This PDF file contains the front matter associated with SPIE Proceedings Volume 9972 including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

The Visible/Infrared Imaging Radiometer Suite (VIIRS) is a key sensor on Suomi National Polar-orbiting Partnership (S-NPP) satellite launched on October 28, 2011 into a polar orbit of 824 km nominal altitude and the JPSS sensors currently being built and integrated. VIIRS collects radiometric and imagery data of the Earth’s atmosphere, oceans, and land surfaces in 22 spectral bands spanning the visible and infrared spectrum from 0.4 to 12.5 μm. Interference filters assembled in ‘butcher-block’ arrays mounted adjacent to focal plane arrays provide spectral definition. Out-of-band signal and out-of-band optical cross-talk was observed for bands in the 0.4 to 1 μm range in testing of VIIRS for S-NPP. Optical cross-talk is in-band or out-of-band light incident on an adjacent filter or adjacent region of the same filter reaching the detector. Out-of-band optical cross-talk results in spectral and spatial ‘impurities’ in the signal and consequent errors in the calculated environmental parameters such as ocean color that rely on combinations of signals from more than one band. This paper presents results of characterization, specification, and coating process improvements that enabled production of filters with significantly reduced out of band light for Joint Polar Satellite System (JPSS) J1 and subsequent sensors. Total transmission and scatter measurements at a wavelength within the pass band can successfully characterize filter performance prior to dicing and assembling filters into butcher block assemblies. Coating and process development demonstrated performance on test samples followed by production of filters for J1 and J2. Results for J1 and J2 filters are presented.

The relative spectral response (RSR) characterization of the JPSS-1 VIIRS spectral bands has achieved “at launch” status in the VIIRS Data Analysis Working Group February 2016 Version 2 RSR release. The Version 2 release improves upon the June 2015 Version 1 release by including December 2014 NIST TSIRCUS spectral measurements of VIIRS VisNIR bands in the analysis plus correcting CO2 influence on the band M13 RSR. The T-SIRCUS based characterization is merged with the summer 2014 SpMA based characterization of VisNIR bands (Version 1 release) to yield a “fused” RSR for these bands, combining the strengths of the T-SIRCUS and the SpMA measurement systems. The M13 RSR is updated by applying a model-based correction to mitigate CO2 attenuation of the SpMA source signal that occurred during M13 spectral measurements. The Version 2 release carries forward the Version 1 RSR for those bands that were not updated (M8-M12, M14-M16A/B, I3-I5, DNBMGS). The Version 2 release includes band average (over all detectors and subsamples) RSR plus supporting RSR for each detector and subsample. The at-launch band average RSR have been used to populate Look-Up Tables supporting the sensor data record and environmental data record at-launch science products. Spectral performance metrics show that JPSS-1 VIIRS RSR are compliant on specifications with a few minor exceptions. The Version 2 release, which replaces the Version 1 release, is currently available on the password-protected NASA JPSS-1 eRooms under EAR99 control.

In this work, we describe an improved thermal-vacuum compatible flat plate radiometric source which has been developed and utilized for the characterization and calibration of remote optical sensors. This source is unique in that it can be used in situ, in both ambient and thermal-vacuum environments, allowing it to follow the sensor throughout its testing cycle. The performance of the original flat plate radiometric source was presented at the 2009 SPIE¹. Following the original efforts, design upgrades were incorporated into the source to improve both radiometric throughput and uniformity. The pre-thermal-vacuum (pre-TVAC) testing results of a spacecraft-level optical sensor with the improved flat plate illumination source, both in ambient and vacuum environments, are presented. We also briefly discuss potential FPI configuration changes in order to improve its radiometric performance. Keywords: Calibration, radiometry, remote sensing, source.

Satellite instruments operating in the reflected solar wavelength region require accurate and precise determination of the optical properties of their diffusers used in pre-flight and post-flight calibrations. The majority of recent and current space instruments use reflective diffusers. As a result, numerous Bidirectional Reflectance Distribution Function (BRDF) calibration comparisons have been conducted between the National Institute of Standards and Technology (NIST) and other industry and university-based metrology laboratories. However, based on literature searches and communications with NIST and other laboratories, no Bidirectional Transmittance Distribution Function (BTDF) measurement comparisons have been conducted between National Measurement Laboratories (NMLs) and other metrology laboratories. On the other hand, there is a growing interest in the use of transmissive diffusers in the calibration of satellite, air-borne, and ground-based remote sensing instruments. Current remote sensing instruments employing transmissive diffusers include the Ozone Mapping and Profiler Suite instrument (OMPS) Limb instrument on the Suomi-National Polar-orbiting Partnership (S-NPP) platform,, the Geostationary Ocean Color Imager (GOCI) on the Korea Aerospace Research Institute’s (KARI) Communication, Ocean, and Meteorological Satellite (COMS), the Ozone Monitoring Instrument (OMI) on NASA’s Earth Observing System (EOS) Aura platform, the Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument and the Geostationary Environmental Monitoring Spectrometer (GEMS).. This ensemble of instruments requires validated BTDF measurements of their onboard transmissive diffusers from the ultraviolet through the near infrared. This paper presents the preliminary results of a BTDF comparison between the NASA Diffuser Calibration Laboratory (DCL) and NIST on quartz and thin Spectralon samples.

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission is formulated to determine long-term climate trends using SI-traceable measurements. The CLARREO mission will include instruments operating in the reflected solar (RS) wavelength region from 320 nm to 2300 nm. The Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO and facilitates testing and evaluation of calibration approaches. The basis of CLARREO and SOLARIS calibration is the Goddard Laser for Absolute Measurement of Response (GLAMR) that provides a radiance-based calibration at reflective solar wavelengths using continuously tunable lasers. SI-traceability is achieved via detector-based standards that, in GLAMR’s case, are a set of NIST-calibrated transfer radiometers. A portable version of the SOLARIS, Suitcase SOLARIS is used to evaluate GLAMR’s calibration accuracies. The calibration of Suitcase SOLARIS using GLAMR agrees with that obtained from source-based results of the Remote Sensing Group (RSG) at the University of Arizona to better than 5% (k=2) in the 720-860 nm spectral range. The differences are within the uncertainties of the NIST-calibrated FEL lamp-based approach of RSG and give confidence that GLAMR is operating at <5% (k=2) absolute uncertainties. Limitations of the Suitcase SOLARIS instrument also discussed and the next edition of the SOLARIS instrument (Suitcase SOLARIS- 2) is expected to provide an improved mechanism to further assess GLAMR and CLARREO calibration approaches.

The sole instrument on NASA’s ICESat-2 spacecraft shown in Figure 1 will be the Advanced Topographic Laser Altimeter System (ATLAS)¹. The ATLAS is a Light Detection and Ranging (LIDAR) instrument; it measures the time of flight of the six transmitted laser beams to the Earth and back to determine altitude for geospatial mapping of global ice. The ATLAS laser beam is split into 6 main beams by a Diffractive Optical Element (DOE) that are reflected off of the earth and imaged by an 800 mm diameter Receiver Telescope Assembly (RTA). The RTA is composed of a 2-mirror telescope and Aft Optics Assembly (AOA) that collects and focuses the light from the 6 probe beams into 6 science fibers. Each fiber optic has a field of view on the earth that subtends 83 micro Radians. The light collected by each fiber is detected by a photomultiplier and timing related to a master clock to determine time of flight and therefore distance. The collection of the light from the 6 laser spots projected to the ground allows for dense cross track sampling to provide for slope measurements of ice fields. NASA LIDAR instruments typically utilize telescopes that are not diffraction limited since they function as a light collector rather than imaging function. The more challenging requirements of the ATLAS instrument require better performance of the telescope at the ¼ wave level to provide for improved sampling and signal to noise. NASA Goddard Space Flight Center (GSFC) contracted the build of the telescope to General Dynamics (GD). GD fabricated and tested the flight and flight spare telescope and then integrated the government supplied AOA for testing of the RTA before and after vibration qualification. The RTA was then delivered to GSFC for independent verification and testing over expected thermal vacuum conditions. The testing at GSFC included a measurement of the RTA wavefront error and encircled energy in several orientations to determine the expected zero gravity figure, encircled energy, back focal length and plate scale. In addition, the science fibers had to be aligned to within 10 micro Radians of the projected laser spots to provide adequate margin for operations on-orbit. This paper summarizes the independent testing and alignment of the fibers performed at the GSFC.

