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All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Applications of Skylab EREP photographs to mapping landforms and environmental geomorphology in the Great Plains and Midwest

The following evaluations of Skylab photographs were undertaken: (1) the 1290 Skylab S190A and S190B photographs of Illinois, Iowa, Kansas, Missouri, Nebraska, and South Dakota were evaluated in detail in terms of coverage, cloud cover, photographic quality, endlap, detectability of roads and stereorelief, and utility for geomorphologic mapping, and (2) the utility of the Skylab photos were tested for interpretive analytic mapping of geomorphologic features over large areas representative of different parts of this region. Photointerpretative maps of analytic geomorphology were obtained for various test areas representative of the varied landscapes in the region. These maps are useful for regional land-use planning, ground-water exploration, and other environmental geomorphologic-geologic applications. Compared with LANDSAT-1 MSS images, Skylab photos afford almost as extensive overviews of large areas but in considerably greater detail, and for many SL photos, moderate stereorelief. However, repetitive multiseasonal, cloud-free coverage by high-quality photos is very limited and many areas have no coverage at all.

Morrison, R. B.↗
NASA NTRSDate not supplied

Development of Multi-Edge Slant Target for Unlocalized MTF Measurement of Airborne Imaging System Payloads

Calibration of imaging instruments is a critical step in effectively characterizing imaging data. A comprehensive characterization of an imaging system provides valuable insight into the overall uncertainties in the results derived from the raw data collected. The Scientifically Calibrated In-Flight Imagery (SCIFLI) team (based at NASA Langley Research Center) has designed, built, tested, and successfully flown the optical payload known as the SCIFLI Airborne Multispectral Imager (SAMI). SAMI is a multispectral imaging payload, complete with sensor configurations for the Ultraviolet-Visible spectrum as well as Near- Infrared, Shortwave Infrared, and Midwave Infrared bands and is fitted with various optical hardware designed to turn, split, and focus light beams to the respective in-band sensors. Radiometric calibrations are performed for SAMI such that the accuracy and uncertainty of thermal and spectral measurements are effectively characterized. However, SAMI does not regularly undergo spatial characterizations to evaluate the performance of the imager at high spatial frequencies. This is essential, as understanding the spatial sensor response of discrete sensors is just as important as the spectral sensor response. The payload currently utilizes a calibration cart for lab testing. Equipped with a modular setup and several radiation sources, it is perfect for performing high-quality radiometric calibrations. This work focuses on using the calibration cart to perform spatial calibrations. A custom designed calibration target is being used to evaluate the optical performance of SAMI. Specifically, the target is designed to measure the Modulation Transfer Function (MTF) of the imager in discrete locations around the focal plane. The results of this characterization will provide insight into the spatial resolution capabilities of the SAMI payload in practice. Future work includes using the results of the study to correct optical imperfections in imagery taken with SAMI.

SAMI↗
NASA NTRS1990

Ultrasonic and radiographic evaluation of advanced aerospace materials: Ceramic composites

Two conventional nondestructive evaluation techniques were used to evaluate advanced ceramic composite materials. It was shown that neither ultrasonic C-scan nor radiographic imaging can individually provide sufficient data for an accurate nondestructive evaluation. Both ultrasonic C-scan and conventional radiographic imaging are required for preliminary evaluation of these complex systems. The material variations that were identified by these two techniques are porosity, delaminations, bond quality between laminae, fiber alignment, fiber registration, fiber parallelism, and processing density flaws. The degree of bonding between fiber and matrix cannot be determined by either of these methods. An alternative ultrasonic technique, angular power spectrum scanning (APSS) is recommended for quantification of this interfacial bond.

Generazio, Edward R.↗
NASA NTRS1999

Correlation Between Bulk Material Defects and Spectroscopic Response in Cadmium Zinc Telluride Detectors

One of the critical challenges for large area cadmium zinc telluride (CdZnTe) detector arrays is obtaining material capable of uniform imaging and spectroscopic response. Two complementary nondestructive techniques for characterizing bulk CdZnTe have been developed to identify material with a uniform response. The first technique, infrared transmission imaging, allows for rapid visualization of bulk defects. The second technique, x-ray spectral mapping, provides a map of the material spectroscopic response when it is configured as a planar detector. The two techniques have been used to develop a correlation between bulk defect type and detector performance. The correlation allows for the use of infrared imaging to rapidly develop wafer mining maps. The mining of material free of detrimental defects has the potential to dramatically increase the yield and quality of large area CdZnTe detector arrays.

