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In June 1991, the NASA/Jet Propulsion Laboratory airborne SAR (AIRSAR) collected the first calibrated multi-channel SAR observations of the Greenland ice sheet.
The high-accuracy Earth-reflected solar spectral radiances from CLARREO Pathfinder (CPF) will serve as in-orbit benchmark measurements for intercalibrating other satellite imagers. The CPF team is developing a state-of-the-art intercalibration method to calibrate the shortwave channel (300-5000 nm) of the CERES instrument against the CPF reference with an uncertainty of 0.3%. Because the CPF instrument only covers spectral range from 350 nm to 2300 nm, the team has developed a spectral extension method to fill in the gaps between the spectral domains of CPF and the CERES shortwave channel. The method solely relies on using the hyperspectral information from the CPF wavelengths to predict the radiances below 350 nm and above 2300 nm. To quantify the relationship between the CPF spectrum and the non-overlapping portions of the spectrum between CPF and CERES, the team has simulated a large ensemble of spectra that cover the spectral range for both CPF and CERES. A hyperspectral bidirectional reflectance model for land surface based on thousands of measured land surface reflectance has been developed. This land surface model as well as the Cox-Munk model for ocean surface are used in the spectral gap filling. Various water/ice clouds, aerosols, atmosphere profiles and surfaces were used to simulate Earth-reflected radiances from 200 nm to 15 um under different solar and sensor geometries. The targeted uncertainty for the CPF-extended broadband CERES radiances is less than 0.1%. The previously derived training spectra were updated to replace the Kurucz solar irradiance model with the TSIS-1 Hybrid Solar Reference Spectrum. The influence of the scalar assumption in radiative transfer model equations on the uncertainty in estimating the broadband radiances was also investigated.
The Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) consists of an Earthviewing reflected solar (RS) spectrometer that will measure the Earth-reflected solar radiation from International Space Station with an SI-traceable radiometric uncertainty of 0.3% (1-sigma). The high-accuracy CPF measurements will provide an in-orbit reference for intercalibrating other spaceflight RS instruments. The CPF intercalibration team has been tasked to develop a state-of-the-art approach to calibrate the shortwave channel (300-5000 nm) of the Clouds and the Earth’s Radiant Energy System (CERES) instrument and the reflective solar bands (RSB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, both onboard the NOAA-20 satellite, against the CPF benchmark measurements. The aimed intercalibration methodology uncertainty for both the target instruments is also 0.3%. To meet this stringent intercalibration accuracy, the CPF team has developed methods for mitigating the impacts of spatial, spectral, and angular differences between the intercalibration footprints from the CPF and target instruments. To further alleviate uncertainty, the CPF team will employ Polarization Distribution Models (PDMs) to characterize the polarization state of the Earth-reflected radiance as a function of the intercalibration footprint scene type, solar and viewing geometry, and wavelength. The PDMs will assist in identifying low-polarized scene radiances for meticulously intercalibrating the polarization sensitive VIIRS instrument against the significantly-less polarization-sensitive CPF instrument. This paper will highlight the CPF mission overview, the details of the CPF intercalibration approach, and additional outcomes of the CPF intercalibration studies that may benefit the broader remote sensing community.community.
The post-launch degradation of the visible (channel 1: 0.58- 068 microns) and near-infrared (channel 2: approx. 0.72 - l.l microns) channels of the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-7, -9, and -11 Polar-orbiting Operational Environmental Satellites (POES) was estimated using the south-eastern part of the Libyan Desert as a radiometrically stable calibration target. The relative annual degradation rates, in per cent, for the two channels are, respectively: 3.6 and 4.3 (NOAA-7); 5.9 and 3.5 (NOAA-9); and 1.2 and 2.0 (NOAA-11). Using the relative degradation rates thus determined, in conjunction with absolute calibrations based on congruent path aircraft/satellite radiance measurements over White Sands, New Mexico (USA), the variation in time of the absolute gain or slope of the AVHRR on NOAA-9 was evaluated. Inter-satellite calibration linkages were established, using the AVHRR on NOAA-9 as a normalization standard. Formulae for the calculation of calibrated radiances and albedos (AVHRR usage), based on these interlinkages, are given for the three AVHRRs.
