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Leveraging the Power of SAR Observations for Forest Monitoring Systems

Earth observations from Synthetic Aperture Radar (SAR) can provide unique information related to forest structure and condition. Despite the many advantages of SAR, particularly where clouds impede optical observations, a knowledge gap has prevented the applied remote sensing community from harnessing its full potential. Here, we discuss the results of a collaboration between SERVIR, a joint program between NASA and the U.S. Agency for International Development (USAID), and SilvaCarbon, the United States' contribution to the Global Forest Observation Initiative, to build global capacity in using SAR for forest monitoring and biomass estimation. This includes primarily the creation of 1) The SAR Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation, 2) a series of international hands-on trainings and training materials, 3) quick-reference guides illustrating SAR concepts, and 4) animated videos explaining how SAR works. The SERVIR-Global community joined efforts to develop a hands-on guide to support decision-makers in the forestry community to leverage the power of SAR technology to better protect and manage forest resources. We worked with world-renowned SAR experts to provide targeted trainings and develop the SAR Handbook. This handbook consists of approachable theoretical background and applied content that contributes to filling the knowledge gap in the applied use of SAR technology for forestry applications. We hope that forest managers and remote sensing specialists will use these materials to benefit from currently available SAR datasets, as well as prepare for future SAR missions, such as NISAR and BIOMASS. Since its release on April 11, 2019, the SAR Handbook has been accessed more than 100,000 times in less than a month, demonstrating the remote sensing community's urgent need and interest to learn and use SAR.

Herndon, Kelsey E.↗

SAGE III ISS Contamination Monitoring Package: Observations in Orbit

The Stratospheric Aerosol and Gas Experiment III (SAGE III) telescope and instrument assembly employ the methods of solar occultation and lunar occultation to retrieve near-global vertical profiles of atmospheric ozone, water vapor, nitrogen dioxide, aerosol extinctions, and other gaseous species and atmospheric state parameters. The SAGE III grating spectrometer measures light within the spectral range of 280 nm to 1037 nm at approximately 1 nm resolution, but retrievals in the Ultraviolet (UV) are particularly sensitive to contamination of the optical train. Therefore, a contamination door that contains a quartz optical window can be closed over the telescope aperture during periods of enhanced external contaminant flux. This optically transparent window permits continued science event acquisition at an acceptably diminished signal-to-noise ratio, which is expected to decline with ongoing accretion of contaminant material. To date, this impact has been short term, and science quality through the window returns to baseline performance after a contamination source is removed and spontaneous desorption removes material from the low-affinity quartz surface. Two Contamination Monitoring Packages (CMPs) consisting of eight Thermoelectric Quartz Crystal Microbalances (TQCMs) from QCM Research provide characterization and redundant monitoring of contaminant deposition from the 2π steradian solid angle on the payload side of the Expedite the Processing of Experiments to the Space Station (ExPRESS) Payload Adapter. CMP data are closely examined by the SAGE III team to determine when the contamination door should remain closed during science events and in what direction the instrument assembly scan head should stow when not acquiring science measurements. Additionally, should the CMPs indicate an unacceptable accretion rate, the ight computer will close the contamination door as part of the automatic fault detection system. Along with spectrometer measurements of the quartz window's transmission, the payload CMPs enable auditing of the mission contamination budget. The process of Thermogravimetric Analysis (TGA) can be used to help identify chemical constituents accreted on the CMP sensors. To be presented here along with an explanation of the CMP systems are the first two and a half years of observations of the contaminant deposition environment around the payload in quiescence and during special events like docking vehicles.

Tyler T Dawson↗

Monitoring River Basin Development and Variation in Water Resources in Transboundary Imjin River in North and South Korea Using Remote Sensing