Parker, Bradford H.↗
NASA NTRS2001

The Role of Combination Techniques in Maximizing the Utility of Precipitation Estimates from Several Multi-Purpose Remote-Sensing Systems

Multi-purpose remote-sensing products from various satellites have proved crucial in developing global estimates of precipitation. Examples of these products include low-earth-orbit and geosynchronous-orbit infrared (leo- and geo-IR), Outgoing Longwave Radiation (OLR), Television Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS) data, and passive microwave data such as that from the Special Sensor Microwave/ Imager (SSM/I). Each of these datasets has served as the basis for at least one useful quasi-global precipitation estimation algorithm; however, the quality of estimates varies tremendously among the algorithms for the different climatic regions around the globe.

Huffman, George J.↗
NASA NTRS2004

The NASA Micro-Pulse Lidar Network (MPLNET): Co-location of Lidars with AERONET

We present the formation of a global-ground based eye-safe lidar network, the NASA Micro-Pulse Lidar Network (MPLNET). The aim of MPLNET is to acquire long-term observations of aerosol and cloud vertical profiles at unique geographic sites within the NASA Aerosol Robotic Network (AERONET). Network growth follows a federated approach, pioneered by AERONET, wherein independent research groups may join MPLNET with their own instrument and site. MPLNET utilizes standard instrumentation and data processing algorithms for efficient network operations and direct comparison of data between each site. The micro-pulse lidar is eye-safe, compact, and commercially available, and most easily allows growth of the network without sacrificing standardized instrumentation gods. Red-time data products (next-day) are available, and include Level 1 daily lidar signal images from the surface to -2Okm, and Level 1.5 aerosol extinction provides at times co-incident with AERONET observations. Testing of our quality assured aerosol extinction products, Level 2, is near completion and data will soon be available. Level 3 products, continuous daylight aerosol extinction profiles, are under development and testing has begun. An overview of h4PL" will be presented. Successful methods of merging standardized lidar operations with AERONET will also be discussed, with the first 4 years of MPLNET results serving as an example.

Welton, Ellsworth J.↗
NASA NTRS2014

Initial Stability Assessment of S-NPP VIIRS Reflective Solar Band Calibration Using Invariant Desert and Deep Convective Cloud Targets

The latest CERES FM-5 instrument launched onboard the S-NPP spacecraft will use the VIIRS visible radiances from the NASA Land Product Evaluation and Analysis Tool Elements (PEATE) product for retrieving the cloud properties associated with its TOA flux measurement. In order for CERES to provide climate quality TOA flux datasets, the retrieved cloud properties must be consistent throughout the record, which is dependent on the calibration stability of the VIIRS imager. This paper assesses the NASA calibration stability of the VIIRS reflective solar bands using the Libya-4 desert and deep convective clouds (DCC). The invariant targets are first evaluated for temporal natural variability. It is found for visible (VIS) bands that DCC targets have half of the variability of Libya-4. For the shortwave infrared (SWIR) bands, the desert has less variability. The brief VIIRS record and target variability inhibits high confidence in identifying any trends that are less than 0.6yr for most VIS bands, and 2.5yr for SWIR bands. None of the observed invariant target reflective solar band trends exceeded these trend thresholds. Initial assessment results show that the VIIRS data have been consistently calibrated and that the VIIRS instrument stability is similar to or better than the MODIS instrument.

VIIRS↗
NASA NTRS2020

Learning instrument invariant characteristics for generating high-resolution global coral reef maps

Coral reefs are one of the most biologically complex and diverse ecosystems within the shallow marine environment. Unfortunately, these underwater ecosystems are threatened by a number of anthropogenic challenges, including ocean acidification and warming, overfishing, and the continued increase of marine debris in oceans. This requires a comprehensive assessment of the world's coastal environments, including a quantitative analysis on the health and extent of coral reefs and other associated marine species, as a vital Earth Science measurement. However, limitations in observational and technological capabilities inhibit global sustained imaging of the marine environment. Harmonizing multimodal data sets acquired using different remote sensing instruments presents additional challenges, thereby limiting the availability of good quality labeled data for analysis. In this work, we develop a deep learning model for extracting domain invariant features from multimodal remote sensing imagery and creating high-resolution global maps of coral reefs by combining various sources of imagery and limited hand-labeled data available for certain regions. This framework allows us to generate, for the first time, coral reef segmentation maps at 2-meter resolution, which is a significant improvement over the kilometer-scale state-of-the-art maps. Additionally, this framework doubles accuracy and IoU metrics over baselines that do not account for domain invariance.

