N20 VIIRS DNB and M bands calibration stability and consistency using a homogeneous ground target

The S-NPP and N20 VIIRS Day-Night band (DNB) and M bands top-of-atmosphere (TOA) radiance and reflectance are calculated and a kernel-driven Bidirectional Reflectance Distribution Function (BRDF) correction model is used to correct the surface and atmosphere combined BRDF influence. Due to degradation in the DNB modulated Relative Spectral Response (RSR), the S-NPP VIIRS observed TOA DNB reflectance indicates a decrease of 1.89% and the SCIAMACHY spectra derived TOA DNB reflectance has a decrease of 1.63% for the past 8.5 years. The N20 VIIRSTOA DNB reflectance decreased 0.50% in the past 2.5 years. The DNB radiance is also compared with the integral of the M bands radiance from M4, M5, and M7. The fitting trends of DNB to the integral of M bands ratios indicate a0.48% decrease for S-NPP VIIRS and 0.14% increase for N20 VIIRS. The N20 VIIRS DNB to integral M bands ratios are closer to 1 than the S-NPP VIIRS data. The BRDF corrected reflectance comparisons show that the N20 VIIRS data is slightly lower than those of S-NPP VIIRS. The averages of the linear fit values of the N20 to S-NPP VIIRS from 2018to 2020 June are -1.97%, -4.99%, -3.36%, and -0.85% for M4, M5, M7, and DNB, respectively. Our results indicate that the S-NPP and N20 VIIRS DNB and M bands calibration have been stable. The cross-sensor differences in DNB and M bands are generally consistent with other independent studies using similar and different approaches.

Libya 4↗

NASA NTRS2020

SNPP VIIRS RSB on-orbit radiometric calibration algorithms Version 2.0 and the performances. Part II: The performances

In Part I (Lei et. al, submitted to J. of Appl. Rem. Sens.),we gave detailed reviews of the algorithms Version 2.0 used for the on-orbit radiometric calibration of the reflective solar bands (RSBs) of the first Visible Infrared Imaging Radiometer Suite instrument. These algorithms improve the accuracy of the measured on-orbit change factor of the solar diffuser bidirectional reflectance distribution function, the H-factor, and reveal that the H-factor is angle dependent. With the help of lunar observations and the improved H-factor, the algorithms give more accurate values for the RSB detector on-orbit F-factor changes (F-factor is a correction factor to the initially retrieved scene spectral radiance). In this paper we review the RSB radiometric calibration performances. We show the H-factor temporal trend, the estimated uncertainty of the retrieved H-factor, and the F-factor temporal trend. Additionally we show the detector signal-to-noise ratio (SNR), the estimated uncertainty of the top-of-the-atmosphere solar spectral reflectance, the reflectance temporal trend for the Libya 4 desert, and the differences in the reflectances among the SNPP and the NOAA-20 VIIRS, and the Aqua MODIS. Our results show that although the SNRs trend downwards, they exceed the requirements by large margins. The reflectances from the Libya 4 desert show that the SNPP VIIRS’ reflectance is higher than those of the Aqua MODIS and the NOAA-20 VIIRS.

on-orbit calibration↗

NASA NTRS2020

SNPP VIIRS RSB on-orbit radiometric calibration algorithms Version 2.0 and the performances. Part I: The algorithms

The first VIIRS instrument is aboard the Suomi National Polar-orbiting Partnership satellite. The instrument has 14 reflective solar bands (RSBs) to passively collect photons reflected from the Earth surface in the design wavelengths from 412 to 2250 nm. The instrument uses a solar diffuser (SD) to radiometrically calibrate its RSBs. When lit by the Sun through an attenuation screen (the SD screen), the SD diffusely reflects off the incident sunlight to act as a radiance source for the calibration. An onboard solar diffuser stability monitor (SDSM) yields the on-orbit change of the SD bidirectional reflectance distribution function (BRDF) by comparing the signal strength from the SD with that from the Sun attenuated by another attenuation screen (the SDSM screen). Complications arise due to the discovery that the on-orbit change of the BRDF is angle dependent. Additionally, the SDSM does not cover the wavelengths for the short-wave infrared bands in the RSBs. Furthermore, satellite yaw maneuvers were performed in the early mission to yield data for refining the prelaunch SDSM screen relative effective transmittance and the relative product of the SD screen transmittance and the BRDF at the mission start. But the yaw maneuver data are coarse in the solar azimuth angles and thus are unable to yield accurate values between the measurement angles. Over the years of performing on-orbit radiometric calibration through the SD for the VIIRSRSBs, we have developed several highly effective calibration algorithms to address the issues mentioned above. This paper reviews these algorithms.