This paper presents methods of monitoring river basin development and water variability for the transboundary river in North and South Korea. River basin development, such as dams and water infrastructure in transboundary rivers, can be a potential factor of tensions between upstream and downstream countries since dams constructed upstream can adversely affect downstream riparians. However, because most of the information related to North Korea has been limited to the public, the information about dams constructed and their locations were inaccurate in many previous studies. In addition, water resources in transboundary rivers can be exploited as a political tool. Specifically, due to the unexpected water release from the Hwanggang Dam, upstream of the transboundary Imjin River in North and South Korea, six South Koreans died on 6 September 2009. The Imjin River can be used as a political tool by North Korea, and seven events were reported as water conflicts in the Imjin River from 2001 to 2016. In this paper, firstly, we have updated the information about the dams constructed over the Imjin River in North Korea using multi-temporal images with a high spatial resolution (15-30 cm) obtained from Google Earth. Secondly, we analyzed inter- and intra-water variability over the Hwanggang Reservoir using open-source images obtained from the Global Surface Water Explorer. We found a considerable change in water surface variability before and after 2008, which might result from the construction of the Hwanggang Dam. Thirdly, in order to further investigate intra-annual water variability, we present a method monitoring water storage changes of the Hwanggang Reservoir using the area-elevation curve (AEC), which was derived from multi-sensor Synthetic Aperture Radar (SAR) images (Sentinel-1A and -1B) and the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM). Since many previous studies for estimating water storage change have depended on satellite altimetry dataset and optical images for deriving AEC, the method adopted in this study is the only application for such inaccessible areas since no altimetry ground track exists for the Hwanggang Reservoir and because clouds can block the study area for wet seasons. Moreover, this study has newly proven that unexpected water release can occur in dry seasons because the water storage in the Hwanggang Reservoir can be high enough to conduct a release that can be used as a geopolitical tool. Using our method, potential risks can be mitigated, not in response to a water release, but based on pre-event water storage changes in the Hwanggang Reservoir.

Kim, Donghwan↗

Design of an Automated Ultrasonic Scanning System for In-Situ Composite Cure Monitoring and Defect Detection

The preliminary design and development of an automated ultrasonic scanning system for in-situ composite cure monitoring and defect detection in the high temperature environment of an oven was completed. This preliminary design is a stepping stone to deployment in the high temperature and high pressure environment of an autoclave, the primary cure method of aerospace grade thermoset composites. Cure monitoring with real-time defect detection during the process could determine when defects form and how they move. In addition, real-time defect detection during cure could assist validating physics-based process models for predicting defects at all stages of the cure cycle. A physics-based process model for predicting porosity and fiber waviness originating during cure is currently under development by the NASA Advanced Composites Project (ACP). For the design, an ultrasonic contact scanner is enclosed in an insulating box that is placed inside an oven during cure. Throughout the cure cycle, the box is nitrogen-cooled to approximately room temperature to maintain a standard operating environment for the scanner. The composite part is mounted on the outside of the box in a vacuum bag on the build/tool plate. The build plate is attached to the bottom surface of the box. The scanner inspects the composite panel through the build plate, tracking the movement of defects introduced during layup and searching for new defects that may form during cure. The focus of this paper is the evaluation and selection of the build plate material and thickness. The selection was based on the required operating temperature of the scanner, the cure temperature of the composite material, thermal conductivity models of the candidate build plates, and a series of ultrasonic attenuation tests. This analysis led to the determination that a 63.5 mm thick build plate of borosilicate glass would be utilized for the system. The borosilicate glass plate was selected as the build plate material due to the low ultrasonic attenuation it demonstrated, its ability to efficiently insulate the scanner while supporting an elevated temperature on the part side of the plate, and the availability of a 63.5 mm thick plate without the need for lamination.

Hudson, Tyler B.↗

Simultaneous Temperature/Pressure Monitoring in Compressible Flows using Hybrid fs/ps Pure-Rotational CARS

We demonstrate simultaneous monitoring of temperature and pressure using a hybrid femtosecond/picosecond pure-rotational CARS technique in a one-dimensional line-imaging configuration. The method employs two detection channels and two 60-ps-duration probe laser beams with independently adjustable time delays from the broadband 35-fs pump/Stokes pulse. Simultaneous temperature and pressure monitoring is demonstrated along the centerline of a canonical under expanded compressible air jet flow emanating from a choked, sonic nozzle. Temperature is measured almost independently of pressure by analyzing CARS spectra obtained with a probe pulse near zero time delay for nearly collision-free acquisition. Pressure is obtained from spectra acquired with long probe time delays to sample the impact of gas-phase collisions. The CARS measurements were obtained in both time-averaged and single-laser-shot mode with 67 μm spatial resolution along the jet axis along a nominally 6-mm line. The measurements span a temperature and pressure range of T= 70-300 K and P= 0.05-1.2atm.

Sean P Kearney↗

GeoNEX: A geostationary earth observatory at NASA Earth eXchange: Earth monitoring from operational geostationary satellite systems

The latest generation of geostationary satellites (Himawari 8/9, GOES-16/17, FY-4, GK-2A) carries sensors that closely mimic the spatial and spectral characteristics of widely used polar-orbiting, global monitoring sensors such as MODIS and VIIRS. When combined, data from various currently operating/planned geostationary platforms provide a geo-ring of hyper-temporal (5-10 minutes), multispectral observations at spatial resolutions as high as 500 m. These high frequency observations offer exciting new possibilities for monitoring our planet, including better retrievals of geophysical variables by overcoming cloud cover, enabling studies of diurnally varying phenomena in the atmosphere, land, and the oceans, and support operational decision-making in agriculture, hydrology and disaster management. The NASA Earth Exchange (NEX) team, in collaboration with scientists from JAXA, KARI, NOAA and other international institutions, created the GeoNEX (www.nasa.gov/geonex) pipeline to integrate data from all available geostationary platforms and produce and distribute spatially, temporally, and radiometrically consistent data for the earth science community. We envision various institutions adapting the Geo component (e.g., GeoNOAA, GeoKARI, GeoChiba, GeoJAXA, GeoCMA) and customizing the pipeline and downstream products to serve the local/regional research and applied science communities.

