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NASA NTRS2008

Potential of VIIRS Time Series Data for Aiding the USDA Forest Service Early Warning System for Forest Health Threats: A Gypsy Moth Defoliation Case Study

The Healthy Forest Restoration Act of 2003 mandated that a national forest threat Early Warning System (EWS) be developed. The USFS (USDA Forest Service) is currently building this EWS. NASA is helping the USFS to integrate remotely sensed data into the EWS, including MODIS data for monitoring forest disturbance at broad regional scales. This RPC experiment assesses the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) and MODIS (Moderate Resolution Imaging Spectroradiometer) data for contribution to the EWS. In doing so, the RPC project employed multitemporal simulated VIIRS and MODIS data for detecting and monitoring forest defoliation from the non-native Eurasian gypsy moth (Lymantria despar). Gypsy moth is an invasive species threatening eastern U.S. hardwood forests. It is one of eight major forest insect threats listed in the Healthy Forest Restoration Act of 2003. This RPC experiment is relevant to several nationally important mapping applications, including carbon management, ecological forecasting, coastal management, and disaster management

Spruce, Joseph P.↗

NASA NTRS2011

Comparison of VIIRS Prelaunch RVS Among Independent Studies

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key sensor carried on the NPOESS (National Polar-orbiting Operational Environmental Satellite System), upgraded and developed recently from heritage instruments including AVHRR, OLS, MODIS, and SeaWiFS. It has on-board calibration components including a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) for the reflective solar bands (RSB), a V-groove blackbody for the thermal emissive bands (TEB), and a space view (SV) port for background subtraction. These on-board calibrators are located at fixed scan angles. The VIIRS response versus scan angle (RVS) was characterized prelaunch in lab ambient conditions and will be used on-orbit to characterize the response for the all scan angles relative to the calibrator scan angle (SD for RSB and blackbody for TEB). Since the RVS is vitally important to the quality of calibrated radiance products, several independent studies were performed and their results were compared and validated. This document provides RVS results from three groups: the NPP Instrument Calibration Support Team (NICST), Raytheon, and the Aerospace Corporation. A comparison of the RVS results obtained using a 2nd order polynomial fit to measurement data is conducted for each band, detector, and half angle mirror (HAM) side. The associated RVS fitting residuals are examined and compared with the relative differences in RVS found between independent studies. Results show that the agreement is within 0.1% and comparable with fitting residuals for all bands except for RSB band M9, where a difference of 0.2% results from the application of the atmospheric water vapor correction for laboratory conditions during the test by Raytheon. NICST has slightly larger RSB RVS uncertainties but still well within the 0.3% total uncertainty allowed for the RVS characterization defined in the Performance Verification Plan.

Wu, Aisheng↗

NASA NTRS2011

A Maximum Likelihood Approach to Determine Sensor Radiometric Response Coefficients for NPP VIIRS Reflective Solar Bands

Optical sensors aboard Earth orbiting satellites such as the next generation Visible/Infrared Imager/Radiometer Suite (VIIRS) assume that the sensors radiometric response in the Reflective Solar Bands (RSB) is described by a quadratic polynomial, in relating the aperture spectral radiance to the sensor Digital Number (DN) readout. For VIIRS Flight Unit 1, the coefficients are to be determined before launch by an attenuation method, although the linear coefficient will be further determined on-orbit through observing the Solar Diffuser. In determining the quadratic polynomial coefficients by the attenuation method, a Maximum Likelihood approach is applied in carrying out the least-squares procedure. Crucial to the Maximum Likelihood least-squares procedure is the computation of the weight. The weight not only has a contribution from the noise of the sensor s digital count, with an important contribution from digitization error, but also is affected heavily by the mathematical expression used to predict the value of the dependent variable, because both the independent and the dependent variables contain random noise. In addition, model errors have a major impact on the uncertainties of the coefficients. The Maximum Likelihood approach demonstrates the inadequacy of the attenuation method model with a quadratic polynomial for the retrieved spectral radiance. We show that using the inadequate model dramatically increases the uncertainties of the coefficients. We compute the coefficient values and their uncertainties, considering both measurement and model errors.