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002 and is currently fully operational. AIRS acquires hyperspectral infrared radiances in 2378 channels ranging in wavelength from 3.7-15.4 um with spectral resolution of better than 1200, and spatial resolution of 13.5 km with global daily coverage. The AIRS was designed to measure temperature and water vapor profiles for improvement in weather forecast and improved parameterization of climate processes. Currently the AIRS Level 1B Radiance Products are assimilated by NWP centers worldwide and have shown considerable forecast improvement. Although the calibration of AIRS (< 200 mK 3 sigma) is sufficient for data assimilation into Numerical Weather Prediction (NWP) models, long term trends of Earth’s climate require radiances with stability approaching 10 mK/year, and absolute accuracies better than 100 mK. This investigation uses views of space during roll maneuvers of the Aqua spacecraft to calibrate the mirror emission (one of the largest error sources for AIRS) and reduce the residual errors in cold scenes. We also present results of a secondary study that uses MODIS data to determine the alignment of the AIRS boresight. In this study we match AIRS and MODIS data and iterate on the assumed boresight to find the minimum difference in signal. In this way we are able to confirm the boresight projections determined shortly after launch.

We compare AIRS, IASI-A and CrIS under the cold conditions encountered in the daily overpasses of Dome Concordia, located on a high plateau in Antarctica, between May 2012 and March 2016. The mean brightness temperature at DomeC for the 900 cm^-1 atmospheric window channel is 218K, but it varies seasonally from 185K to 255K. Averaged over all simultaneous overpass data AIRS is 26±13 mK warmer than IASI-A, AIRS is 116±7 mK colder than CrIS. This is excellent agreement and consistent with SNO analysis in the literature. However, we find that differences for both AIRS/IASI-A and AIRS/CrIS are temperature dependent. AIRS is 120 mK colder at 200K, but 150 mK warmer at 230K than IASI-A. AIRS is 120 mK colder at 200K, 50mK colder at 230K than CrIS. Differences and scene temperature sensitivity of this magnitude have also been reported by other investigators. A scene temperature dependence bias can create a sampling bias which need to be taken into account when comparing data from current instruments, and even more so when analyzing data from vintage instruments with respect to climate change.

AIRS on EOS-Aqua and CrIS on Suomi NPP are two hyperspectral infrared sounders with similar capabilities and orbits, so there is a great opportunity to compare their absolute calibration while they are both in orbit. This insures that long-term climate record can be created by concatenating the two instrument records. There are significant differences in instrument architecture which may lead to subtle differences and complicate attempts to combine the records. We use Tropical Simultaneous Nadir Observations (TSNOs), cases where both instruments are looking nearly at the same place at the same time, to explore the differences. Due to the presence of cold clouds and clear hot desert surface, the data cover a brightness temperature range from 190 K to 340 K. We concentrate on the differences between the mean of the two instruments using atmospheric window channels as function of brightness temperature in 20-K wide bins. With the currently available AIRS and CrIS official calibrated data, radiometric differences as large as 0.3 K are seen at the extreme temperatures. These differences may be reduced in future releases of the AIRS and CrIS calibration.

Now in its 17th year of operation, the Enhanced Thematic Mapper + (ETM+), on board the Landsat-7 satellite, continues to systematically acquire imagery of the Earth to add to the 40+ year archive of Landsat data. Characterization of the ETM+ on-orbit radiometric performance has been on-going since its launch in 1999. The radiometric calibration of the reflective bands is still monitored using on-board calibration devices, though the Pseudo-Invariant Calibration Sites (PICS) method has proven to be an effective tool as well. The calibration gains were updated in April 2013 based primarily on PICS results, which corrected for a change of as much as -0.2%/year degradation in the worst case bands. A new comparison with the SADE database of PICS results indicates no additional degradation in the updated calibration. PICS data are still being tracked though the recent trends are not well understood. The thermal band calibration was updated last in October 2013 based on a continued calibration effort by NASA/Jet Propulsion Lab and Rochester Institute of Technology. The update accounted for a 0.036 W/m² sr μm or 0.26K at 300K bias error. The updated lifetime trend is now stable to within +/- 0.4K.

The Landsat Project is planning to implement a new collection management strategy for Landsat products generated at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The goal of the initiative is to identify a collection of consistently geolocated and radiometrically calibrated images across the entire Landsat archive that is readily suitable for time-series analyses. In order to perform an accurate land change analysis, the data from all Landsat sensors must be on the same radiometric scale. Landsat 7 Enhanced Thematic Mapper Plus (ETM+) is calibrated to a radiance standard and all previous sensors are cross-calibrated to its radiometric scale. Landsat 8 Operational Land Imager (OLI) is calibrated to both radiance and reflectance standards independently. The Landsat 8 OLI reflectance calibration is considered to be most accurate. To improve radiometric calibration accuracy of historical data, Landsat 1-7 sensors also need to be cross-calibrated to the OLI reflectance scale. Results of that effort, as well as other calibration updates including the absolute and relative radiometric calibration and saturated pixel replacement for Landsat 8 OLI and absolute calibration for Landsat 4 and 5 Thematic Mappers (TM), will be implemented into Landsat products during the archive reprocessing campaign planned within the new collection management strategy. This paper reports on the planned radiometric calibration updates to the solar reflective bands of the new Landsat collection.

The Landsat 8 Operational Land Imager (OLI) impressed science users soon after launch in early 2013 with both its radiometric and geometric performance. After three years on-orbit, OLI continues to exceed expectations with its high signal-to-noise ratio, low striping, and stable response. The few artifacts that do exist, such as ghosting, continue to be minimal and show no signs of increasing. The on-board calibration sources showed a small decrease in response during the first six months of operations in the coastal aerosol band, but that decrease has stabilized to less than a half percent per year since that time. The other eight bands exhibit very little change over the past three years and have remained well within a half percent of their initial response to all on-board calibration sources. Analysis of lunar acquisitions also agree with the on-board calibrators. Overall, the OLI on-board the Landsat 8 spacecraft continues to provide exceptional measurements of the Earth's surface to continue the long tradition of Landsat.

Imagery from the Landsat 8 Thermal Infrared Sensor (TIRS) have exhibited scene-dependent non-uniform banding and absolute calibration artifacts since the instrument began operation in 2013. These artifacts have been attributed to a stray light effect in which radiance from outside the nominal field-of-view of the instrument enters the optical system and adds a non-uniform signal to the focal plane detectors. A major effort was launched to characterize the stray light sources and derive an operational software correction that could easily be applied to the ground processing system. The proposed solution relies on a regression analysis in which TIRS scene imagery is used in combination with a detailed optical model to calculate the extra stray light signal on the detectors. The predicted signal is then subtracted from the scene data to remove the stray light artifacts. The resulting imagery from the correction algorithm displays a vast improvement in both banding and absolute error over the current TIRS product. The algorithm has the added benefit of being able to run in 'real time' with no additional data needed. Comparisons to MODIS thermal imagery have demonstrated high performance for scenes all over the world and over different material types and temperatures. A summary of these validation studies will be discussed here.

The Landsat 9 mission, currently under development and proceeding towards a targeted launch in late 2020, will be very similar to the Landsat 8 mission, launched in 2013. Like Landsat 8, Landsat 9 is a joint effort between NASA and USGS with two sensors, the Operational Land Imager 2 (OLI-2), essentially a copy of the OLI on Landsat 8 and the Thermal Infrared Sensor 2 (TIRS-2), very similar to the TIRS on Landsat 8. The OLI-2, like OLI, provides 14-bit image data, though for Landsat 9, all 14 bits will be retained and transmitted to the ground. The focal plane modules to be used for OLI-2 were flight spares for OLI and are currently being retested by Ball Aerospace. Results indicate radiometric performance comparable to OLI. The TIRS was a class C instrument, with a 3-year design lifetime, and therefore had limited redundancy. TIRS-2 will be a class B instrument, with a 5-year design lifetime, like OLI (and OLI-2), necessitating design changes to increase redundancy. The stray light and Scene Select Mechanism (SSM) encoder problems observed on orbit with TIRS have also instigated a few design changes to TIRS-2. Stray light analysis and testing have indicated that additional baffles in the TIRS-2 optical system will suppress the out-of-field response. The SSM encoder problems have not been definitively traced to a route cause, though conductive anodic filament growth in the circuit boards is suspected. Improved designs for the encoder are being considered for TIRS-2. The spare Focal Plane Array (FPA) from TIRS is planned for use in TIRS-2; FPA spectral and radiometric performance testing is scheduled for September of this year at NASA’s Goddard Space Flight Center.

Many inter-consistency efforts force empirical agreement between satellite and airborne sensors viewing a source nearly coincident in time and geometry that ensures consistency between sensors rather than relying on a physical understanding of the source. Several research groups organized a campaign at Algodones Dunes in March 2015 in an effort to measure and characterize parameters that can be used for a source model that will enable this physical understanding. This work will provide an overview of the parameters retrieved from airborne and ground-based measurements made during the campaign. Examples of model-based predictions of at-sensor radiance will be shown for Landsat and MODIS. This approach will provide insight into uncertainties of sensor inter-consistency studies and allow for documented SI-traceability and associate error budget. The Algodones model and subsequent test site models can be used for the assessing inter-calibration accuracies of the upcoming Climate Absolute Reflectance and Refractivity Observatory (CLARREO) Pathfinder mission.