Domain Adaptation↗
NASA NTRS2023

Variably Premixed Rotating Detonation Engine for Evaluation of Detonation Cycle Dynamics

A variably premixed rotating detonation engine using gaseous hydrogen and air reactants is introduced to enable investigation of key cycle processes while varying the homogeneity of the reactant inlet conditions. Two chamber configurations are investigated, the first with reactants filling the entire span of a straight annular channel and the second with a slightly larger channel and a backward-facing step. The first configuration permits both premixed and non-premixed fuel injection, enabling mixing quality modulation. The second configuration is operated only at fully premixed conditions. Operating modes and detonation wave speeds are characterized using exhaust-plume imaging, while the chamber heat release field is captured by transverse imaging through a transparent outer body. Tests using the first configuration were characterized by unstable counterpropagating modes with low detonation wave speeds regardless of the state of premixing, while the second configuration rendered single-wave behavior with wave speeds up to 86% of the Chapman–Jouguet velocity. Comparisons with a simple computational fluid dynamics model of the second configuration indicate that reactant preheating significantly influences the detonation wave topology, highlighting the potential utility of the test platform for isolating key physics associated with the effects of reactant premixing, preheating, and chamber geometry on rotating detonation engine operation.

Detonation↗
NASA NTRS2023

Using Dome Concordia to Characterize the Long-Term Stability of VIIRS Thermal Emissive Bands

The Visible Infrared Imaging Radiometer Suite (VIIRS) instruments aboard the Suomi NPP and NOAA-20 spacecraft have successfully provided Earth image products since 2011 and 2017, respectively. Maintaining accurate radiometric calibration and calibration consistency between the two sensors is a necessity for the continued quality of long-term data records. In this work, the use of frequent VIIRS measurements of brightness temperature over the area surrounding Dome Concordia (Dome C), Antarctica (75.1 °S, 123.4°E) to track the long-term stability of its thermal emissive bands (TEB) is presented. The extremely dry, cold, and rarefied atmosphere of the site makes it ideal to track and detect long-term changes in the TEB responses via analysis of near-nadir and off-nadir VIIRS overpasses in reference to the surface temperature measurements provided by an automated weather station (AWS). Multi-year Dome C measurements have been used to assess the stability of the VIIRS response-versus-scan-angle (RVS) of the half-angle-mirror (HAM), derived from prelaunch characterization, and detector differences at multiple scan angles. Also, included in this work is the RVS stability assessments using the Dome C overpasses. The methodology developed via this work will also be applied to the recently launched VIIRS instrument onboard the NOAA-21 satellite (previously JPSS-2) in the future.

Amit Angal↗
NASA NTRS1993

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS): Recent Improvements to the Sensor and Data Facility

AVIRIS operations at the Jet Propulsion Laboratory consist primarily of a sensor task and a data facility task. The sensor task is responsible for AVIRIS sensor meaintenance, laboratory calibration, and field operations. The AVIRIS data facility is responsible for data archiving, data calibration, quality monitoring and distribution. In this paper we describe recent improvements in these two primary AVIRIS tasks.

Airborne↗
NASA NTRS2022

Florida Water Resources: Assessing Coastal Resiliency Across Florida's Aquatic Preserves in Response to Hurricane Forces

Intensifying weather events, sea level rise, and extensive coastal development in Southwestern Florida are escalating the need for Florida’s mangrove conservation. These mangroves are imperative for coastline stabilization, habitat provision for native species, and water quality management. Our partner, the Florida Department of Environmental Protection (FDEP), Office of Resilience and Coastal Protection is tasked with monitoring and conserving the Charlotte Harbor, Estero Bay, Rookery Bay, and Pinellas County Aquatic Preserves. We developed the Growth, Resilience, and Optical Vegetation Evaluator (GROVE) Google Earth Engine toolset for partners to determine mangrove forest extent through time, analyze mangrove forest health, and collect several water quality parameters within the preserves from January 2002–August 2022. The toolset provides easily accessible data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager 2 (OLI-2), and the Shuttle Radar Topography Mission (SRTM). Using training datasets of known mangrove forest locations, we also established a machine learning approach to create mangrove extent maps. Maps from all four preserves indicated migration of mangrove forests inland as the greatest areas of change were transitional zones. Additionally, normalized difference vegetation index (NDVI), normalized difference turbidity index (NDTI), and chlorophyll-a maps were generated for the partners. This project provides decision makers with a useful tool for understanding temporal changes in Florida’s aquatic preserves, identifying areas of ecological stress, and providing actionable data to make informed plans for mangrove preservation.