We present a demonstration of the in-flight polarization angle calibration for the JAXA/ISAS second strategic large class mission, LiteBIRD, and estimate its impact on the measurement of the tensor-to-scalar ratio parameter, r, using simulated data. We generate a set of simulated sky maps with CMB and polarized foreground emission, and inject instrumental noise and polarization angle offsets to the 22 (partially overlapping) LiteBIRD frequency channels. Our in-flight angle calibration relies on nulling the EB cross correlation of the polarized signal in each channel. This calibration step has been carried out by two independent groups with a blind analysis, allowing an accuracy of the order of a few arc-minutes to be reached on the estimate of the angle offsets. Both the corrected and uncorrected multi-frequency maps are propagated through the foreground cleaning step, with the goal of computing clean CMB maps. We employ two component separation algorithms, the Bayesian-Separation of Components and Residuals Estimate Tool (B-SeCRET), and the Needlet Internal Linear Combination (NILC). We find that the recovered CMB maps obtained with algorithms that do not make any assumptions about the foreground properties, such as NILC, are only mildly affected by the angle miscalibration. However, polarization angle offsets strongly bias results obtained with the parametric fitting method. Once the miscalibration angles are corrected by EB nulling prior to the component separation, both component separation algorithms result in an unbiased estimation of the r parameter. While this work is motivated by the conceptual design study for LiteBIRD, its framework can be broadly applied to any CMB polarization experiment. In particular, the combination of simulation plus blind analysis provides a robust forecast by taking into account not only detector sensitivity but also systematic effects.
Spaceborne microwave radiometers with high frequency channels (150-183 GHz) are important for retrieving many geophysical parameters such as snowfall, ice water path, and atmospheric water vapor profiles. In order to obtain accurate retrievals from the brightness temperature measurements, the radiometers must be properly calibrated. Several methods have been developed to analyze the on-orbit calibration, including comparisons with radiative transfer models, comparisons with radiosonde profiles, and cross-calibration with similar radiometers. This paper introduces a new method to calibrate high frequency channels that utilizes TB histograms. This new method gives an independent approach that can be used by itself to analyze radiometer calibration or in conjunction with other methods to corroborate results.
Three computer programs have been written to preprocess digitized outputs of sensors during rocket-engine tests at Stennis Space Center (SSC). The programs apply exclusively to the SSC "E" test-stand complex and utilize the SSC file format. The programs are the following: 1) Engineering Units Generator (EUGEN) converts sensor-output-measurement data to engineering units. The inputs to EUGEN are raw binary test-data files, which include the voltage data, a list identifying the data channels, and time codes. EUGEN effects conversion by use of a file that contains calibration coefficients for each channel; 2) QUICKLOOK enables immediate viewing of a few selected channels of data, in contradistinction to viewing only after post test processing (which can take 30 minutes to several hours depending on the number of channels and other test parameters) of data from all channels. QUICKLOOK converts the selected data into a form in which they can be plotted in engineering units by use of Winplot (a free graphing program written by Rick Paris); and 3) EUPLOT provides a quick means for looking at data files generated by EUGEN without the necessity of relying on the PVWAVE based plotting software.
Three computer programs have been written to preprocess digitized outputs of sensors during rocket-engine tests at Stennis Space Center (SSC). The programs apply exclusively to the SSC E test-stand complex and utilize the SSC file format. The programs are the following: Engineering Units Generator (EUGEN) converts sensor-output-measurement data to engineering units. The inputs to EUGEN are raw binary test-data files, which include the voltage data, a list identifying the data channels, and time codes. EUGEN effects conversion by use of a file that contains calibration coefficients for each channel. QUICKLOOK enables immediate viewing of a few selected channels of data, in contradistinction to viewing only after post-test processing (which can take 30 minutes to several hours depending on the number of channels and other test parameters) of data from all channels. QUICKLOOK converts the selected data into a form in which they can be plotted in engineering units by use of Winplot (a free graphing program written by Rick Paris). EUPLOT provides a quick means for looking at data files generated by EUGEN without the necessity of relying on the PV-WAVE based plotting software.
Three computer programs have been written to preprocess digitized outputs of sensors during rocket-engine tests at Stennis Space Center (SSC). The programs apply exclusively to the SSC E test-stand complex and utilize the SSC file format. The programs are the following: (1) Engineering Units Generator (EUGEN) converts sensor-output-measurement data to engineering units. The inputs to EUGEN are raw binary test-data files, which include the voltage data, a list identifying the data channels, and time codes. EUGEN effects conversion by use of a file that contains calibration coefficients for each channel. (2) QUICKLOOK enables immediate viewing of a few selected channels of data, in contradistinction to viewing only after post-test processing (which can take 30 minutes to several hours depending on the number of channels and other test parameters) of data from all channels. QUICKLOOK converts the selected data into a form in which they can be plotted in engineering units by use of Winplot. (3) EUPLOT provides a quick means for looking at data files generated by EUGEN without the necessity of relying on the PVWAVE based plotting software.