Ramakrishna R Nemani↗

The Seoul National University AGN Monitoring Project. II. BLR Size and Black Hole Mass of Two AGNs

Active galactic nuclei (AGNs) show a correlation between the size of the broad line region and the monochromatic continuum luminosity at 5100 Å, allowing black hole mass estimation based on single-epoch spectra. However, the validity of the correlation is yet to be clearly tested for high-luminosity AGNs. We present the first reverberation mapping results of the Seoul National University AGN Monitoring Project (SAMP), which is designed to focus on luminous AGNs for probing the high end of the size–luminosity relation. We report time lag measurements of two AGNs, namely, 2MASS J10261389+5237510 and SDSS J161911.24+501109.2, using the light curves obtained over an ~1000 days period with an average cadence of 10 and 20 days, respectively, for photometry and spectroscopy monitoring. Based on a cross-correlation analysis and Hβ line width measurements, we determine the Hβ lag as 41.8(+4.9, -6.0) and 52.6(+17.6, -14.7) days in the observed frame, and black hole mass as 3.65(+0.49,-0.57) X 10 (exp 7) Solar Mass and 23.02(+7.81,-6.56) X 10 (exp 7) Solar Mass, respectively, for 2MASS J1026 and SDSS J1619.

Suvendu Rakshit↗

SAGE III/ISS Contamination Monitoring Package: Observations in Orbit

The Stratospheric Aerosol and Gas Experiment III (SAGE III) telescope and instrument assembly employ the methods of solar occultation and lunar occultation to retrieve near-global vertical profiles of atmospheric ozone, water vapor, nitrogen dioxide, aerosol extinctions, and other gaseous species and atmospheric state parameters. The SAGE III grating spectrometer measures light within the spectral range of 280 nm to 1037 nm at approximately 1 nm resolution, but retrievals in the Ultraviolet (UV) are particularly sensitive to contamination of the optical train. Therefore, a contamination door that contains a quartz optical window can be closed over the telescope aperture during periods of enhanced external contaminant flux. This optically transparent window permits continued science event acquisition at an acceptably diminished signal-to-noise ratio, which is expected to decline with ongoing accretion of contaminant material. To date, this impact has been short term, and science quality through the window returns to baseline performance after a contamination source is removed and spontaneous desorption removes material from the low-affinity quartz surface. Two Contamination Monitoring Packages (CMPs) consisting of eight Thermoelectric Quartz Crystal Microbalances (TQCMs) from QCM Research provide characterization and redundant monitoring of contaminant deposition from the 2pi steradian solid angle on the payload side of the Expedite the Processing of Experiments to the Space Station (ExPRESS) Payload Adapter. CMP data are closely examined by the SAGE III team to determine when the contamination door should remain closed during science events and in what direction the instrument assembly scan head should stow when not acquiring science measurements. Additionally, should the CMPs indicate an unacceptable accretion rate, the flight computer will close the contamination door as part of the automatic fault detection system. Along with spectrometer measurements of the quartz window's transmission, the payload CMPs enable auditing of the mission contamination budget. The process of Thermogravimetric Analysis (TGA) can be used to help identify chemical constituents accreted on the CMP sensors. To be presented here along with an explanation of the CMP systems are the first two and a half years of observations of the contaminant deposition environment around the payload in quiescence and during special events like docking vehicles.

Tyler T Dawson↗

Assured Performance of Additively Manufactured and Composite Parts through Embedded Sensing and Life Cycle Monitoring: An Enabler for in-Space Use

Lightweight composites have a range of applications in aerospace where operational costs and mission (payload) capabilities depend significantly on component weight. Additive manufacturing of the composite components expands the design and production space allowing for complex part geometries. A limiting factor to the utilization of the composites in high value applications, such as aerospace generally, and particularly for in-space applications, is the ability to determine the part quality both at the time of production as well as through the lifetime of the component. Work on monitoring the performance of additively manufactured and autoclaved composites that encompasses the design and manufacturing as well as use in operational environments will be discussed. Optimization of the component design for manufacturability, the use of process monitoring sensors during the component build as well as embedding of carbon nanotube yarn based structural sensors will be described.

