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At least 235 records · Page 13

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

Materials currently populating Earth orbital regimes can be distinguished by comparing remote observational data to that of optical material measurements obtained in the laboratory. Experimentation for this research primarily involved the acquisition of spectroscopic measurements on materials of interest to the telescopic observational community for enhanced space situational awareness. Common spacecraft materials worthy of preeminent analysis for this investigation include a carbon-carbon (c-c) matrix composite, various black thermal paints, a GPS solar cell and three different cover glass components. These materials were subjected to a simulated geosynchronous Earth orbit (GEO) space environment with the intent of observing material optical property behavior over quantitative exposure time. The aforementioned materials have been measured in their pristine and GEO simulated exposed conditions. A reflectance spectrometer and a bi-directional reflectance distribution function (BRDF) optical system have been operated to perform material characterization, optical property analysis, and to further compare such data to telescopic observational data acquired on equal materials.

Reyes, Jacqueline A.↗

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.↗

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↗

Cross-Calibration of Terra and Aqua MODIS Using RadCalNet

The twin MODIS instruments onboard the Terra and Aqua spacecraft have been successfully operating for nearly two decades and providing complementary observations of the Earth’s land, ocean, and atmosphere. Although the two MODIS instruments view the entire Earth’s surface once every 2-3 days, simultaneous views between them are limited due to their varying orbits. Therefore, the intercomparison between these two instruments has been previously performed using a transfer instrument (such as AVHRR) or using lunar measurements normalized using a common model such as the USGS ROLO. In recent years RadCalNet, a CEOS initiative, has provided SI-traceable Top-of-Atmosphere (TOA) reflectances from a coordinated network of instrumented land-based sites. RadCalNet facilitates a unique mechanism to perform cross-calibration of instruments by minimizing the uncertainties associated with overpass time differences. In this work, the near-simultaneous TOA reflectance measurements from the Railroad Valley, US (RVUS) are used as a transfer to compare the on-orbit observations for the Terra and Aqua MODIS RSB. Near-nadir overpasses from January 2013 to January 2019 are processed and matched up with near-simultaneous RadCalNet measurements. Results show that the VIS/NIR bands agree to within 2% and the SWIR bands agree to within 5%. Also, discussed in this work are the future efforts that will be undertaken to expand this comparison to include other instruments, other sites, and both nadir- and off-nadir views after compensation for BRDF effects.

Amit Angal↗

Generation of Land Surface Reflectance with Combined Geo-KOMPSAT-2A AMI and Himawari 8 AHI Observations

The latest generation of geostationary satellites has opened a new era of Earth observations with unprecedented spatiotemporal resolution and spectral range. Together with GOES 16/17 ABI, FY4-A AGRI, and Himawari-8 AHI, a new Korean geostationary satellite (Geo-KOMPSAT-2A AMI) has operationally collected a full-disk image in 16 channels every ten minutes since July 2019, allowing diurnal land surface monitoring over a large proportion of Asia and all of Oceania. Retrieving accurate surface reflectance (SR) over land from GK-2A/AMI is a challenging but high priority objective. One of the challenges is the absence of a spectral band in the 2.2 m SWIR range from AMI, which is required by many atmospheric correction algorithms to retrieve atmospheric aerosol properties. To remedy this issue, we adopt a strategy that combines concurrent GK-2A/AMI and Himawari 8/AHI observations in order to derive AMI SR. We have adapted the NASA Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to process the data stream from Himawari 8/AHI. The advantages of the MAIAC algorithm is its capability to exploit the high temporal frequency and varying illumination geometry of the geostationary data for advanced cloud/snow detection, aerosol retrieval, and characterization of surface bidirectional reflectance properties. Leveraging the similarities of spectral bands and the sun-target-sensor geometry between AMI and AHI, we are able to create denser time series of observations and enhanced BRDF samples over most of the spatial coverage of AMI (and AHI). The combined stereo-type observations not only help derive SR for AMI but also enhance retrievals of the corresponding AHI surface products. We evaluate the resulting AMI SR using ground (AERONET) observations and corresponding MODIS products. Further, we discuss potential challenges in utilizing the geostationary satellite data for land surface monitoring.