The general design, calibration, and performance of a new high-sensitivity radiation pyrometer are described. The pyrometer can determine time-resolved temperatures (as low as 1500 K) in shocked materials by measuring the spectral radiance of light emitted from shocked solid samples in the visible and near-infrared wavelength range (0.5-1.0 micron). The high sensitivity of the radiation pyrometer is attributed to the large angular aperture (0.06 sr), the large bandwidth per channel (up to 0.1 micron), the large photodiode detection areas (1.0 sq cm), and the small number of calibrated channels (4) among which light is divided.
A document describes an algorithm created to estimate the mass placed on a sample verification sensor (SVS) designed for lunar or planetary robotic sample return missions. A novel SVS measures the capacitance between a rigid bottom plate and an elastic top membrane in seven locations. As additional sample material (soil and/or small rocks) is placed on the top membrane, the deformation of the membrane increases the capacitance. The mass estimation algorithm addresses both the calibration of each SVS channel, and also addresses how to combine the capacitances read from each of the seven channels into a single mass estimate. The probabilistic approach combines the channels according to the variance observed during the training phase, and provides not only the mass estimate, but also a value for the certainty of the estimate. SVS capacitance data is collected for known masses under a wide variety of possible loading scenarios, though in all cases, the distribution of sample within the canister is expected to be approximately uniform. A capacitance-vs-mass curve is fitted to this data, and is subsequently used to determine the mass estimate for the single channel s capacitance reading during the measurement phase. This results in seven different mass estimates, one for each SVS channel. Moreover, the variance of the calibration data is used to place a Gaussian probability distribution function (pdf) around this mass estimate. To blend these seven estimates, the seven pdfs are combined into a single Gaussian distribution function, providing the final mean and variance of the estimate. This blending technique essentially takes the final estimate as an average of the estimates of the seven channels, weighted by the inverse of the channel s variance.
Since its launch in May 2002, Aqua MODIS has successfully operated for more than 20 years and has continuously generated a wide range of data products that have enabled and supported the remote sensing community and users worldwide for their studies of the Earth’s system by monitoring changes in its key environmental parameters. Although Aqua MODIS, designed with a lifetime requirement of 6 years, is currently operated in its extended mission phase, it continues to make high quality global observations of the Earth’s surface via its 36 spectral bands that cover wavelengths from visible to long-wave infrared. To date, all instrument on-board calibrators (OBC) remain capable of performing their design functions, providing various calibration data sets to help monitor on-orbit changes in sensor responses and performance characteristics. In addition to the OBC, regularly scheduled lunar observations and select Earth-view targets are used extensively to support sensor on-orbit calibration, especially for the calibration of the visible channels (or bands). In this paper, we provide an overview of Aqua MODIS on-orbit calibration activities and methodologies for both reflective solar bands (RSB) and thermal emissive bands (TEB), illustrate its on-orbit performance over the past 20 years using examples derived from OBC measurements, lunar observations, and Earth-view response trends, and describe various calibration improvements made over its entire mission. We focus on key issues identified since launch, such as solar diffuser degradation, electronic crosstalk, and on-orbit changes in sensor response versus scan-angle, along with approaches and strategies developed to mitigate their impact on sensor calibration quality. Also discussed in this paper are some of the key calibration enhancements incorporated recently in the Collection 6.1 and the upcoming Collection 7 Level-1B algorithms.
As Synthetic Aperture Radar (SAR) system performance and experience in SAR signature evaluation increase, quantitative analysis becomes more and more important. Such analyses require an absolute radiometric calibration of the complete SAR system. To keep the expenditure on calibration of future multichannel and multisensor remote sensing systems (e.g., X-SAR/SIR-C) within a tolerable level, data from different tracks and different sensors (channels) must be cross calibrated. The 1989 joint E-SAR/DC-8 SAR calibration campaign gave a first opportunity for such an experiment, including cross sensor and cross track calibration. A basic requirement for successful cross calibration is the stability of the SAR systems. The calibration parameters derived from different tracks and the polarimetric properties of the uncalibrated data are used to describe this stability. Quality criteria for a successful cross calibration are the agreement of alpha degree values and the consistency of radar cross sections of equally sized corner reflectors. Channel imbalance and cross talk provide additional quality in case of the polarimetric DC-8 SAR.
The initial characterization of the Thematic Mapper (TM) thermal band is reported including gain stability, gain relation to internal calibration, corrections for channel-to-channel and scan direction differences, an approximate comparison to ground truth, and a calculation of noise equivalent temperature difference. Updated calibration information is also presented.
A spectroradiometer which measures spectral reflectivities and irradiance in discrete spectral channels was tested to determine the accuracy of its wavelength calibration. This sensor is a primary tool in the remote sensing investigations conducted on biomass at NASA's Goddard Space Flight Center. Measurements have been collected on crop and forest plants both in the laboratory and field with this radiometer to develop crop identification and plant stress remote sensing techniques. Wavelength calibration is essential for use in referencing the study measurements with those of other investigations and satellite remote sensor data sets. This calibration determines a wavelength vs channel address conversion which was found to have an RMS deviation of approximately half a channel, or 1.5 nm in the range from 360 to 1050 nm. A comparison of these results with those of another test showed an average difference of approximately 4 nm, sufficiently accurate for most investigative work.