The use of Pseudo Invariant Calibration Sites (PICS) for establishing the radiometric trending of optical remote sensing systems has a long history of successful implementation. Past studies have shown that the PICS method is useful for evaluating the trend of sensors over time or cross-calibration of sensors but was not considered until recently for deriving absolute calibration. Current interest in using this approach to establish absolute radiometric calibration stems from recent research that indicates that with empirically derived models of the surface properties and careful atmospheric characterisation Top of Atmosphere (TOA) reflectance values can be predicted and used for absolute sensor radiometric calibration. Critical to the continued development of this approach is the accurate characterization of the Bidirectional Reflectance Distribution Function (BRDF) of PICS sites. This paper presents BRDF data collected by a high-performance portable goniometer system in order to develop a temporal BRDF model for the Algodones Dunes in California. The results demonstrated that the BRDF of a reasonably simple sand surface was complex with changes in anisotropy taking place in response to changing solar zenith angles. The nature of these complex interactions would present challenges to future model development.

We measure and describe the angular dependence of field and laboratory hyperspectral reflectance measurements of sediments from the Algodones Dunes, CA using the Goniometer of the Rochester Institute of Technology (GRIT) and compare with NASA G-LiHT hyperspectral imagery. G-LiHT imagery was acquired concurrently during a joint field experiment in March 2015 conducted by NASA Goddard, South Dakota State University, University of Arizona, University of Lethbridge, and Rochester Institute of Technology (RIT). Radiative transfer models1 and our own observations10 demonstrate that the angular dependence observed in the bidirectional reflectance distribution (BRDF)^1,2,3,4,5,6 is strongly influenced by factors such as density, grain size distribution, moisture content, and surface roughness.^5,6,7,8,9 Hapke’s model applied to a uniform sediment predicts increasing reflectance as density increases, however, we have observed that multiple scattering and the presence of optically contrasting mineral fractions can lead to the opposite trend.^9,10 The degree of multiple scattering is influenced by incident illumination zenith angle, which determines whether the Hapke prediction is observed or the opposite trend.¹⁰ To better match observations, modifications of the model are necessary.¹⁰ In this paper, we consider some initial work showing the relationship between NASA G-LiHT hyperspectral imagery and GRIT¹⁰ field and laboratory BRDF and GRIT-Two (GRIT-T)¹¹ laboratory BRDF. We also discuss preliminary work using this data for retrieval of geophysical properties of the sediment such as density from multi-angular measurements.

Density, particle size distribution, surface moisture, and mineral content are some important geophysical properties that affect the bi-directional reflectance factor (BRF) of particulate media such as sand. According to radiative transfer theory, several of these geophysical properties are known to directly affect the overall level of reflectance, as well as the functional form of the opposition effect, for homogeneous, particulate media.¹ Most sands are composite, i.e. non-homogeneous, and do not follow the standard distributions (with approximate analytical solutions) for particle size. Therefore, conventional radiative transfer models need to be modified to account for the complex nature of sand. In this work, we examine the impact of density on the functional form of the opposition effect, and we show that differences in density are expressed in a characteristic way. The measurements are collected using the laboratory and field-deployable Goniometer of the Rochester Institute of Technology-Two (GRIT-T). And, the results are based on sediment samples collected from the Algodones Sand Dunes System in southeastern California during the NASA Algodones Dunes Field Experiment conducted in March 2015.

Climate change studies require long-term, continuous records that extend beyond the lifetime, and the temporal resolution, of a single remote sensing satellite sensor. The inter-calibration of spaceborne sensors is therefore desired to provide spatially, spectrally, and temporally homogeneous datasets. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool is a first principle-based synthetic image generation model that has the potential to characterize the parameters that impact the accuracy of the inter-calibration of spaceborne sensors. To demonstrate the potential utility of the model, we compare the radiance observed in real image data to the radiance observed in simulated image from DIRSIG. In the present work, a synthetic landscape of the Algodones Sand Dunes System is created. The terrain is facetized using a 2-meter digital elevation model generated from NASA Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) imager. The material spectra are assigned using hyperspectral measurements of sand collected from the Algodones Sand Dunes System. Lastly, the bidirectional reflectance distribution function (BRDF) properties are assigned to the modeled terrain using the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF product in conjunction with DIRSIG's Ross-Li capability. The results of this work indicate that DIRSIG is in good agreement with real image data. The potential sources of residual error are identified and the possibilities for future work are discussed.

Launched on June 23rd, 2015 from Kourou, Sentinel 2A has been providing images for more than 1 year now. The satellite behavior is very satisfactory and the quality of data fulfills the requirements with comfortable margins. The realization and implementation of the satellite has been realized under the responsibility of ESA, for the European Commission. The In Orbit Commissioning phase lasted 4 months, concluded by a review on October 16th, 2015. At this date, the S2A space segment handover took place from the Project Manager (ESA/ESTEC) to the Mission Manager (ESA/ESRIN). The subset of Image Quality commissioning was delegated by ESA to CNES, referring to the experience of the French Space Agency on previous imagers. This phase lasted 7 months after the launch, extending beyond the IOCR. Actually, some parameters required several months before converging to a stable state. This paper presents the status of the satellite, from an IQ prospective, just before it entered its operational phase. The radiometric and geometric performances are listed, including: the absolute radiometric calibration, the equalization, the SNR, the absolute and the multi-temporal location accuracy. The accomplishment of a part of the Global Reference Image over Europe is evoked as well. The IQ commissioning phase ended on January 28th, 2016. From this date, the monitoring of IQ parameters is under the responsibility of ESA/ESRIN. Nevertheless, CNES continues to support ESA to survey the accuracy of S2A performances. The article ends by dealing with the future of S2A that will work together with S2B by the end of 2016.

The recently launched SENTINEL-3 mission measures sea surface topography, sea/land surface temperature, and ocean/land surface colour with high accuracy. The mission provides data continuity with the ENVISAT mission through acquisitions by multiple sensing instruments. Two of them, OLCI (Ocean and Land Colour Imager) and SLSTR (Sea and Land Surface Temperature Radiometer) are optical sensors designed to provide continuity with Envisat's MERIS and AATSR instruments. During the commissioning, in-orbit calibration and validation activities are conducted. Instruments are in-flight calibrated and characterized primarily using on-board devices which include diffusers and black body. Afterward, vicarious calibration methods are used in order to validate the OLCI and SLSTR radiometry for the reflective bands. The calibration can be checked over dedicated natural targets such as Rayleigh scattering, sunglint, desert sites, Antarctica, and tentatively deep convective clouds. Tools have been developed and/or adapted (S3ETRAC, MUSCLE) to extract and process Sentinel-3 data. Based on these matchups, it is possible to provide an accurate checking of many radiometric aspects such as the absolute and interband calibrations, the trending correction, the calibration consistency within the field-of-view, and more generally this will provide an evaluation of the radiometric consistency for various type of targets. Another important aspect will be the checking of cross-calibration between many other instruments such as MERIS and AATSR (bridge between ENVISAT and Sentinel-3), MODIS (bridge to the GSICS radiometric standard), as well as Sentinel-2 (bridge between Sentinel missions). The early results, based on the available OLCI and SLSTR data, will be presented and discussed.

The Deep Space Climate Observatory (DSCOVR), launched on 11 February 2015, is a satellite positioned near the Lagrange-1 (L1) point, carrying several instruments that monitor space weather, and Earth-view sensors designed for climate studies. The Earth Polychromatic Imaging Camera (EPIC) onboard DSCOVR continuously views the sun illuminated portion of the Earth with spectral coverage in the UV, VIS, and NIR bands. Although the EPIC instrument does not have any onboard calibration abilities, its constant view of the sunlit Earth disk provides a unique opportunity for simultaneous viewing with several other satellite instruments. This arrangement allows the EPIC sensor to be intercalibrated using other well-characterized satellite instrument reference standards. Two such instruments with onboard calibration are MODIS, flown on Aqua and Terra, and VIIRS, onboard Suomi-NPP. The MODIS and VIIRS reference calibrations will be transferred to the EPIC instrument using both all-sky ocean and deep convective clouds (DCC) ray-matched EPIC and MODIS/VIIRS radiance pairs. An automated navigation correction routine was developed to more accurately align the EPIC and MODIS/VIIRS granules. The automated navigation correction routine dramatically reduced the uncertainty of the resulting calibration gain based on the EPIC and MODIS/VIIRS radiance pairs. The SCIAMACHY-based spectral band adjustment factors (SBAF) applied to the MODIS/ VIIRS radiances were found to successfully adjust the reference radiances to the spectral response of the specific EPIC channel for over-lapping spectral channels. The SBAF was also found to be effective for the non overlapping EPIC channel 10. Lastly, both ray-matching techniques found no discernable trends for EPIC channel 7 over the year of publically released EPIC data.