Additive Manufacturing↗

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6 reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped over time for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1 reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

water-related ecosystems; surface water extent; ma↗

Modeling the Worst-Case-Scenario of Soil Drydown for Agricultural Drought Monitoring in Kansas Using NASA Earth Observations and In-situ Parameters

Climatologists in Kansas have observed rapid shifts from wet to dry conditions and rapid intensification of drought conditions for the state in recent years. As a leading state in agricultural production, drought events can lead to decreased crop yields and impact the state’s economy. The exponential decay of soil moisture content is a major consequence of drought and can exacerbate these impacts on agricultural production. This study examined the rate of soil moisture drydown in Kansas to understand and monitor the worst-case-scenario of short-term soil water shortage. Soil Moisture Active Passive (SMAP) L-band Radiometer rootzone soil moisture imagery from March 2015 to June 2019 was used to estimate the minimum and maximum soil moisture capacity throughout the state. In situ soil moisture parameters, such as the exponential decay constant, were approximated from the Kansas Mesonet system. These variables were inputs into an exponential decay model that forecasted gridded rootzone soil moisture in a scenario that assumed no precipitation for a user-identified period of time. The forecasts were output on the order of weeks to capture the rapid shifts in soil moisture content. Another model was used to identify areas in Kansas currently below a given percentage of the relative soil moisture saturation, measured as a function of minimum, maximum, and current soil moisture. This model forecasted the number of days until each cell in the soil moisture grid reached the input percentage of relative soil moisture saturation. The gridded model outputs and workflow were developed in partnership with the Kansas Water Office and Kansas Office of the State Climatologist at Kansas State University, as a part of their drought monitoring efforts.

NASA DEVELOP↗

HydroSAR: A Cloud-based SAR Data Analysis Service to Monitor Hydrological Disasters and their Impact on Population and Agriculture

Weather-related hazards are ubiquitous around the world including: 1) hurricane storm surges, 2) rapid snowmelt and heavy rainfall, 3) severe weather leading to flash floods, and 4) seasonal freeze and thaw of rivers that may lead to ice jams. Each of these hazards affects human settlements and has the potential to impact agricultural productivity. In each setting, end-users in disaster management need access to data processing tools helpful in mapping past and current disasters. Analysis of past events supports risk mitigation by understanding what has already occurred and how to alleviate those impacts in the future. Having capabilities to generate the same products in a response setting means that lessons learned from risk analysis will carry forward to event response. Synthetic aperture radar (SAR) data are particularly useful for these activities due to their all-weather 24/7 monitoring capabilities. In this effort we present HydroSAR, a cloud-based SAR data analysis service for the mapping of meteorological and hydrological disasters as well as their impact on population and agriculture. As part of this project we have developed a series of SAR-based value added products for the monitoring of surface hydrology (image time series, change detection, flood extent, flood depth) and the assessment of impacts on population (flood depth) and agriculture (active agriculture, inundated agriculture, flood duration). We also developed a cloud-based platform for generating these products over affected areas and are working with end-users to integrate derived product into decision-making workflows The paper will briefly introduce the SAR-based products that were developed for this effort. We describe the cloud-based production pipeline that was built to automatically generate these products in near-real time over extended regions. The integration of SAR-based information into hazard preparation and response activities is described for a number of recent disasters including the 2019 forest fires in Alaska, 2019 flooding in the U.S. Midwest, the 2020 U.S. severe weather easter outbreak, 2020 tropical storm Christobal, 2020 cyclone Amphan, 2020, Alaska Spring breakup flooding, and the 2020 flood season in Eastern India, Bangladesh, and Nepal.

Franz Josef Meyer↗

Tracking 2020 Decreases in Carbon Dioxide Due to the COVID19 Pandemic in NASA’s GEOS Modeling system: Implications for Space-Based Carbon Monitoring