geostationary satellite↗

Detecting Short Term Drought Impact in the Southwest US Using GOES-16 ABI Data

Satellite optical remote sensing has been often used for monitoring broad-region vegetation change, for example, phenology observations and the year-to-year leaf area index (LAI) responses to climate oscillations. However, rapid responses of vegetation to day-to-day weather perturbations are difficult to detect using available optical remote sensing satellites because of the low frequency of the observations. Sun-synchronous optical sensors, such as Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR), can observe a target area once a day. Daily observations cannot distinguish whether short-term changes in Normalized Differential Vegetation Index (NDVI) are actual LAI change or cloud contamination. NOAA’s GOES satellites make observations every 10 to 15 minutes using the Advanced Baseline Imager (ABI). In this study, we used the Geostationary-NASA Earth Exchange (GeoNEX) L1G Top-of-Atmosphere (TOA) ABI data to detect drought impact on NDVI time series in the Southwest US. We used an empirical method to cancel the BRDF effect of varying solar zenith angle. The ABI was able to detect short term drought impacts as well as an NDVI decrease in the dry season. Increased NDVI right after a rainfall followed by an immediate decrease was observed. These ABI NDVI changes were correlated with the RGB time series from PhenoCam Network data. Results indicated that the ABI can be used for short-term analysis of LAI and can detect small LAI changes caused by drought in an arid area, suggesting the potential for its use in near-real time drought monitoring applications.

ABI↗

Update on EPIC MAIAC V2 Algorithm: Atmospheric Correction

Alexei Lyapustin presented a new v2 MAIAC atmospheric correction algorithm for EPIC. The v2 algorithm introduced new projection removing spatial distortions, a more accurate retrieval of spectral surface reflectance using ancillary MAIAC MODIS BRDF dataset, and a new technique for simultaneous retrieval of aerosol optical depth and spectral absorption. AERONET validation shows that v2 significantly improved AOD accuracy compared to v1, while the retrieved single scattering albedo in the Blue shows a very good accuracy comparable to that of AERONET for both biomass burning smoke and mineral dust aerosols.

Alexei Lyapustin↗

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↗

Neural Network Reflectance Prediction Model for Both Open Ocean and Coastal Waters

Remote sensing of global ocean color is a valuable tool for understanding the ecology and biogeochemistry of the worlds oceans, and provides critical input to our knowledge of the global carbon cycle and the impacts of climate change. Ocean polarized reflectance contains information about the constituents of the upper ocean euphotic zone, such as colored dissolved organic matter (CDOM), sediments, phytoplankton, and pollutants. In order to retrieve the information on these constituents, remote sensing algorithms typically rely on radiative transfer models to interpret water color or remote-sensing reflectance; however, this can be resource-prohibitive for operational use due to the extensive CPU time involved in radiative transfer solutions. In this work, we report a fast model based on machine learning techniques, called Neural Network Reflectance Prediction Model (NNRPM), which can be used to predict ocean bidirectional polarized reflectance given inherent optical properties of ocean waters. This supervised model is trained using a large volume of data derived from radiative transfer simulations for coupled atmosphere and ocean systems using the successive order of scattering technique (SOS-CAOS). The performance of the model is validated against another large independent test dataset generated from SOS-CAOS. The model is able to predict both polarized and unpolarized reflectances with an absolute error (AE) less than 0.004 for 99% of test cases. We have also shown that the degree of linear polarization (DoLP) for unpolarized incident light can be predicted with an AE less than 0.002 for 99% of test cases. In general, the simulation time of SOS-CAOS depends on optical depth, and required accuracy. When comparing the average speeds of the NNRPM against the SOS-CAOS model for the same parameters, we see that the NNRPM is able to predict the Ocean BRDF 6000 times faster than SOS-CAOS. Both ultraviolet and visible wavelengths are included in the model to help differentiate between dissolved organic material and chlorophyll in the study of the open ocean and the coastal zone. The incorporation of this model into the retrieval algorithm will make the retrieval process more efficient, and thus applicable for operational use with global satellite observations.

radiative transfer↗

Highly Absorptive Pupil Mask Fabricated with Black Silicon

Many of NASA’s direct imaging of exoplanet missions and projects require fabricated coronagraph masks to control scattering and diffraction of light. The designed, patterned mask intended for the coronagraphic testbeds are highly absorptive in the visible range on non-metallic regions. In this work, we employed the cryogenic etching process to fabricate black silicon (BSi) to achieve a high aspect ratio (HAR) structures with higher etch rate than conventional reactive ion etching (REI). Recent bidirectional reflectance distribution function (BRDF) measurements of uniformly etched BSi on silicon wafer show highly diffusive BSi with a specular reflective component in the orders of seven magnitudes lower than the total hemispherical reflectance when the polarized or non-polarized incident beam is used.

black-silicon↗

First Provisional Land Surface Reflectance Product from Geostationary Satellite Himawari-8 AHI