Remote sensing↗
NASA NTRS2021

Air Pollution Scenario over Pakistan: Characterization and Ranking of Extremely Polluted Cities using Long-Term Concentrations of Aerosols and Trace Gases

Pakistan ranks third in the world in terms of mortality attributable to air pollution, with aerosol mass concentrations (PM2.5) consistently well above WHO (World Health Organization) air quality guidelines (AQG). However, regulation is dependent on a sparse network of air quality monitoring stations and insufficient ground data. This study utilizes long-term observations of aerosols and trace gases to characterize and rank the air pollution scenarios and pollution characteristics of 80 selected cities in Pakistan. Datasets used include (1) the Aqua and Terra (AquaTerra) MODIS (Moderate Resolution Imaging Spectroradiometer) Level 2 Collection 6.1 merged Dark Target and Deep Blue (DTB) aerosol optical depth (AOD) retrieval products; (2) the CAMS (Copernicus Atmosphere Monitoring Service) reanalysis PM1, PM2.5, and PM10 data; (3) the MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) reanalysis PM2.5 data, (4) the OMI (Ozone Monitoring Instrument) tropospheric vertical column density (TVCD) of nitrogen dioxide (NO2), and VCD of sulfur dioxide (SO2) in the Planetary Boundary Layer (PBL), (5) the VIIRS (Visible Infrared Imaging Radiometer Suite) Nighttime Lights data, (6) MODIS Collection 6 Version 2 global monthly fire location data (MCD14ML), (7) population density, (8) MODIS Level 3 Collection 6 land cover types, (9) AERONET (AErosol RObotic NETwork) Version 3 Level 2.0 data, and (10) ground-based PM2.5 concentrations from air quality monitoring stations. Potential Source Contribution Function (PSCF) analyses were performed by integrating with ground-based PM2.5 concentrations and the NOAA (National Oceanic and Atmospheric Administration) HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) air parcel back trajectories to identify potential pollution source areas which are responsible for extreme air pollution in Pakistan. Results show that the ranking of the top polluted cities depends on the type of pollutant considered and the metric used. For example, Jhang, Multan, and Vehari were characterized as the top three polluted cities in Pakistan when considering AquaTerra DTB AOD products; for PM1, PM2.5, and PM10 Lahore, Gujranwala, and Okara were the top three; for tropospheric NO2 VCD Lahore, Rawalpindi, and Islamabad and for PBL SO2 VCD Lahore, Mirpur, and Gujranwala. The results demonstrate that Pakistan’s entire population has been exposed to high PM2.5 concentrations for many years, with a mean annual value of 54.7 μg/cu. m, over all Pakistan from 2003 to 2020. This value exceeds Pakistan’s National Environmental Quality Standards (Pak-NEQS, i.e., <15 μg/cu. m annual mean) for ambient air defined by the Pakistan Environmental Protection Agency (Pak-EPA) as well as the WHO Interim Target-1 (i.e., mean annual PM2.5 <35 μg/cu. m). The spatial analyses of the concentrations of aerosols and trace gases in terms of population density, nighttime lights, land cover types, and fire location data, and the PSCF analysis indicate that Pakistan’s air quality is strongly affected by anthropogenic sources inside of Pakistan, with contributions from surrounding countries. Statistically significant positive (increasing) trends in PM1, PM2.5, PM10, tropospheric NO2 VCD, and SO2 VCD were observed in ~89%, ~67%, ~48%, 91%, and ~88% of the Pakistani cities (80 cities), respectively. This comprehensive analysis of aerosol and trace gas levels, their characteristics in spatio-temporal domains, and their trends over Pakistan, is the first of its kind. Results will be helpful to the Ministry of Climate Change (Government of Pakistan), Pak-EPA, SUPARCO (Pakistan Space and Upper Atmosphere Research Commission), policymakers, and the local research community to mitigate air pollution and its effects on human health.