The COVID19 pandemic led to abrupt, worldwide changes in human activity and related emissions of air pollutants and greenhouse gases that are unprecedented in modern times. NASA satellites have demonstrated their ability to observe some of these impacts, particularly in relation to short-lived gases like nitrogen dioxide (NO2), which is emitted primarily from transportation. Bottom-up analyses of carbon dioxide (CO2) emissions suggest that the growth of atmospheric CO2 has also slowed, but differences are much more subtle than for NO2 because of the lifetime of atmospheric CO2 and sectoral differences in emission reductions. Estimates of CO2 from NASA’s Orbiting Carbon Observatory 2 (OCO-2) provide a unique view of COVID19 impacts, but observed changes in the column-average CO2 can be difficult to interpret because of gaps in spatial coverage. Assimilating these data into the Goddard Earth Observing System (GEOS), an integrated Earth system model with an advanced Constituent Data Assimilation System (CoDAS), helped to reveal changes in CO2 that are consistent with separate, bottom-up analyses of emissions reductions. Both indicate that from February-April of 2020, the growth in CO2 over Europe, North America, and Asia was roughly 0.3 ppm less than during the previous four years. Anomalies derived from gap-filled GEOS OCO-2 CoDAS products contribute to a joint effort by the world’s space agencies to track COVID19 impacts on the Earth. However, attribution of these changes is complicated by interannual variability in atmospheric circulation and the influence of climate on ocean and land carbon sinks. We discuss these results from the perspective of space-based carbon monitoring, which has received considerable support over the past decade from NASA. Our results demonstrate the accomplishments of current sensors and data assimilation systems, but also highlight challenges in providing high quality, low latency information to the public. In particular, understanding and attributing CO2 changes during 2020 requires year-specific information about land and ocean fluxes, which is often delayed for months or even years. We discuss current limitations and potential solutions to address these lags, which would support more reliable and timely space-based carbon monitoring.

COVID-19↗

Improving Drought Monitoring for the Middle East and North Africa Region via Data Assimilation Using the NASA Land Information System (LIS)

Food and water security become an increasingly pressing concern for countries within the Middle East and North Africa (MENA) region under climate change. Droughts are among the most important issues facing this region in both economic and social terms, which have become much more severe in recent decades. An effective drought monitoring and early warning system is, therefore, critical to support drought impact assessment and risk management. This presentation describes the effort to improve the simulation of hydrological conditions for such semi-arid environment by Noah Multi-parameterization Land Surface Model within the NASA Land Information System (LIS) via assimilating remotely sensed leaf area index and soil moisture in the presence of irrigation. Multi-source satellite evapotranspiration products are used to evaluate the model performance under the impact of the choice of met-forcings, the presence of irrigation and data assimilation. The improved model configuration is aimed to deliver a better soil moisture estimation for the composite drought indicator (CDI) for drought monitoring and to provide a better initial condition in support for hydrological drought forecasting.

Wanshu Nie↗

Developing a Hydrological Monitoring and Sub-Seasonal to Seasonal Forecasting System for South and Southeast Asian River Basins

South and Southeast Asia is subject to significant hydrometeorological extremes, including drought. Under rising temperatures, growing populations, and an apparent weakening of the South Asian monsoon in recent decades, concerns regarding drought and its potential impacts on water and food security are on the rise. Reliable sub-seasonal to seasonal (S2S) hydrological forecasts could, in principle, help governments and international organizations to better assess risk and act in the face of an oncoming drought. Here, we leverage recent improvements in S2S meteorological forecasts and the growing power of Earth Observations to provide more accurate monitoring of hydrological states for forecast initialization. Information from both sources is merged in a South and Southeast Asia sub-seasonal to seasonal hydrological forecasting system (SAHFS-S2S), developed collaboratively with the NASA SERVIR program and end-users across the region. This system applies the Noah-MultiParameterization (NoahMP) Land Surface Model (LSM) in the NASA Land Information System (LIS), driven by downscaled meteorological fields from the Global Data Assimilation System (GDAS) and Climate Hazards InfraRed Precipitation products (CHIRP and CHIRPS) to optimize initial conditions. The NASA Goddard Earth Observing System Model - sub-seasonal to seasonal (GEOS-S2S) forecasts, downscaled using the National Center for Atmospheric Research (NCAR) General Analog Regression Downscaling (GARD) tool and quantile mapping, are then applied to drive 5-km resolution hydrological forecasts to a 9-month forecast time horizon. Results show that the skillful predictions of root zone soil moisture can be made one to two months in advance for forecasts initialized in rainy seasons and up to 8 months when initialized in dry seasons. The memory of accurate initial conditions can positively contribute to forecast skills throughout the entire 9-month prediction period in areas with limited precipitation. This SAHFS-S2S has been operationalized at the International Centre for Integrated Mountain Development (ICIMOD) to support drought monitoring and warning needs in the region.

Yifan Zhou↗

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↗

Operations Automation Using the Link Monitor and Control Operator Assistant

The Link Monitor & Control Operator Assistant (LMC OA) is a knowledge-based prototype system which uses Artificial Intelligence (AI) techniques to provide semi-automated monitor and control functions to support operations of the Deep Space Network (DSN) 70-Meter antenna at the Goldstone Deep Space Communications Camplex (DSCC).

Goldstone↗