A provisional surface reflectance (SR) product from the Advanced Himawari Imager (AHI) on-board the new generation geostationary satellite (Himawari-8) covering the period between July 2015 and December 2018 is made available to the scientific community. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is used in conjunction with time series Himawari-8 AHI observations to generate 1-km gridded and tiled land SR every 10 minutes during day time. This Himawari-8 AHI SR product includes retrieved atmospheric properties (e.g., aerosol optical depth at 0.47μm and 0.51μm), spectral surface reflectance (AHI bands 1–6), parameters of the RTLS BRDF model, and quality assurance flags. Product evaluation shows that Himawari-8 AHI data on average yielded 35% more cloud-free, valid pixels in a single day when compared to available data from the low earth orbit (LEO) satellites Terra/Aqua with MODIS sensor. Comparisons of Himawari-8 AHI SR against corresponding MODIS SR products (MCD19A1) over a variety of land cover types with the similar viewing geometry show high consistency between them, with correlation coefficients (r) being 0.94 and 0.99 for red and NIR bands, respectively. The high-frequency geostationary data are expected to facilitate studies of ecosystems on daily to diurnal time scales, complementing observations from networks such as the FLUXNET.

Himawari-8 AHI↗

Using the Diurnal Variability in GeoNEX TOA Reflectances for Earth Monitoring

Observations from the third-generation geostationary satellite instruments (GOES 16/17 ABI, Himawari 8/9 AHI, and etc.) have spatial resolution and spectral band configurations comparable to flagship LEO sensors (e.g., MODIS/VIIRS). More importantly, these data are acquired at very high temporal resolution, faithfully recording the variations of the full disk of Earth at every 5-10 minutes. They thus provide unique information about Earth’s atmosphere and surface. In order to explore the unique information content of geostationary data, this study systematically analyzes the diurnal variability in the GeoNEX L1G TOA reflectance products and compares them to simulated results by state-of-the-art radiative transfer codes. Our results show that • The smoothness of the TOA reflectance diurnal cycle provides a convenient and reliable way to identify stable atmospheric conditions and filter out passing clouds/shadows. • The diurnal variability of the blue band (0.47µm) reflectance is regulated mainly by atmospheric optical conditions over a majority of land cover types. As such, the diurnal variability of the blue band data allows us to retrieve AOD without invoking the use of spectral band ratios (SRC) as in previous algorithms. • In comparison, the diurnal variability of the short-wave infrared band (2.2µm) BRFs is mainly regulated by surface reflectance and the sun-target-satellite geometry. This information allows us to test and, if suitable, retrieve surface BRDF parameters. • Spectral band ratios, especially those between the 2.2µm and 0.47µm bands, are not constant but vary by locations and sun-target-satellite geometries. Our analysis clearly demonstrates that the information provided in high-frequent geostationary observations is unique and complementary to LEO sensors. Therefore, a synergy of GEO and LEO (and other) sensors has the great potential to improve existing remote sensing models and algorithms for better Earth monitoring.

Diurnal Variability↗

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↗

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↗

Updates on the Debrisat Hypervelocity Experiment and Characterization of Fragments in Support of Environmental Models

To develop, maintain, and update orbital debris environmental and break-up models, such as the NASA Orbital Debris Engineering Model (ORDEM) and the NASA Standard Satellite Breakup Model (SSBM), the NASA Orbital Debris Program Office (ODPO) relies on the most recent validated datasets from various measurement sources, both laboratory and environmental. One key project that will provide insight for break-up events using modern-day spacecraft materials and construction techniques is the DebriSat laboratory hypervelocity-impact test. Based on the mass of the target, the projectile, and the impact velocity, the expected number of fragments greater than 2 mm, generated using the NASA SSBM, was estimated to be close to 85,000. To date, the DebriSat fragment database continues to grow, with over 200,000 fragments collected that will help inform updates to the SSBM. Additionally, the growing fragment ensemble will support key parameters for the next release of NASA’s environmental models, employing fragment shapes, densities, and size distributions. To further support these environmental models, specifically the size parameter used in ground-based optical measurements, optical characterization on a subset of DebriSat fragments is being conducted in ODPO’s Optical Measurement Center (OMC). Broadband bidirectional reflectance distribution (BRDF) measurements will provide insight into the optical-based NASA Size Estimation Model (OSEM). The OSEM equates an object’s brightness to size (e.g., diameter of a disk or sphere) given several assumed parameters, including a defined phase function, albedo, and range. To address the first defined parameter, the ODPO has been using ray-tracing software to simulate light conditions in the OMC and to generate phase functions (i.e., specular, Lambertian, and experimentally-derived) of known shapes, materials, and sizes. This simulated data, in addition to the experimentally derived measurements collected in the OMC, will aid in determining whether a new phase function would be suitable for an updated OSEM. The OSEM also assumes a single-value albedo, thus pre-impact spectral measurements on a subset of DebriSat materials were acquired for baseline material characterization and to provide insight into spacecraft material taxonomies. This DebriSat spectral data, along with spectral measurements from other known spacecraft material samples, will allow for better analyses of albedo variations and the effect on size calculations of defined laboratory targets, thus further supporting OSEM updates. This paper provides an overview of DebriSat, the status of the project, updates on the parameter distributions, an overview of the NASA SSBM, and ongoing fragment characterization efforts within the OMC.