on-orbit cailbration↗

NASA NTRS2020

SNPP VIIRS RSB on-orbit radiometric calibration algorithms Version 2.0 and the performances. Part I: The algorithms

The first VIIRS instrument is aboard the Suomi National Polar-orbiting Partnership satellite. The instrument has 14 reflective solar bands (RSBs) to passively collect photons reflected from the Earth surface in the design wavelengths from 412 to 2250 nm. The instrument uses a solar diffuser (SD) to radiometrically calibrate its RSBs. When lit by the Sun through an attenuation screen (the SD screen), the SD diffusely reflects off the incident sunlight to act as a radiance source for the calibration. An onboard solar diffuser stability monitor (SDSM) yields the on-orbit change of the SD bidirectional reflectance distribution function (BRDF) by comparing the signal strength from the SD with that from the Sun attenuated by another attenuation screen (the SDSM screen). Complications arise due to the discovery that the on-orbit change of the BRDF is angle dependent. Additionally, the SDSM does not cover the wavelengths for the short-wave infrared bands in the RSBs. Furthermore, satellite yaw maneuvers were performed in the early mission to yield data for refining the prelaunch SDSM screen relative effective transmittance and the relative product of the SD screen transmittance and the BRDF at the mission start. But the yaw maneuver data are coarse in the solar azimuth angles and thus are unable to yield accurate values between the measurement angles. Over the years of performing on-orbit radiometric calibration through the SD for the VIIRSRSBs, we have developed several highly effective calibration algorithms to address the issues mentioned above. This paper reviews these algorithms.

Ning Lei↗

NASA NTRS2020

SNPP VIIRS RSB on-orbit radiometric calibration algorithms Version 2.0 and the performances. Part II: The performances

In Part I (Lei et. al, submitted to J. of Appl. Rem. Sens.),we gave detailed reviews of the algorithms Version 2.0 used for the on-orbit radiometric calibration of the reflective solar bands (RSBs) of the first Visible Infrared Imaging Radiometer Suite instrument. These algorithms improve the accuracy of the measured on-orbit change factor of the solar diffuser bidirectional reflectance distribution function, the H-factor, and reveal that the H-factor is angle dependent. With the help of lunar observations and the improved H-factor, the algorithms give more accurate values for the RSB detector on-orbit F-factor changes (F-factor is a correction factor to the initially retrieved scene spectral radiance). In this paper we review the RSB radiometric calibration performances. We show the H-factor temporal trend, the estimated uncertainty of the retrieved H-factor, and the F-factor temporal trend. Additionally we show the detector signal-to-noise ratio (SNR), the estimated uncertainty of the top-of-the-atmosphere solar spectral reflectance, the reflectance temporal trend for the Libya 4 desert, and the differences in the reflectances among the SNPP and the NOAA-20 VIIRS, and the Aqua MODIS. Our results show that although the SNRs trend downwards, they exceed the requirements by large margins. The reflectances from the Libya 4 desert show that the SNPP VIIRS’ reflectance is higher than those of the Aqua MODIS and the NOAA-20 VIIRS

Ning Lei↗

NASA NTRS2020

Performance of NOAA-20 VIIRS Solar Diffuser and Solar Diffuser Stability Monitor

Visible Infrared Imaging Radiometer Suite (VIIRS) radiometrically calibrates its reflective solar bands (RSBs) primarily through a sunlit onboard solar diffuser (SD). The sunlit SD provides a known radiance under the condition that the absolute product of the SD screen transmittance and the bidirectional reflectance distribution function (BRDF) along the SD-to-telescope direction is accurately known. The BRDF changes due to solar exposure. The change, referred to as the H-factor, is monitored by the onboard SD stability monitor (SDSM). The accuracy of the retrieved H-factor propagates to the retrieved F-factor which corrects the scene spectral radiance. High accuracy of the retrieved H-factor relies on high accuracies in the SDSM screen relative effective transmittance and the relative product of the SD screen effective transmittance and the BRDF at the mission start, and a high SDSM detector signal-to-noise ratio (SNR). This article briefly reviews the algorithms used for the NOAA-20 (N20) VIIRS RSB on-orbit radiometric calibration. Additionally, we show the performance of the N20 VIIRS SDSM, giving the SDSM detector SNRs and the SDSM detector gain temporal changes. We develop a model for the SNRs. The model shows that the decreased SNRs in time are due to the detector gain decreases. We also show the N20 VIIRS SD on-orbit performance, measured by the retrieved H-factor and the estimated standard deviation of its error. The H-factor for the telescope view is obtained from the H-factor for the SDSM view, multiplied by an H-factor angular dependence term. We use an innovative method to determine the angular dependence, using the dependence obtained for the Suomi National Polar-orbiting Partnership (SNPP) VIIRS.

VIIRS↗