The detection of primordial B modes of the cosmic microwave background (CMB) could provide information about the early stages of the Universe's evolution. The faintness of this signal requires exquisite calibration accuracy and control of instrumental systematic effects which otherwise could bias the measurements. In this work, we study the impact of an imperfect relative polarisation gain calibration on the recovered value of the tensor-to-scalar ratio r for the LiteBIRD experiment, through the application of the blind Needlet Internal Linear Combination (NILC) foreground-cleaning method. We derive requirements on the relative calibration accuracy of the overall polarisation gain (Δg ν ) for each LiteBIRD frequency channel. Our results show that minimum variance techniques, as NILC, are less sensitive to systematic gain calibration uncertainties compared to a parametric approach, if the latter is not equipped with a proper modelling of these instrumental effects. In this study, the most stringent requirements are found in the channels where the CMB signal is relatively brighter, with the tightest constraints at 166 GHz (Δg ν ≈ 0.16%). This differs from the outcome of an analogous analysis performed with a parametric method, where the tightest requirements are obtained for the foreground-dominated channels. Gain calibration uncertainties, corresponding to the derived requirements, are then simultaneously propagated into all frequency channels. By doing so, we find that the overall impact on estimated r is lower than the total gain systematic budget for LiteBIRD approximately by a factor 5, due to the correlations of the impacts of gain calibration uncertainties in different frequency channels. In order to decouple the systematic effect from the specific choice of the model, we derive the requirements assuming constant spectral parameters for the foreground emission. To assess the robustness of the obtained results against more realistic scenarios, we repeat the analysis assuming sky models of intermediate and high complexity. In these further cases, we adopt an optimised NILC pipeline, called the Multi-Clustering NILC (MC-NILC). We find that the impact of gain calibration uncertainties on r is lower than the LiteBIRD gain systematics budget for the intermediate-complexity sky model. For the high-complexity case, instead, it would be necessary to tighten the requirements by a factor 1.8.
Three techniques for the absolute calibration of two reflective channels of the NOAA AVHRR sensors are described and compared. The technique 1 is based on field measurements and refers to another calibrated satellite sensor; technique 2 utilizes the reflectance-based calibration method; and technique 3 estimates the calibration by reference to another satellite sensor. NOAA-9 and NOAA-10 AVHRR images are analyzed. It is observed that the responsivity of the images degrade compared to prelaunch calibration. The effect of degradation in responsivity of the AVHRR sensors on vegetation indices are studied. It is noted that the uncertainties in the calibration methods is about 7-10 percent making them useful for many applications.
The calibration of the historical AVHRR visible channels has always been hindered by the degrading NOAA satellite orbits. The complete AVHRR record spans over three decades making it useful for cloud, aerosol, and land use climate studies. Studies that monitor long-term changes in these properties require climate quality calibration. The AVHRR sensors do not have any onboard visible calibration, unlike the IR channels. Many AVHRR post-launch calibration methods have been published. Some of these are based on the pseudo invariant targets such as desert and polar ice and others employ direct calibration transfer from a well-calibrated sensor such as MODIS. Most historical studies only employed only one method and reconciling calibration differences from multiple studies was difficult. This study employs multiple calibration approaches, which are then merged according to their individual uncertainty. Since the visible spectral response functions are similar across AVHRR sensor and that the morning and afternoon orbits usually degrade in the same manner, an afternoon and morning orbiter during the MODIS era is chosen as the reference AVHRR sensor. The reference AVHRR sensor is inter-calibrated with the Aqua-MODIS Collection 6 standard using simultaneous nadir overpass (SNO) radiance pairs. Three pseudo invariant target approaches are utilized, deserts, polar ice and deep convective clouds. These sites are characterized using reference AVHRR reflectances as a function of solar zenith angle. The multiple calibration approach is then validated with non-reference AVHRR sensor during the MODIS era, using AVHRR and MODIS SNO measurements. For historical AVHRR satellite having consistent calibration across invariant targets then validates the approach. This calibration effort is in sponsored by the NOAA CDR program to provide climate quality visible calibration coefficients to the remote sensing community. Each of the calibration approaches are unique and when utilized in tandem can accurately calibrate the AVHRR record. AVHRR calibration methods cannot rely on repeatable annual orbits for calibration model development. Inconsistent results prompt code and invariant target examinations that cannot be determined using only single method approaches. Results from this study will be presented at the meeting.