Heather Cowardin↗

Landsat 9 Operational Land Imager2 (OLI2) Diffuser Panel Response Lab Predictions vs. Pre-Launch Measurements

The radiometric calibration of OLI-2 for Landsat 9 uses two types of sources: pre-launch radiance calibrated sphere sources and on-board flight solar diffuser panels. For both calibration articles the instrument contractor, Ball Aerospace Corp. assured the NIST scale transfer via laboratory measurements. The NIST reflectance scale transfer was conducted for the OLI-2 two flight diffusers at the University of Arizona Optical Sciences Center. In this report we present an approach in which the per detector information can be derived for the reflectance panel sources from their BRDF characterization. Using such information enables a cross-check of the as measured reflectance results during the prelaunch diffuser collects illuminated by a Heliostat. This information then enables a derivation of the uncertainty levels to allow assessment of the two radiometric calibration paths agreement.

Raviv Levy↗

Goniometric and Polarized Imaging Spectroscopic Lab Measurements ofSpacecraft Materials

To better characterize the spectral response of common spacecraft materials, the following laboratory measurements are presented to support the Space Situational Awareness community in the analysis of remotely sensed observational data. Of interest is classifying material reflective properties using spectral bidirectional reflectance distribution function (BRDF) data and spatially resolved polarized imaging spectroscopy, allowing laboratory data to be applicable to ground-based optical telescope observations. The team acquired a typical CubeSat solar panel and a sample of multi-layer insulation commonly used on spacecraft for initial measurements. The data were collected at the Goniometer of the Rochester Institute of Technology (GRIT) laboratory with a field and laboratory goniometer housing two Analytical Spectral Device (ASD) spectrometers and a Headwall micro-Hyperspec E-Series imaging spectrometer with an adjustable linear polarizer. The goniometer provides spectral reflectance over a broad spectral range from 350-2500 nm at 1 nm spacing with 3 nm spectral resolution in the visible and near infrared and 8 nm in the shortwave infrared. The Headwall imager covers a spectral range from 400-1000 nm with 1.6 nm spectral resolution. We present the results from these initial measurements that show highly reflective regions at various locations in the angular domain for both materials. In addition, the solar cell spectra exhibited strong interference effects typically observed with thin films. Our team is pursuing a variety of typical solar cells to assess variations in product type. The spatially resolved polarization ratio maps show variability across the materials due to surface structure and varying material composition. Based on these results, we outline a plan for simulating spectral radiance light curves of the materials in various orbital configurations as they would be measured from ground- based telescopes for a clear observing sky during twilight. The paper will also present a plan for expanding ours of interest to determine if the results presented are unique to these samples and to categorize the spectral response for different material classes.

Chris H. Lee↗

A Comparison of Multi-Angle Implementation of Atmospheric Correction and MOD09 Daily Surface Reflectance Products from MODIS

This study presents the first systematic comparison of MAIAC Collection 6 MCD19A1 daily surface reflectance (SR) product with standard MODIS SR (MOD/MYD09). The study was limited to four tiles located in mid-Atlantic United States (H11V05), Canada (H12V03),central Amazon (H11V09), and North-Eastern China (H27V05) and used over 5000 MODIS granules in 2018. Overall, there is a remarkable agreement between the best quality pixels of the two products, in particular in the Red and NIR bands. Over selected tiles, the evaluation found that MAIAC provides from 4 to 25% more high-quality retrievals thanMOD09 annually, with the largest difference in tropical regions, confirming results of the previous studies. The comparison of spectral characteristics showed a systematic MAIAC-MOD09 difference increasing from NIR to Blue, typical of biases of a Lambertian assumption in MOD09 algorithm. Over the North-Eastern China, MCD19A1 SR is found more stable at wide range of aerosol optical depth (AOD) variations, whereasMOD09 SR shows a consistent positive bias increasing with AOD and at shorter wavelengths. The observed SR differences can be attributed to differences in cloud detection, aerosol retrieval and in atmospheric correction which is performed using an accurate BRDF-coupled radiative transfer model in MAIAC and a Lambertian surface model in MOD09. While this study is not representative of the global performance because of its limited geographical coverage, it should help the land community to better understand the differences between the two products.

MAIAC↗