In this study, we performed the vicarious radiometric calibration of KOMPSAT-3A multispectral bands by using 6S radiative transfer model, radiometric tarps, MFRSR measurements. Furthermore, to prepare the accurate input parameter, we also did experiment work to measure the BRDF of radiometric tarps based on hyperspectral gonioradiometer to compensate the observation geometry difference between satellite and ASD Fieldspec 3. Also, we measured point spread function (PSF) by using the bright star and corrected multispectral bands based on the Wiener filter. For accurate atmospheric constituent effects such as aerosol optical depth, column water, and total ozone, we used MFRSR instrument and estimated related optical depth of each gases. Based on input parameters for 6S radiative transfer model, we simulated top of atmosphere (TOA) radiance by observed by KOMPSAT-3A and matched-up the digital number. Consequently, DN to radiance coefficients was determined based on aforementioned methods and showed reasonable statistics results.

The Advanced Himawari Imager (AHI) is the primary instrument aboard Himawari-8 and has 16 multispectral channels, including six visible and near infrared and 10 thermal emissive bands. The 3.9-μm channel imagery of AHI has spatial resolution of 2 km and performs routine full-disk imaging every 10 minutes. There have been stray light observed in the full disk imagery of the AHI 3.9-μm channel over a few weeks around February and October-November when the line of sight of the sun is at ~10 to ~20 degrees south of the nadir of the Himawari-8. In this paper, difference data between consecutive AHI 3.9-μm images have been processed to quantitatively characterize and monitor the AHI stray light. Stray light indices are also developed to trend the occurrence, position and magnitude of the stray light in the AHI 3.9- μm imageries. It is also found that the stray light is the greatest in the AHI 3.9-μm band but also is detectable in other Mid-Wavelength IR channels. Analysis of the ratio of stray light magnitude between AHI 3.9-μm and 6.2-μm band indicates that it is consistent with the ratio of solar radiance for these two bands. This suggests that the stray light is mainly due to direct illumination of the attenuated solar radiation on the AHI detector rather than from onboard thermal body emission due to heating. The upcoming Advanced Baseline Imager (ABI) onboard the GOES-R satellite has very similar spectral and spatial characteristics as AHI. Therefore, characterizing the stray light in the 3.9-μm channel of AHI helps support post-launch calibration activities of ABI.

A new generation of imaging instruments Advanced Baseline Imager (ABI) is to be launched aboard the Geostationary Operational Environmental Satellites - R Series (GOES-R). Four ABI flight modules (FM) are planned to be launched on GOES-R,S,T,U, the first one in the fall of 2016. Pre-launch testing is on-going for FM3 and FM4. ABI has 16 spectral channels, six in the visible/near infrared (VNIR 0.47 − 2.25 μm), and ten in the thermal infrared (TIR 3.9 − 13.3 μm) spectral regions, to be calibrated on-orbit by observing respectively a solar diffuser and a blackbody. Each channel has hundreds of detectors arranged in columns. Operationally one Analytic Generation of Spectral Response (ANGEN) function will be used to represent the spectral response function (SRF) of all detectors in a band. The Vendor conducted prelaunch end-to-end SRF testing to compare to ANGEN; detector specific SRF data was taken for: i) best detector selected (BDS) mode - for FM 2,3, and 4; and ii) all detectors (column mode) - for four spectral bands in FM3 and FM4. The GOES-R calibration working group (CWG) has independently used the SRF test data for FM2 and FM3 to study the potential impact of detector-to-detector SRF differences on the ABI detected Earth view radiances. In this paper we expand the CWG analysis to include the FM4 SRF test data - the results are in agreement with the Vendor analysis, and show excellent instrument performance and compare the detector-to-detector SRF differences and their potential impact on the detected Earth view radiances for all of the tested ABI modules.

In developing software for independent verification and validation (IV and V) of the Image Navigation and Registration (INR) capability for the Geostationary Operational Environmental Satellite – R Series (GOES-R) Advanced Baseline Imager (ABI), we have encountered an image registration artifact which limits the accuracy of image offset estimation at the subpixel scale using image correlation. Where the two images to be registered have the same pixel size, subpixel image registration preferentially selects registration values where the image pixel boundaries are close to lined up. Because of the shape of a curve plotting input displacement to estimated offset, we call this a stair-step artifact. When one image is at a higher resolution than the other, the stair-step artifact is minimized by correlating at the higher resolution. For validating ABI image navigation, GOES-R images are correlated with Landsat-based ground truth maps. To create the ground truth map, the Landsat image is first transformed to the perspective seen from the GOES-R satellite, and then is scaled to an appropriate pixel size. Minimizing processing time motivates choosing the map pixels to be the same size as the GOES-R pixels. At this pixel size image processing of the shift estimate is efficient, but the stair-step artifact is present. If the map pixel is very small, stair-step is not a problem, but image correlation is computation-intensive. This paper describes simulation-based selection of the scale for truth maps for registering GOES-R ABI images.

One of the main objectives of the Geostationary Operational Environmental Satellite R-Series (GOES-R) field campaign is to validate the SI traceability of the Advanced Baseline Imager. The campaign plans include a feasibility demonstration study for new near surface unmanned aircraft system (UAS) measurement capability that is being developed to meet the challenges of validating geostationary sensors. We report our progress in developing our initial systems by presenting the design and preliminary characterization results of the sensor suite. The design takes advantage of off-the-shelf technologies and fiber-based optical components to make hemispheric directional measurements from a UAS. The characterization results -- including laboratory measurements of temperature effects and polarization sensitivity -- are used to refine the radiometric uncertainty budget towards meeting the validation objectives for the campaign. These systems will foster improved validation capabilities for the GOES-R field campaign and other next generation satellite systems.

The GOES-R field campaign (planned for April – June 2017) is focused to support post-launch validation of the Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM). Great emphasis has been placed in the development of methodologies to achieve the ABI GOES-R field campaign primary objective - validation of ABI L1b spectral radiance observations to ensure the SI traceability established pre-launch. An integrated approach using high altitude aircraft, near surface UAS, and satellite reference measurements was developed to achieve the ABI validation objectives of the GOES-R field campaign. The high-altitude aircraft measurements coupled with special ABI collections are planned to provide the primary pathway (direct comparison) to validate ABI SI traceability of all ABI operational detectors. Near surface Unmanned Aircraft Systems (UAS) are planned to provide a secondary pathway to validate ABI SI traceability through coincident near surface measurements of Earth validation targets using the Earth’s surface as a reference (indirect comparison). Satellite reference measurements obtained through special ABI collections and Simultaneous Nadir Overpass (SNO) of reference sensors will also provide a secondary pathway to validate ABI SI traceability. A detailed description of each validation approach, the critical components, and the preliminary expected uncertainties will be presented. The combined collections offer advanced post-launch validation capabilities and foster new perspectives for science teams during the post-launch validation and monitoring of NOAA’s next generation of operational environmental satellites.

MODIS is a key instrument of NASA’s Earth Observing System. It has successfully operated for 16+ years on the Terra satellite and 14+ years on the Aqua satellite, respectively. MODIS has 36 spectral bands at three different nadir spatial resolutions, 250m (bands 1-2), 500m (bands 3-7), and 1km (bands 8-36). MODIS subframe measurement is designed for bands 1-7 to match their spatial resolution in the scan direction to that of the track direction. Within each 1 km frame, the MODIS 250 m resolution bands sample four subframes and the 500 m resolution bands sample two subframes. The detector gains are calibrated at a subframe level. Due to calibration differences between subframes, noticeable subframe striping is observed in the Level 1B (L1B) products, which exhibit a predominant radiance-level dependence. This paper presents results of subframe differences from various onboard and earth-view data sources (e.g. solar diffuser, electronic calibration, spectro-radiometric calibration assembly, Earth view, etc.). A subframe bias correction algorithm is proposed to minimize the subframe striping in MODIS L1B image. The algorithm has been tested using sample L1B images and the vertical striping at lower radiance value is mitigated after applying the corrections. The subframe bias correction approach will be considered for implementation in future versions of the calibration algorithm.