Lei, Ning↗

NASA NTRS2011

NPP VIIRS Geometric Performance Status

Visible Infrared Imager Radiometer Suite (VIIRS) instrument on-board the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) satellite is scheduled for launch in October, 2011. It is to provide satellite measured radiance/reflectance data for both weather and climate applications. Along with radiometric calibration, geometric characterization and calibration of Sensor Data Records (SDRs) are crucial to the VIIRS Environmental Data Record (EDR) algorithms and products which are used in numerical weather prediction (NWP). The instrument geometric performance includes: 1) sensor (detector) spatial response, parameterized by the dynamic field of view (DFOV) in the scan direction and instantaneous FOV (IFOV) in the track direction, modulation transfer function (MTF) for the 17 moderate resolution bands (M-bands), and horizontal spatial resolution (HSR) for the five imagery bands (I-bands); 2) matrices of band-to-band co-registration (BBR) from the corresponding detectors in all band pairs; and 3) pointing knowledge and stability characteristics that includes scan plane tilt, scan rate and scan start position variations, and thermally induced variations in pointing with respect to orbital position. They have been calibrated and characterized through ground testing under ambient and thermal vacuum conditions, numerical modeling and analysis. This paper summarizes the results, which are in general compliance with specifications, along with anomaly investigations, and describes paths forward for characterizing on-orbit BBR and spatial response, and for improving instrument on-orbit performance in pointing and geolocation.

Lin, Guoqing↗

NASA NTRS2011

Post-Launch Calibration Support for VIIRS Onboard NASA NPP Spacecraft

The NPP Instrument Calibration Support Element (NICSE) is one of the elements within the NASA NPP Science Data Segment (SDS). The primary responsibility of NICSE is to independently monitor and evaluate on-orbit radiometric and geometric performance of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument and to validate its Sensor Data Record (SDR) [1]. The NICSE interacts and works closely with other SDS Product Evaluation and Analysis Tools Elements (PEATE) and the NPP Science Team (ST) and supports their on-orbit data product calibration and validation efforts. The NICSE also works closely with the NPP Instrument Calibration Support Team (NICST) during sensor pre-launch testing in ambient and thermal vacuum environment [2]. This paper provides an overview of NICSE VIIRS sensor post-launch calibration support with a focus on the use of sensor on-board calibrators (OBC) for the radiometric calibration and characterization. It presents the current status of NICSE post-launch radiometric calibration tool development effort based on its design requirements

Xiong, Xiaoxion↗

NASA NTRS2012

Early Transition and Use of VIIRS and GOES-R Products by NWS Forecast Offices

The Visible Infrared Imaging Radiometer Suite (VIIRS) on the NPOESS Preparatory Project (NPP) satellite, part of the Joint Polar Satellite System (JPSS), and the ABI and GLM sensors scheduled for the GOES-R geostationary satellite will bring advanced observing capabilities to the operational weather community. The NASA Short-term Prediction Research and Transition (SPoRT) project at Marshall Space Flight Center has been facilitating the use of real-time experimental and research satellite data by NWS Weather Forecast Offices (WFOs) for a number of years to demonstrate the planned capabilities of future sensors to address particular forecast challenges through improve situational awareness and short-term weather forecasts. For the NOAA GOES-R Proving Ground (PG) activity, SPoRT is developing and disseminating selected GOES-R proxy products to collaborating WFOs and National Centers. SPoRT developed the a pseudo-Geostationary Lightning Mapper product and helped in the transition of the Algorithm Working Group (AWG) Convective Initiation (CI) proxy product for the Hazardous Weather Testbed (HWT) Spring Experiment,. Along with its partner WFOs, SPoRT is evaluating MODIS/GOES Hybrid products, which brings ABI-like data sets from existing NASA instrumentation in front of the forecaster for everyday use. The Hybrid uses near real-time MODIS imagery to demonstrate future ABI capabilities, while utilizing standard GOES imagery to provide the temporal frequency of geostationary imagery expected by operational forecasters. In addition, SPoRT is collaborating with the GOES-R hydrology AWG to transition a baseline proxy product for rainfall rate / quantitative precipitation estimate (QPE) to the OCONUS regions. For VIIRS, SPoRT is demonstrating multispectral observing capabilities and the utility of low-light channels not previously available on operational weather satellites to address a variety of weather forecast challenges. This presentation will discuss the results of transitioning these products to collaborating WFOs throughout the country.

Fuell, Kevin K.↗

NASA NTRS2012

NPP VIIRS Early On-Orbit Geometric Performance

The NASA/NOAA Visible Infrared Imager Radiometer Suite (VIIRS) instrument on-board the Suomi National Polar-orbiting Partnership (NPP) satellite was launched in October, 2011. The instrument geometric performance includes sensor spatial response, band-to-band co-registration (BBR), and geolocation accuracy and precision. The geometric performance is an important aspect of sensor data record (SDR) calibration and validation. In this paper we will discuss geometric performance parameter characterization using the first seven-month of VIIRS' earth and lunar data, and compare with the at-launch performance using ground testing data and analysis of numerical modeling results as the first step in on-orbit geometric calibration and validation.