Muhammad Bilal↗
NASA NTRS2022

Simultaneous Characterization of Wildfire Smoke and Surface Properties With Imaging Spectroscopy During the FIREX-AQ Field Campaign

We introduce and evaluate an approach for the simultaneous retrieval of aerosol and surface properties from Airborne Visible/Infrared Imaging Spectrometer Classic (AVIRIS-C) data collected during wildfires. The joint National Aeronautics and Space Administration (NASA) National Oceanic and Atmospheric Administration Fire Influence on Regional to Global Environments and Air Quality field campaign took place in August 2019, and involved two aircraft and coordinated ground-based observations. The AVIRIS-C instrument acquired data from onboard NASA's high altitude ER-2 research aircraft, coincident in space and time with aerosol observations obtained from the Aerosol Robotic Network (AERONET) DRAGON mobile platform in the smoke plume downwind of the Williams Flats Fire in northern Washington in August 2019. Observations in this smoke plume were used to assess the capacity of optimal-estimation based retrievals to simultaneously estimate aerosol optical depth (AOD) and surface reflectance from Visible Shortwave Infrared (VSWIR) imaging spectroscopy. Radiative transfer modeling of the sensitivities in spectral information collected over smoke reveal the potential capacity of high spectral resolution retrievals to distinguish between sulfate and smoke aerosol models, as well as sensitivity to the aerosol size distribution. Comparison with ground-based AERONET observations demonstrates that AVIRIS-C retrievals of AOD compare favorably with direct sun AOD measurements. Our analyses suggest that spectral information collected from the full VSWIR spectral interval, not just the shortest wavelengths, enables accurate retrievals. We use this approach to continuously map both aerosols and surface reflectance at high spatial resolution across heterogeneous terrain, even under relatively high AOD conditions associated with wildfire smoke.

FIREX-AQ↗
NASA NTRS2002

Impact of lossy compression on diagnostic accuracy of radiographs for periapical lesions

OBJECTIVES: The purpose of this study was to evaluate the lossy Joint Photographic Experts Group compression for endodontic pretreatment digital radiographs. STUDY DESIGN: Fifty clinical charge-coupled device-based, digital radiographs depicting periapical areas were selected. Each image was compressed at 2, 4, 8, 16, 32, 48, and 64 compression ratios. One root per image was marked for examination. Images were randomized and viewed by four clinical observers under standardized viewing conditions. Each observer read the image set three times, with at least two weeks between each reading. Three pre-selected sites per image (mesial, distal, apical) were scored on a five-scale score confidence scale. A panel of three examiners scored the uncompressed images, with a consensus score for each site. The consensus score was used as the baseline for assessing the impact of lossy compression on the diagnostic values of images. The mean absolute error between consensus and observer scores was computed for each observer, site, and reading session. RESULTS: Balanced one-way analysis of variance for all observers indicated that for compression ratios 48 and 64, there was significant difference between mean absolute error of uncompressed and compressed images (P <.05). After converting the five-scale score to two-level diagnostic values, the diagnostic accuracy was strongly correlated (R (2) = 0.91) with the compression ratio. CONCLUSION: The results of this study suggest that high compression ratios can have a severe impact on the diagnostic quality of the digital radiographs for detection of periapical lesions.

NASA Discipline Space Human Factors↗
NASA NTRS2008

Advanced Land Imager Assessment System

The Advanced Land Imager Assessment System (ALIAS) supports radiometric and geometric image processing for the Advanced Land Imager (ALI) instrument onboard NASA s Earth Observing-1 (EO-1) satellite. ALIAS consists of two processing subsystems for radiometric and geometric processing of the ALI s multispectral imagery. The radiometric processing subsystem characterizes and corrects, where possible, radiometric qualities including: coherent, impulse; and random noise; signal-to-noise ratios (SNRs); detector operability; gain; bias; saturation levels; striping and banding; and the stability of detector performance. The geometric processing subsystem and analysis capabilities support sensor alignment calibrations, sensor chip assembly (SCA)-to-SCA alignments and band-to-band alignment; and perform geodetic accuracy assessments, modulation transfer function (MTF) characterizations, and image-to-image characterizations. ALIAS also characterizes and corrects band-toband registration, and performs systematic precision and terrain correction of ALI images. This system can geometrically correct, and automatically mosaic, the SCA image strips into a seamless, map-projected image. This system provides a large database, which enables bulk trending for all ALI image data and significant instrument telemetry. Bulk trending consists of two functions: Housekeeping Processing and Bulk Radiometric Processing. The Housekeeping function pulls telemetry and temperature information from the instrument housekeeping files and writes this information to a database for trending. The Bulk Radiometric Processing function writes statistical information from the dark data acquired before and after the Earth imagery and the lamp data to the database for trending. This allows for multi-scene statistical analyses.