MODIS has 36 spectral bands located on four focal plane assemblies (FPAs), covering wavelengths from 0.41 to 14.4 μm. MODIS bands 1-30 collect data using photovoltaic (PV) detectors and, therefore, are referred to as the PV bands. Similarly, bands 31-36 using photoconductive (PC) detectors are referred to as the PC bands. The MODIS instrument was built with a set of on-board calibrators (OBCs) in order to track on-orbit changes of its radiometric, spatial, and spectral characteristics. In addition, an electronic calibration (ECAL) function can be used to monitor on-orbit changes of its electronic responses (gains). This is accomplished via a series of stair step signals generated by the ECAL function. These signals, in place of the FPA detector signals, are amplified and digitized just like the detector signals. Over the entire mission of both Terra and Aqua MODIS, the ECAL has been performed for the PV bands and used to assess their on-orbit performance. This paper provides an overview of MODIS on-orbit calibration activities with a focus on the PV ECAL, including its calibration process and approaches used to monitor the electronic performance. It presents the results derived and lessons learned from Terra and Aqua MODIS on-orbit ECAL. Also discussed are some of the applications performed with the information provided by the ECAL data.

It has been found that there is severe electronic noise in the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) bands 27-30 which corresponds to wavelengths ranging between 6.7 μm to 9.73 μm. The cause for the issue has been identified to be crosstalk, which is significantly amplified since 2010 due to severe degradation in the electronic circuitry. The crosstalk effect causes unexpected discontinuity/change in the calibration coefficients and induces strong striping artifacts in the earth view (EV) images. Also it is noticed, that there are large long-term drifts in the EV brightness temperature (BT) in these bands. An algorithm using a linear approximation derived from on-orbit lunar observations has been developed to correct the crosstalk effect for them. It was demonstrated that the crosstalk correction can remarkably minimize the discontinuity/change in the calibration coefficients, substantially reduce the striping in the EV images, and significantly remove the long-term drift in the EV BT in all these bands. In this paper, we present the recent progresses in the crosstalk effect analysis and its mitigation. In addition, we will show that besides these four bands, the TEBs in other satellite remote sensors also have significant crosstalk contaminations. Further, it will be demonstrated that the crosstalk correction algorithm we developed can be successfully applied to all the contaminated TEBs to significantly reduce the crosstalk effects and substantially improve both the image quality and the radiometric accuracy of Level-1B (L1B) products for the bands.

MODerate resolution Imaging Spectroradiometer (MODIS), a remarkable heritage sensor in the fleet of Earth Observing System for the National Aeronautics and Space Administration (NASA) is in space orbit on two spacecrafts. They are the Terra (T) and Aqua (A) platforms which tracks the Earth in the morning and afternoon orbits. T-MODIS has continued to operate over 15 years easily surpassing the 6 year design life time on orbit. Of the several science products derived from MODIS, one of the primary derivatives is the MODIS Cloud Mask (MOD035). The cloud mask algorithm incorporates several of the MODIS channels in both reflective and thermal infrared wavelengths to identify cloud pixels from clear sky. Two of the thermal infrared channels used in detecting clouds are the 6.7 μm and 8.5 μm. Based on a difference threshold with the 11 μm channel, the 6.7 μm channel helps in identifying thick high clouds while the 8.5 μm channel being useful for identifying thin clouds. Starting 2010, it had been observed in the cloud mask products that several pixels have been misclassified due to the change in the thermal band radiometry. The long-term radiometric changes in these thermal channels have been attributed to the electronic crosstalk contamination. In this paper, the improvement in cloud detection using the 6.7 μm and 8.5 μm channels are demonstrated using the electronic crosstalk correction. The electronic crosstalk phenomena analysis and characterization were developed using the regular moon observation of MODIS and reported in several works. The results presented in this paper should significantly help in improving the MOD035 product, maintaining the long term dataset from T-MODIS which is important for global change monitoring.

The MODerate Resolution Imaging Spectroradiometer (MODIS) sensors onboard Terra and Aqua satellites are calibrated on-orbit with a solar diffuser (SD) for the reflective solar bands (RSB). The MODIS sensors are operating beyond their designed lifetime and hence present a major challenge to maintain the calibration accuracy. The degradation of the onboard SD is tracked by a solar diffuser stability monitor (SDSM) over a wavelength range from 0.41 to 0.94 μm. Therefore, any degradation of the SD beyond 0.94 μm cannot be captured by the SDSM. The uncharacterized degradation at wavelengths beyond this limit could adversely affect the Level 1B (L1B) product. To reduce the calibration uncertainties caused by the SD degradation, invariant Earth-scene targets are used to monitor and calibrate the MODIS L1B product. The use of deep convective clouds (DCCs) is one such method and particularly significant for the short-wave infrared (SWIR) bands in assessing their long-term calibration stability. In this study, we use the DCC technique to assess the performance of the Terra and Aqua MODIS Collection-6 L1B for RSB 1 3-7 , and 26, with spectral coverage from 0.47 to 2.13 μm. Results show relatively stable trends in Terra and Aqua MODIS reflectance for most bands. Careful attention needs to be paid to Aqua band 1, Terra bands 3 and 26 as their trends are larger than 1% during the study time period. We check the feasibility of using the DCC technique to assess the stability in MODIS bands 17-19. The assessment test on response versus scan angle (RVS) calibration shows substantial trend difference for Aqua band 1between different angles of incidence (AOIs). The DCC technique can be used to improve the RVS calibration in the future.

Large stripes, observed on first Sentinel-2/MSI images over ocean, are not due to instrumental artifacts but to the target itself. The same kind of signature can be observed on Landsat-8/OLI. Both MSI and OLI instruments are known for their excellent radiometric quality for land observation. The MSI’s focal plane is composed by 12 elements to cover the 300km-swath, respectively 14 elements for a 185km-swath for OLI. For technical reason, elements were slightly shifted forward/backward alternatively in the focal plane. As a consequence, each element has a different viewing angle than the next/previous one, leading for a considered target on the ground to a significant difference in zenith/azimuthal viewing angles. These angular variations, fully acceptable for the land mission, become sensitive for specific targets such as sunglint, a highly directional signal. It was already demonstrated the possibility to retrieve surface wind speed from bidirectional space measurements with POLDER/PARASOL instruments. Indeed, using multiple viewing angles is a good way to better constrain the inversion because it doesn’t fully rely on the absolute estimation of a unique measurement. Somehow, MSI or OLI can be seen as bidirectional sensors for targets located between 2 elements of the focal plane. Knowing the exact acquisition geometry, the observed radiometric gap can be directly related to the surface wind speed. Because it is a relative estimation, this inversion becomes more robust to aerosol contamination. Finally, an improved retrieval can be foreseen thanks to the multiple spectral bands provided by MSI and OLI.

There is a growing interest in high spatial resolution imagery for the retrieval of biogeochemical components over water to study the processes involved in inland and coastal waters as well as in the open ocean. High spatial resolution satellite presents a kind of different problems to the ones for coarse spatial resolution satellites (i.e. MODIS) for deriving ocean color products (i.e. chlorophyll-a or colored dissolved organic matter at a specific wavelength). The SeaDAS package has recently added the capability to handle Landsat 8 data and to produce ocean color standard products, but validation of the atmospheric correction with in situ data is needed. In this work, different schemes for atmospheric correction within SeaDAS are applied. These schemes include the use of the NIR-SWIR 2, SWIR 1-SWIR 2 combinations, with and without spatial averaging to account for the low signal-to-noise ratio (SNR) in the SWIR bands. The products from the atmospheric correction in SeaDAS, i.e. remote-sensing reflectance (Rrs) at four different wavelengths, are compared with in situ data. This is the first attempt to compare in situ Rrs with the output from SeaDAS/l2gen.

The ultimate objective of this work is to improve characterization of the ice cover distribution in the polar areas, to improve sea ice mapping and to develop a new automated real-time high spatial resolution multi-sensor ice extent and ice edge product for use in operational applications. Despite a large number of currently available automated satellite-based sea ice extent datasets, analysts at the National Ice Center tend to rely on original satellite imagery (provided by satellite optical, passive microwave and active microwave sensors) mainly because the automated products derived from satellite optical data have gaps in the area coverage due to clouds and darkness, passive microwave products have poor spatial resolution, automated ice identifications based on radar data are not quite reliable due to a considerable difficulty in discriminating between the ice cover and rough ice-free ocean surface due to winds. We have developed a multisensor algorithm that first extracts maximum information on the sea ice cover from imaging instruments VIIRS and MODIS, including regions covered by thin, semitransparent clouds, then supplements the output by the microwave measurements and finally aggregates the results into a cloud gap free daily product. This ability to identify ice cover underneath thin clouds, which is usually masked out by traditional cloud detection algorithms, allows for expansion of the effective coverage of the sea ice maps and thus more accurate and detailed delineation of the ice edge. We have also developed a web-based monitoring system that allows comparison of our daily ice extent product with the several other independent operational daily products.