Wolfe, Robert E.↗

NASA NTRS2012

Analysis of Suomi - NPP VIIRS Vignetting Functions Based on Yaw Maneuver Data

The Suomi NPP Visible Infrared Imager Radiometer Suite (VIIRS) reflective bands are calibrated on-orbit via reference to regular solar observations through a solar attenuation screen (SAS) and diffusely reflected off a Spectralon (Registered Trademark) panel. The degradation of the Spectralon panel BRDF due to UV exposure is tracked via a ratioing radiometer (SDSM) which compares near simultaneous observations of the panel with direct observations of the sun (through a separate attenuation screen). On-orbit, the vignetting functions of both attenuation screens are most easily measured when the satellite performs a series of yaw maneuvers over a short period of time (thereby covering the yearly angular variation of solar observations in a couple of days). Because the SAS is fixed, only the product of the screen transmission and the panel BRDF was measured. Moreover, this product was measured by both VIIRS detectors as well as the SDSM detectors (albeit at different reflectance angles off the Spectralon panel). The SDSM screen is also fixed; in this case, the screen transmission was measured directly. Corrections for instrument drift and degradation, solar geometry, and spectral effects were taken into consideration. The resulting vignetting functions were then compared to the pre-launch measurements as well as models based on screen geometry.

Xiong, Xiaoxiong↗

NASA NTRS2012

Initial On-Orbit Radiometric Calibration of the Suomi NPP VIIRS Reflective Solar Bands

The on-orbit radiometric response calibration of the VISible/Near InfraRed (VISNIR) and the Short-Wave InfraRed (SWIR) bands of the Visible/Infrared Imager/Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (NPP) satellite is carried out through a Solar Diffuser (SD). The transmittance of the SD screen and the SD's Bidirectional Reflectance Distribution Function (BRDF) are measured before launch and tabulated, allowing the VIIRS sensor aperture spectral radiance to be accurately determined. The radiometric response of a detector is described by a quadratic polynomial of the detector?s digital number (dn). The coefficients were determined before launch. Once on orbit, the coefficients are assumed to change by a common factor: the F-factor. The radiance scattered from the SD allows the determination of the F-factor. In this Proceeding, we describe the methodology and the associated algorithms in the determination of the F-factors and discuss the results.

Lei, Ning↗

NASA NTRS2012

Characterization of NPP Visible/Infrared Imager Radiometer Suite (VIIRS) Reflective Solar Bands Dual Gain Anomaly

The Visible/Infrared Imager Radiometer Suite (VIIRS) contains six dual gain bands in the reflective solar spectrum. The dual gain bands are designed to switch gain mode at pre-defined thresholds to achieve high resolution at low radiances while maintaining the required dynamic range for science. During pre-launch testing, an anomaly in the electronic response before transitioning from high to low gain was discovered and characterized. On-orbit, the anomaly was confirmed using MODIS data collected during Simultaneous Nadir Overpasses (SNOs). The analysis of the Earth scene data shows that dual gain anomaly can be determined at the orbital basis. To characterize the dual gain anomaly, the anomaly region and electronic offsets were tracked per week during the first 8 month of VIIRS operation. The temporal analysis shows the anomaly region can drift ~20 DN and is impacted by detectors DC Restore. The estimated anomaly flagging regions cover ~2.5 % of the high gain dynamic range and are consistent with prelaunch and on-orbit LUT. The prelaunch results had a smaller anomaly range (30-50 DN) and are likely the results of more stable electronics from the shorter data collection time. Finally, this study suggests future calibration efforts to focus on the anomaly's impact on science products and possible correction method to reduce uncertainties.

Lee, Shihyan↗

NASA NTRS2012

VIIRS On-Orbit Optical Anomaly - Investigation, Analysis, Root Cause Determination and Lessons Learned

A gradual, but persistent, decrease in the optical throughput was detected during the early commissioning phase for the Suomi National Polar-Orbiting Partnership (SNPP) Visible Infrared Imager Radiometer Suite (VIIRS) Near Infrared (NIR) bands. Its initial rate and unknown cause were coincidently coupled with a decrease in sensitivity in the same spectral wavelength of the Solar Diffuser Stability Monitor (SDSM) raising concerns about contamination or the possibility of a system-level satellite problem. An anomaly team was formed to investigate and provide recommendations before commissioning could resume. With few hard facts in hand, there was much speculation about possible causes and consequences of the degradation. Two different causes were determined as will be explained in this paper. This paper will describe the build and test history of VIIRS, why there were no indicators, even with hindsight, of an on-orbit problem, the appearance of the on-orbit anomaly, the initial work attempting to understand and determine the cause, the discovery of the root cause and what Test-As-You-Fly (TAYF) activities, can be done in the future to greatly reduce the likelihood of similar optical anomalies. These TAYF activities are captured in the lessons learned section of this paper.