Chander, Gyanesh↗
NASA NTRS2015

NASA COAST and OCEANIA Airborne Missions in Support of Ecosystem and Water Quality Research in the Coastal Zone

Worldwide, coastal marine ecosystems are exposed to land-based sources of pollution and sedimentation from anthropogenic activities including agriculture and coastal development. Ocean color products from satellite sensors provide information on chlorophyll (phytoplankton pigment), sediments, and colored dissolved organic material. Further, ship-based in-water measurements and emerging airborne measurements provide in situ data for the vicarious calibration of current and next generation satellite ocean color sensors and to validate the algorithms that use the remotely sensed observations. Recent NASA airborne missions over Monterey Bay, CA, have demonstrated novel above- and in-water measurement capabilities supporting a combined airborne sensor approach (imaging spectrometer, microradiometers, and a sun photometer). The results characterize coastal atmospheric and aquatic properties through an end-to-end assessment of image acquisition, atmospheric correction, algorithm application, plus sea-truth observations from state-of-the-art instrument systems. The primary goal of the airborne missions was to demonstrate the following in support of calibration and validation exercises for satellite coastal ocean color products: 1) the utility of a multi-sensor airborne instrument suite to assess the bio-optical properties of coastal California, including water quality; and 2) the importance of contemporaneous atmospheric measurements to improve atmospheric correction in the coastal zone. Utilizing an imaging spectrometer optimized in the blue to green spectral domain enables higher signal for detection of the relatively dark radiance measurements from marine and freshwater ecosystem features. The novel airborne instrument, Coastal Airborne In-situ Radiometers (C-AIR) provides measurements of apparent optical properties with high dynamic range and fidelity for deriving exact water leaving radiances at the land-ocean boundary, including radiometrically shallow aquatic ecosystems. Simultaneous measurements supporting empirical atmospheric correction of image data were accomplished using the Ames Airborne Tracking Sunphotometer (AATS-14). Flight operations are presented for the instrument payloads using the CIRPAS Twin Otter flown over Monterey Bay during the seasonal fall algal bloom in 2011 (COAST) and 2013 (OCEANIA) to support bio-optical measurements of phytoplankton for coastal zone research. Further, this airborne capability can be responsive to first flush rain events that deliver higher concentrations of sediments and pollution to coastal waters via watersheds and overland flow.

Airborne Equipment↗
NASA NTRSDate not supplied

Performance Assessment of the NOAA-20 VIIRS RSB Using Deep Convective Clouds

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the NOAA-20 (N20) satellite was launched on November 18, 2017. The N20 VIIRS reflective solar bands (RSBs) are calibrated on-orbit using a solar diffuser. An accurate on-orbit calibration is crucial to the high-quality downstream products facilitating atmosphere, ocean and land applications. In this study, the stability of the Level 1B (L1B) reflectance product is investigated using measurements over deep convective clouds (DCCs) for M-bands M1-M5, M7-M11, and I-bands I1-I3. The methodologies developed previously for Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors and Suomi National Polar-orbiting Partnership (SNPP) VIIRS are extended and applied to the N20 RSB to derive DCC-based trends. The Collection 2 L1B data produced by NASA Land Science Investigator-led Processing Systems (SIPS) is used to evaluate the performance of the N20 VIIRS RSB calibration. At nadir, the reflectance trends for M1, M5, M8-M11, and I3 are insignificant compared to their corresponding variations (STDs) except for bands M2-M4, M7, and I1-I2, whose trends are larger than or equivalent to their STDs. The reflectance is relatively stable compared to their STDs for all the study RSBs at six aggregation zones across the entire scan angle range. Also discussed in this paper are the detector-to-detector differences and half-angle mirror side differences using the DCCs. Future applications using DCCs, which include an intercomparison with SNPP VIIRS, are also discussed.

N20 VIIRS↗