EarthCARE is ESA’s third Earth Explorer Core Mission, with JAXA providing one instrument. The mission allows unique data product synergies to improve understanding of atmospheric cloud–aerosol interactions and Earth’s radiation balance. Retrieved data will be used to improve climate and numerical weather prediction models. EarthCARE accommodates two active instruments: an ATmospheric LIDar (ATLID) and a Cloud Profiling Radar (CPR), and two passive instruments: a Multi Spectral Imager (MSI) and a BroadBand Radiometer (BBR). The instruments will provide simultaneous, collocated imagery, allowing both individual and common data products. The active instruments provide data on microscopic levels, measured through the atmospheric depth. 3-D models of the atmospheric interactions are constructed from the data, which can be used to calculate radiation balance. The large footprint of the MSI provides contextual information for the smaller footprints of the active instruments. Data from the BBR allows the loop to be closed by providing a macroscopic measurement of the radiation balance. This paper will describe the passive instruments development status. MSI is a compact instrument with a 150 km swath providing 500 m pixel data in seven channels, whose retrieved data will give context to the active instrument measurements, as well as providing cloud and aerosol information. BBR measures reflected solar and emitted thermal radiation from the scene. To reduce uncertainty in the radiance to flux conversion, three independent view angles are observed for each scene. The combined data allows more accurate flux calculations, which can be further improved using MSI data.

The European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) are co-operating to develop as part of ESA’s Living Planet Programme, the third Earth Explorer Core Mission, EarthCARE, with the fundamental objective of improving the understanding of the processes involving clouds, aerosols and radiation in the Earth’s atmosphere. EarthCARE payload consists of two active and two passive instruments: an ATmospheric LIDar (ATLID), a Cloud Profiling Radar (CPR), a Multi-Spectral Imager (MSI) and a Broad-Band Radiometer (BBR). The four instruments data are processed individually and in a synergetic manner to produce a large range of products, which include vertical profiles of aerosols, liquid water and ice, observations of cloud distribution and vertical motion within clouds, and will allow the retrieval of profiles of atmospheric radiative heating and cooling. Operating in the UV range at 355 nm, ATLID provides atmospheric echoes with a vertical resolution up to 100 m from ground to an altitude of 40 km. Thanks to a high spectral resolution filtering, the lidar is able to separate the relative contribution of aerosol (Mie) and molecular (Rayleigh) scattering, which gives access to aerosol optical depth. Co-polarised and cross-polarised components of the Mie scattering contribution are also separated and measured on dedicated channels. This paper gives an overview of the mission science objective, the satellite configuration with its four instruments and details more specifically the implementation and development status of the Atmospheric Lidar. Manufacturing status and first equipment qualification test results, in particular for what concerns the laser transmitter development are presented.

EUMETSAT is providing space based observations for operational meteorology and climate monitoring. The observations are measured by geostationary and sun-synchronous polar orbiting satellites in the frame of mandatory programmes. In the frame of optional programmes further observations for altimetry and oceanography are collected and disseminated. In the frame of third party programmes, EUMETSAT makes available data from other agencies’ satellites to the user community. Since summer 2015 MSG-4 complements the current operational fleet of operational geostationary spacecraft, Meteosat-7, which is the last satellite of the first generation and the three satellites of the Second Generation of Meteosat, Meteosat-8, Meteosat-9 and Meteosat-10. MSG-4 became Meteosat-11 and was stored in orbit after successful commissioning. Two satellites of the EUMETSAT Polar System (EPS) provide data from sunsynchronous polar orbit. Metop-B, the second of a series of three satellites, launched in September 2012 and Metop-A, the first of the series, in orbit since October 2006 provide operational services. The satellites belong to the Initial Joint Polar System (IJPS) with the US. EUMETSAT’s first optional programme continues to provide data from the Jason-2 satellite since summer 2008. As follow on the Jason-3 satellite was launched in January 2016 and is currently in commissioning. To assure continuity development of Meteosat Third Generation (MTG) is ongoing. The EPS-SG programme was fully approved in summer 2015. In the frame of the Copernicus Programme (formerly GMES (Global Monitoring for Environment and Security)) EUMETSAT will operate the marine part of the Sentinel-3 satellite. It was launched in February 2016 and is currently under commissioning.

The goal of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission is to provide high-accuracy data for evaluation of long-term climate change trends. Essential to the CLARREO project is demonstration of SI-traceable, reflected measurements that are a factor of 10 more accurate than current state-of-the-art sensors. The CLARREO approach relies on accurate, monochromatic absolute radiance calibration in the laboratory transferred to orbit via solar irradiance knowledge. The current work describes the results of field measurements with the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) that is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. Recent measurements of absolute spectral solar irradiance using SOLARIS are presented. The ground-based SOLARIS data are corrected to top-of-atmosphere values using AERONET data collected within 5 km of the SOLARIS operation. The SOLARIS data are converted to absolute irradiance using laboratory calibrations based on the Goddard Laser for Absolute Measurement of Radiance (GLAMR). Results are compared to accepted solar irradiance models to demonstrate accuracy values giving confidence in the error budget for the CLARREO reflectance retrieval.

The Ionospheric Connection Explorer (ICON) is a NASA Heliophysics Explorer Mission designed to study the ionosphere. ICON will examine the Earth's upper atmosphere to better understand the relationship between Earth weather and space-weather drivers. ICON will accomplish its science objectives using a suite of 4 instruments, one of which is the Extreme Ultraviolet Spectrograph (EUV). EUV will measure daytime altitude intensity profile and spatial distribution of ionized oxygen emissions (O⁺ at 83.4 nm and 61.7 nm) on the limb in the thermosphere (100 to 500 km tangent altitude). EUV is a single-optic imaging spectrometer that observes in the extreme ultraviolet region of the spectrum. In this paper, we describe instrumental performance calibration measurement techniques and data analysis for EUV. Various measurements including Lyman-α scattering, instrumental and component efficiency, and field-of-view alignment verification were done in custom high-vacuum ultraviolet calibration facilities. Results from the measurements and analysis will be used to understand the instrument performance during the in-flight calibration and observations after launch.

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 m 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.

The Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) has been onorbit for almost five years. VIIRS has 22 spectral bands, among which fourteen are reflective solar bands (RSB) covering a spectral range from 0.410 to 2.25 μm. The SNPP VIIRS RSB have performed very well since launch. The radiometric calibration for the RSB has also reached a mature stage after almost five years since its launch. Numerous improvements have been made in the standard RSB calibration methodology. Additionally, a hybrid calibration method, which takes the advantages of both solar diffuser calibration and lunar calibration and avoids the drawbacks of the two methods, successfully finalizes the highly accurate calibration for VIIRS RSB. The successfully calibrated RSB data record significantly impacts the ocean color products, whose stringent requirements are especially sensitive to calibration accuracy, and helps the ocean color products to reach maturity and high quality. Nevertheless, there are still many challenge issues to be investigated for further improvements of the VIIRS sensor data records (SDR). In this presentation, the robust results of the RSB calibrations and the ocean product performance will be presented. The reprocessed SDR is now in more science tests, in addition to the ocean science tests already completed one year ago, readying to be the mission-long operational SDR.

Built on strong heritage of the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor, the Visible Infrared Imaging Radiometer Suite (VIIRS) carried on Suomi NPP (National Polar-orbiting Partnership) satellite (http://npp.gsfc.nasa.gov/viirs.html) has been in operation for nearly five fives. The on-board calibration of the VIIRS reflective solar bands (RSB) relies on a solar diffuser (SD) located at a fixed scan angle and a solar diffuser stability monitor (SDSM). The VIIRS response versus scan angle (RVS) was characterized prelaunch in lab ambient conditions and is currently used to determine the on orbit response for all scan angles relative to the SD scan angle. Since the RVS is vitally important to the quality of calibrated level 1B products, it is important to monitor its on-orbit stability. In this study, the RVS stability is examined based on reflectance trends collected from 16-day repeatable orbits over preselected pseudo-invariant desert sites in Northern Africa. These trends cover nearly entire Earth view scan range so that any systematic drifts in the scan angle direction would indicate a change in RVS. This study also compares VIIRS RVS on-orbit stability results with those from Aqua and Terra MODIS over the first four years of mission for a few selected bands, which provides further information on potential VIIRS RVS on-orbit changes.