Iona, Glenn↗

NASA NTRS2012

Evaluation and Validation of Global Land Surface Products Derived from Landsat, MODIS, and VIIRS

Data at medium and coarse resolution from the Landsat, MODIS, and VIIRS instruments provide crucial and indispensable time-series for the land component of the study of global change. This talk will be divided into two main sections. In the first part, a summary of the status of the processing, archiving, and early (Launch +6 months) on-orbit evaluation of the VIIRS Land Environmental Data Records (EDRs), will be presented. In the second part, results from an uncertainty analysis of MODIS- and Landsat-based albedo retrievals, based on collocated comparisons with tower and airborne multiangular measurements collected at the Cloud and Radiation Testbed (CART) site during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC'07), will be discussed.

Roman, Miguel O.↗

NASA NTRS2015

A Bispectral Composite Threshold Approach for Automatic Cloud Detection in VIIRS Imagery

The detection of clouds in satellite imagery has a number of important applications in weather and climate studies. The presence of clouds can alter the energy budget of the Earth‐atmosphere system through scattering and absorption of shortwave radiation and the absorption and re‐emission of infrared radiation at longer wavelengths. The scattering and absorption characteristics of clouds vary with the microphysical properties of clouds, hence the cloud type. Thus, detecting the presence of clouds over a region in satellite imagery is important in order to derive atmospheric or surface parameters that give insight into weather and climate processes. For many applications however, clouds are a contaminant whose presence interferes with retrieving atmosphere or surface information. In these cases, is important to isolate cloud‐free pixels, used to retrieve atmospheric thermodynamic information or surface geophysical parameters, from cloudy ones. This abstract describes an application of a two‐channel bispectral composite threshold (BCT) approach applied to VIIRS imagery. The simplified BCT approach uses only the 10.76 and 3.75 micrometer spectral channels from VIIRS in two spectral tests; a straight‐forward infrared threshold test with the longwave channel and a shortwave - longwave channel difference test. The key to the success of this approach as demonstrated in past applications to GOES and MODIS data is the generation of temporally and spatially dependent thresholds used in the tests from a previous number of days at similar observations to the current data. The paper and subsequent presentation will present an overview of the approach and intercomparison results with other satellites, methods, and against verification data.

LaFontaine Frank J.↗

NASA NTRS2015

Retrieving the Height of Smoke and Dust Aerosols by Synergistic Use of VIIRS, OMPS, and CALIOP Observations

Aerosol Single scattering albedo and Height Estimation (ASHE) algorithm was first introduced in Jeong and Hsu (2008) to provide aerosol layer height as well as single scattering albedo (SSA) for biomass burning smoke aerosols. One of the advantages of this algorithm was that the aerosol layer height can be retrieved over broad areas, which had not been available from lidar observations only. The algorithm utilized aerosol properties from three different satellite sensors, i.e., aerosol optical depth (AOD) and Ångström exponent (AE) from Moderate Resolution Imaging Spectroradiometer (MODIS), UV aerosol index (UVAI) from Ozone Monitoring Instrument (OMI), and aerosol layer height from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Here, we extend the application of the algorithm to Visible Infrared Imaging Radiometer Suite (VIIRS) and Ozone Mapping and Profiler Suite (OMPS) data. We also now include dust layers as well as smoke. Other updates include improvements in retrieving the AOD of nonspherical dust from VIIRS, better determination of the aerosol layer height from CALIOP, and more realistic input aerosol profiles in the forward model for better accuracy.

aerosol↗

NASA NTRS2016

Functional Form of the Radiometric Equation for the SNPP VIIRS Reflective Solar Bands: An Initial Study

The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite is a passive scanning radiometer and an imager, observing radiative energy from the Earth in 22 spectral bands from 0.41 to 12 microns which include 14 reflective solar bands (RSBs). Extending the formula used by the Moderate Resolution Imaging Spectroradiometer instruments, currently the VIIRS determines the sensor aperture spectral radiance through a quadratic polynomial of its detector digital count. It has been known that for the RSBs the quadratic polynomial is not adequate in the design specified spectral radiance region and using a quadratic polynomial could drastically increase the errors in the polynomial coefficients, leading to possible large errors in the determined aperture spectral radiance. In addition, it is very desirable to be able to extend the radiance calculation formula to correctly retrieve the aperture spectral radiance with the level beyond the design specified range. In order to more accurately determine the aperture spectral radiance from the observed digital count, we examine a few polynomials of the detector digital count to calculate the sensor aperture spectral radiance.