To assure data quality, the Earth-observing Visible Infrared Imaging Radiometer Suite (VIIRS) regularly performs on orbit radiometric calibrations of its 22 spectral bands. The primary calibration radiance source for the reflective solar bands (RSBs) is a sunlit solar diffuser (SD). During the calibration process, sunlight goes through a perforated plate (the SD screen) and then strikes the SD. The SD scattered sunlight is used for the calibration, with the spectral radiance proportional to the product of the SD screen transmittance and the SD bidirectional reflectance distribution function (BRDF). The BRDF is decomposed to the product of its value at launch and a numerical factor quantifying its change since launch. Therefore, the RSB calibration requires accurate knowledge of the product of the SD screen transmittance and the BRDF (RSB; launch time). Previously, we calculated the product with yaw maneuver data and found that the product had improved accuracy over the prelaunch one. With both yaw maneuver and regular on orbit data, we were able to improve the accuracy of the SDSM screen transmittance and the product for the solar diffuser stability monitor SD view. In this study, we use both yaw maneuver and a small portion of regular on-orbit data to determine the product for the RSB SD view.

The use of a specially manufactured solar diffuser (SD) is at the heart of the on-orbit calibration of the reflective solar bands (RSBs) for many important satellite sensors. This includes the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite, and the Moderate-resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites. Within the current standard calibration procedure is an implicit assumption of an idealized degradation of SD in which its angular dependence remains the same functional form with the overall degradation level characterized by a single parameter, the SD degradation factor. This permits the measurement of the SD reflectance performance, measured by the SD stability monitor (SDSM) at a given outgoing angle with respect to the SD, to be used as a valid substitute for the SD reflectance performance toward the RSB direction that is at a different outgoing angle. Recent in-depth studies have uncovered evidence to contradict this assumption, and due to this difference in the outgoing angles between the RSBs and SDSM, the RSB calibration coefficients inherit growing bias. In this exposition, we will explicitly show the evolving angular dependence in SD degradation for SNPP VIIRS and Terra/Aqua MODIS. By examining the angular dependence of the available detector response within each calibration event we are able to build a historical trend clearly demonstrating evolving angular dependence. We refer to this phenomenon as the “SD degradation nonuniformity effect”. Our finding lays out a very basic mismatch between the use of the SD and the current official RSB calibration methodology that will be an important issue to be addressed.

The VIIRS Day-Night Band (DNB) offers measurements over a dynamic range from full daylight to the dimmest nighttime. This makes radiometric calibration difficult because effects that are otherwise negligible become significant for the DNB. One of these effects is electronic hysteresis and this paper evaluates this effect and its impact on calibration. It also considers possible correction algorithms. The cause of this hysteresis is uncertain, but since the DNB uses a charge-coupled device (CCD) detector array, it is likely the result of residual charge or charge depletion. The effects of hysteresis are evident in DNB imagery. Steaks are visible in the cross-track direction around very bright objects such as gas flares. Dark streaks are also visible after lightning flashes. Each VIIRS scan is a sequence of 4 sectors: space view (SV); Earth-view (EV); blackbody (BB) view; and solar diffuser (SD) view. There are differences among these sectors in offset that can only be explained as being the result of hysteresis from one sector to the next. The most dramatic hysteresis effect is when the sun illuminates the SD and hysteresis is then observed in the SV and EV. Previously this was hypothesized to be due to stray light leaking from the SD chamber, but more careful evaluation shows that this can only be the result of hysteresis. There is a stray light correction algorithm that treats this as stray light, but there are problems with this that could be remedied by instead using the characterization presented here.

The atmospheric turbulence effects on the light field at the altitude of the VIIRS from a ground based Lambertian source were investigated. It has been shown theoretically that the radiant intensity follows the Lambert’s law despite of turbulent perturbations. The corresponding average irradiance at the altitude of the VIIRS can be determined via the inverse square law. Light field scintillation was evaluated numerically by the discretized mode representation of the source and the multiple random phase screen simulation method. Our results will contribute to the study of using ground based light source for the validation/calibration of the VIIRS DNB.

The Suomi National Polar orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) has onboard calibrators called blackbody (BB) and Space View (SV) for Thermal Emissive Band (TEB) radiometric calibration. In normal operation, the BB temperature is set to 292.5 K providing one radiance level. From the NOAA’s Integrated Calibration and Validation System (ICVS) monitoring system, the TEB calibration factors (F-factors) have been trended and show very stable responses, however the BB Warm-Up-Cool-Down (WUCD) cycles provide detectors’ gain and temperature dependent sensitivity measurements. Since the launch of S-NPP, the NOAA Sea Surface Temperature (SST) group noticed unexpected global SST anomalies during the WUCD cycles. In this study, the TEB Ffactors are calculated during the WUCD cycle on June 17th 2015. The TEB F-factors are analyzed by identifying the VIIRS On-Board Calibrator Intermediate Product (OBCIP) files to be Warm-Up or Cool-Down granules. To correct the SST anomaly, an F-factor correction parameter is calculated by the modified C1 (or b1) values which are derived from the linear portion of C1 coefficient during the WUCD. The F-factor correction factors are applied back to the original VIIRS SST bands showing significantly reducing the F-factor changes. Obvious improvements are observed in M12, M14 and M16, but corrections effects are hardly seen in M16. Further investigation is needed to find out the source of the F-factor oscillations during the WUCD.

This paper describes trends in the Suomi National Polar‐orbiting Partnership (SNPP) spacecraft ephemeris data over the four and half years of on-orbit operations. It then discusses the implications of these trends on the geometric performance of the Visible Infrared Imaging Radiometer Suite (VIIRS), one of the instruments onboard SNPP. The SNPP ephemeris data includes time stamped spacecraft positions and velocities that are used to calculate the spacecraft altitude and sub-satellite locations. Through drag make-up maneuvers (DMUs) the orbital mean altitude (spacecraft altitude averaged over an orbit) has been maintained at 838.8 km to within +/- 0.2 km and the orbital period at 101.5 minutes to within +/- 0.2 seconds. The corresponding orbital mean velocity in the terrestrial frame of reference has been maintained at 7524 m/s to within +/- 0.5 m/s. Within an orbit, the altitude varies from 828 km near 15° N to 856 km near the South Pole. Inclination adjust maneuvers (IAMs) have maintained the orbit inclination angle at 98.67° to with +/- 0.07° and the sun-synchronous local time at ascending node (LTAN) at 13:28 to within +/- 5 minutes. Besides these trends, it is interesting to observe that the orbit’s elliptic shape has its major axis linking the perigee and apogee shorter than the line linking the ascending node and the descending node. This effect is caused by the Earth’s oblate spheroid shape and deviates from a Keplerian orbit theory in which the two orbiting bodies are point masses. VIIRS has 5 imagery resolution bands, 16 moderate resolution bands and a day-night band, with 32, 16 and 16 detectors, respectively, aligned in the spacecraft flight (aka. track) direction. For each band’s sample within a scan, the detectors sample the Earth’s surface simultaneously in the track direction in the Earth Centered Inertial frame of reference. The distance between the center of the area sensed by the trailing detectors of one scan and the leading detectors of the next includes a component caused by earth rotation. This earth rotation component is relatively small (~70 m/s) for an orbit like SNPP, but must be taken into account in the design of low-Earth orbit scanning sensors similar to VIIRS to ensure contiguous coverage at nadir.

Following the successful operations of the first Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on-board the Suomi National Polar‐orbiting Partnership (SNPP) spacecraft since launch in October 2011, a second VIIRS instrument to be on-board the first Joint Polar Satellite System (JPSS-1) satellite has been fabricated, tested and integrated onto the spacecraft, readying for launch in 2017. The ground testing, including geometric functional performance testing and characterization, at the sensor level was completed in December 2014. Testing at the spacecraft level is on-going. The instrument geometric performance includes sensor (detector) spatial response, band-to-band coregistration (BBR), scan plane and pointing stability. The parameters have been calibrated and characterized through ground testing under ambient and thermal vacuum conditions, and numerical modeling and analysis. VIIRS sensor spatial response is measured by line spread functions (LSFs) in the scan and track directions for every detector. We parameterize the LSFs by: 1) dynamic field of view (DFOV) in the scan direction and instantaneous FOV (IFOV) in the track direction; and 2) modulation transfer function (MTF) for the 17 moderate resolution bands (M-bands) and for the five imagery bands (I-bands). We define VIIRS BBR for M-bands and I-bands as the overlapped fractional area of angular pixel sizes from the corresponding detectors in a band pair, including nested I-bands within the M-bands. The ground tests result in static BBR matrices. VIIRS pointing measurements include scan plane tilt and instrument-to-spacecraft mounting coefficients. This paper summarizes the pre-launch test results along with anomaly investigations. The pre-launch performance parameters will be tracked or corrected for as needed in on-orbit operations.

The U.S. National Weather Service currently assimilates into its numerical weather prediction models satellite observations from the aging MODIS instruments that track polar winds from motion of both clouds and atmospheric moisture. Next generation weather observations are provided by VIIRS instruments, but VIIRS lacks a water vapor channel at 6.7 μm, allowing for only cloud-tracking of winds. An addition of the 6.7 μm channel to future VIIRS instruments has been proposed. The additional channel could replace a 750-m channel at 1.6 μm (M10) that shares spectral response characteristics with a 375-m channel (I3). M10 data would then be synthesized by the 2-by-2 aggregation of I3 pixels. Radiometric response of such a synthesized channel is very similar to the actual one, although some differences exist. In this study, SNR (signal-to-noise ratio) for the M10 data simulated by the aggregation of the I3 pixels was compared with SNR for the actual M10 data. SNR for the simulated M10 was found to be always lower than SNR for the actual M10. This result contrasts with results of an analogous SNR comparison for bands I2 and M7 that share the same spectral response at 865 nm. Aggregated I2 data have SNR comparable to actual M7 data measured with the low gain, although lower than high-gain M7. The main reason for the different SNR behavior may be the use of microlenses with the I3 and M10 detectors, but not with the I2 and M7 ones.

Overhauser magnetometer is a kind of high-precision devices for magnetostatic field measurement. It is widely used in geological survey, earth field variations, UXO detection etc. However, the original Overhauser magnetometer JOM-2 shows great shortcomings of low signal to noise ratio (SNR) and high power consumption, which directly affect the performance of the device. In order to increase the sensitivity and reduce power consumption, we present an improved Overhauser magnetometer. Firstly, compared with the original power board which suffers from heavy noise for improper EMC design, an improved power broad with 20mV peak to peak noise is presented in this paper. Then, the junction field effect transistor (JFET) is used as pre-amplifier in our new design, to overcome the higher current noise produced by the original instrumentation amplifier. By adjusting the parameters carefully low noise factor down to 0.5 dB can be obtained. Finally, the new architecture of ARM + CPLD is adopted to replace the original one with DSP+CPLD. So lower power consumption and greater flash memory can be realized. With these measures, an improved Overhauser magnetometer with higher sensitivity and lower power consumption is design here. The experimental results indicate that the sensitivity of the improved Overhauser magnetometer is 0.071nT, which confirms that the new magnetometer is sensitive to earth field measurement.

SpaceEye-1 earth observation satellite, developed by Satrec Initiative Co. Ltd., is a 300 kg scale spacecraft with high resolution electro-optical payload (EOS-D) which performs 1 m GSD, 12 km swath in low earth orbit. Metering structure of EOS-D is manufactured with Carbon Fiber Reinforced Plastic (CFRP). Due to the moisture emission from CFRP metering structure, this spaceborne electro-optical payload undergoes shrinkage after orbit insertion. The shrinkage of metering structure causes change of the distance between primary and secondary mirror. In order to compensate the moisture shrinkage effect, two types of thermal refocusing mechanism were developed, analyzed and applied to EOS-D. Thermal analysis simulating in-orbit thermal condition and thermo-elastic displacement analysis was conducted to calculate the performance of refocusing mechanism. For each EOS-D telescope, analytical refocusing range (displacement change between primary and secondary mirror) was 2.5 um and 3.6 um. Thus, the refocusing mechanism can compensate the dimensional instability of metering structure caused by moisture emission. Furthermore, modal, static and wavefront error analysis was conducted in order to evaluate natural frequency, structural stability and optical performance. As a result, it can be concluded that the refocusing system of EOS-D payload can perform its function in orbit.

The paper describes the design procedure that allows identification of the optimal parameters of the light source based on optically connected integrating spheres. This source provides a high dynamic range of output radiance with high uniformity of radiance distribution throughout an output aperture. The procedure deals with relative parameters of apertures of primary and secondary integrating spheres, aperture areas, density of lamps and etc. It makes possible calculation of the set of optimal parameters that guarantees the maximal output radiance with high uniformity of its distribution through an output aperture. The paper demonstrates the application of this procedure in the light source design.

The Visible Infrared Imaging Radiometer Suite (VIIRS) in the Suomi National Polar-orbiting Partnership (SNPP) satellite has been on orbit for nearly five years since its launch on 28 October 2011. The NOAA Ocean Color (OC) Team through the investigations of Sun and Wang has recently achieved robust calibration of the VIIRS reflective solar bands (RSBs) and generated its own version of the sensor data records (SDRs) with accuracy sufficient for ocean color applications. For the purpose of making a direct evaluation of the SDR performance, for both the OC version and the official Interface Processing Data Segment (IDPS) version, we utilize an inter-sensor radiometric comparison of SNPP VIIRS against the MODerate-resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite for the spectrally matching RSBs. The VIIRS RSBs M1–M8, from 410 to 1238 nm in the spectral range, are tested. Except for the VIIRS M1 versus MODIS Band 8 result, the radiance comparison time series shows that the OC SDRs demonstrate good agreement with Aqua MODIS and overall better results than the IDPS SDRs, such as less variation, no large discrepancy at the beginning of the VIIRS mission, and no long-term drift. The VIIRS M1 versus MODIS Band 8 trend is the lone exception showing a drift in the OC SDR-based trends, but eventually a downward drift of 1% in Aqua MODIS Band 8 is identified to be the cause. It is readily concluded that the inter-comparison result directly demonstrates the OC SDRs to be correct within statistics, especially considering that the ocean color products derived from the OC SDRs have already matured and demonstrated good agreement with in situ data. On the other hand, the IDPS SDR results demonstrably expose the known inherent growing bias in RSB calibration that affects any versions of the SNPP VIIRS SDRs not using the correctly mitigated calibration baseline. The inter-comparison of two moderate resolution sensors is also an exercise in statistics, and we briefly discuss key points of the pixel-based analysis that establishes the precision and the reliability of the result

In VHF pulse Ground Penetrating Radar(GPR) system, the echo pass through the antenna and transmission line circuit, then reach the GPR receiver. Thus the reflection coefficient at the receiver sampling gate interface, which is at the end of the transmission line, is different from the real reflection coefficient of the media at the antenna interface, which could cause the GPR receiving error. The pulse GPR receiver is a wideband system that can't be simply described as traditional narrowband transmission line model. Since the GPR transmission circuit is a linear system, the linear transformation method could be used to analyze the characteristic of the GPR receiving system. A GPR receiver calibration method based on transmission line theory is proposed in this paper, which analyzes the relationship between the reflection coefficients of theory calculation at antenna interface and the measuring data by network analyzer at the sampling gate interface. Then the least square method is introduced to calibrate the transfer function of the GPR receiver transmission circuit. This calibration method can be useful in media quantitative inversion by GPR. When the reflection coefficient at the sampling gate is obtained, the real reflection coefficient of the media at the antenna interface can be easily determined.

The reflected solar instrument that is part of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission is being formulated with a goal of providing SI-traceable measurement of radiance that is an order of magnitude more accurate than the current imaging sensors. The Goddard Laser for Absolute Measurement of Radiance (GLAMR) is a key element to reaching such accuracy along with transferring the laboratory calibration to on-orbit measurements. Results from field reflectance retrievals using three separate instruments all of which have been calibrated using GLAMR are shown. The instruments include a commercial field spectrometer and a portable version of CLARREO’s calibration demonstration system. The third instrument is NASA Goddard’s Lidar, Hyperspectral and Thermal Imager (G-LiHT) which is an airborne system. All three were operated during a March 2013 measurement campaign at Red Lake Playa, Arizona as part of the on-orbit commissioning phase of Landsat 8. Reflectance is derived from near-coincident measurements by the three sensors for a small area of the playa. The retrieved results are SI-traceable and demonstrate the ability to transfer the GLAMR calibration to the field. Use of the G-LiHT data in the calibration of Landsat-7 and -8 sensors permits them both to be placed on the GLAMR-scale as well.

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major instrument within NASA’s Earth Observation System missions, has operated for over 16 and 14 years onboard the Terra and Aqua satellites, respectively. Its reflective solar bands (RSB) covering a spectral range from 0.4 to 2.1 μm are primarily calibrated using the on-board solar diffuser (SD), with its on-orbit degradation monitored using the Solar Diffuser Stability Monitor. RSB calibrations are supplemented by near-monthly lunar measurements acquired from the instrument’s space-view port. Nine bands (bands 8-16) in the visible to near infrared spectral range from 0.412 to 0.866 μm are primarily used for ocean color observations. During a recent reprocessing of ocean color products, performed by the NASA’s Ocean Biology Processing Group, detector-to-detector differences of up to 1.5% were observed in bands 13-16 of Terra MODIS. This paper provides an overview of the current approach to characterize the MODIS detector-to-detector differences. An alternative methodology was developed to mitigate the observed impacts for bands 13-16. The results indicated an improvement in the detector residuals and in turn are expected to improve the MODIS ocean color products. This paper also discusses the limitations, subsequent enhancements, and the improvements planned for future MODIS calibration collections.