Lei, Ning↗

NASA NTRS2016

S-NPP VIIRS Calibration and Performance Update

The first VIIRS instrument has successfully operated for more than 4 years on-board the Suomi-National Polar-orbiting Partnership (S-NPP) spacecraft. The sensor data records (SDR) derived from VIIRS on-orbit observations have been used to produce many environment data records (EDR), enabling a wide range of applications by the users from operational and research community. This paper provides an overview of instrument operations and its calibration activities, and presents an update of its radiometric performance, in terms of on-orbit changes in sensor spectral band responses and noise characterization. It also describes the effort made to improve sensor calibration, and the strategies developed in support of producing consistent SDR and, consequently, the EDR with improved quality.

Xiong, X.↗

NASA NTRS2017

Products of the SNPP VIIRS SD Screen Transmittance and the SD BRDFs From Both Yaw Maneuver and Regular On-Orbit Data

To ensure data quality, the Earth-observing Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership satellite regularly performs on-orbit radiometric calibration of its 22 spectral bands. The primary radiance source for the calibration of the VIIRS reflective solar bands (RSBs) is a sunlit onboard solar diffuser (SD).During the calibration process, sunlight goes through a perforated plate (the SD screen) and then strikes the SD. The sunlight, scattered off the SD of near-Lambertian property, is used for the calibration. Consequently, the spectral radiance of the scattered sunlight is proportional to the product of the SD screen transmittance and the SD bidirectional reflectance distribution function (BRDF) value at the observation direction. The BRDF value is decomposed to the product of its initial value at launch and a numerical degradation factor that quantifies the decrease from the initial value. The degradation factor is determined by an onboard SD stability monitor (SDSM). During the BRDF degradation factor determination process, the SDSM receives the SD scattered sunlight and the sunlight that goes through another perforated plate at almost the same time. The ratio of the signal strengths from the two observations is used to determine the BRDF degradation factor. Consequently, the RSB radiometric calibration requires the accurate knowledge of the product of the SD screen transmittance and the initial BRDF value as sensed by the RSB and the SDSM detectors. We use both yaw maneuver and a small portion of regular on-orbit data to determine the products.

Lei, Ning↗

NASA NTRS2016

Using Ground Targets to Validate S-NPP VIIRS Day-Night Band Calibration

In this study, the observations from S-NPP VIIRS Day-Night band (DNB) and Moderate resolution bands (M bands) of Libya 4 and Dome C over the first four years of the mission are used to assess the DNB low gain calibration stability. The Sensor Data Records produced by NASA Land Product Evaluation and Algorithm Testing Element (PEATE) are acquired from nearly nadir overpasses for Libya 4 desert and Dome C snow surfaces. A kernel-driven bidirectional reflectance distribution function (BRDF) correction model is used for both Libya 4 and Dome C sites to correct the surface BRDF influence. At both sites, the simulated top-of-atmosphere (TOA) DNB reflectances based on SCIAMACHY spectral data are compared with Land PEATE TOA reflectances based on modulated Relative Spectral Response (RSR). In the Libya 4 site, the results indicate a decrease of 1.03% in Land PEATE TOA reflectance and a decrease of 1.01% in SCIAMACHY derived TOA reflectance over the period from April 2012 to January 2016. In the Dome C site, the decreases are 0.29% and 0.14%, respectively. The consistency between SCIAMACHY and Land PEATE data trends is good. The small difference between SCIAMACHY and Land PEATE derived TOA reflectances could be caused by changes in the surface targets, atmosphere status, and on-orbit calibration. The reflectances and radiances of Land PEATE DNB are also compared with matching M bands and the integral M bands based on M4, M5, and M7. The fitting trends of the DNB to integral M bands ratios indicate a 0.75% decrease at the Libya 4 site and a 1.89% decrease at the Dome C site. Part of the difference is due to an insufficient number of sampled bands available within the DNB wavelength range. The above results indicate that the Land PEATE VIIRS DNB product is accurate and stable. The methods used in this study can be used on other satellite instruments to provide quantitative assessments for calibration stability.

Chen, Xuexia↗