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At least 253 records · Page 14

Vicarious Calibration of the Long Near Infrared Band: Cross-Sensor Differences in Sensitivity

Numerous assumptions and approximations are employed when translating satellite-derived radiance to surface remote sensing reflectance (RRS) for ocean color applications. Among these is the vicarious calibration coefficient (g) of the “long” near infrared band (NIRL) used for atmospheric correction. For this band, the prelaunch calibration has always been deemed sufficient [thus g(NIRL) = 1.00] as long as other bands are vicariously calibrated. Recent research, however, suggests that Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua RRS time series is quite sensitive to g(NIRL) (and associated vicarious gains in other bands). In this work, we assessed the sensitivity of Visible Infrared Imaging Radiometer Suite onboard the Suomi National Polar-orbiting Partnership satellite (VIIRS/SNPP) RRS to NIRL calibration and compared our results to previous MODIS/Aqua and Sea-viewing Wide Field-of-View Sensor onboard OrbView2 (SeaWiFS)/OrbView2 analysis. In doing so, we note that g(NIRL) sensitivities of mission-averaged RRS time series are lower for VIIRS and Sea-WiFS, relative to MODIS. At the scale of monthly climatologies (MCs), however, all sensors show prominent g(NIRL) sensitivity with that of SeaWiFS being the most substantial. These findings informed simulation analyses, whereby we identified signal-tonoise ratio (SNR) and radiant path geometry, as well as their interaction, as having notable impacts on g(NIRL) sensitivity. As such, g(NIRL) sensitivity is a necessary consideration for reflectance uncertainty budgets, especially for sensors with higher NIR SNR or particular prevailing radiant path geometries. Given the geometry components embedded within g(NIRL) sensitivity, such studies should be coupled with cross-sensor intercalibrations [e.g., using simultaneous same view (SSV) measurements] toward minimizing NIRL errors between satellite instruments, but such efforts will not completely remediate remaining cross-sensor biases in RRS. Index Terms—Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua, ocean color, ocean gyres, Sea-viewing Wide Field-of-View Sensor onboard OrbView2 (SeaWiFS), system vicarious calibration (SVC), Visible Infrared Imaging Radiometer Suite onboard the Suomi National Polar-orbiting Partnership satellite (VIIRS/SNPP).

MODIS↗

Quantitative spectroscopy for the analysis of GOME data

Accurate analysis of the global ozone monitoring experiment (GOME) data to obtain atmospheric constituents requires reliable, traceable spectroscopic parameters for atmospheric absorption and scattering. Results are summarized for research that includes: the re-determination of Rayleigh scattering cross sections and phase functions for the 200 nm to 1000 nm range; the analysis of solar spectra to obtain a high-resolution reference spectrum with excellent absolute vacuum wavelength calibration; Ring effect cross sections and phase functions determined directly from accurate molecular parameters of N2 and O2; O2 A band line intensities and pressure broadening coefficients; and the analysis of absolute accuracies for ultraviolet and visible absorption cross sections of O3 and other trace species measurable by GOME.

Chance, K.↗

Recent Surface Reflectance Measurement Campaigns with Emphasis on Best Practices, SI Traceability and Uncertainty Estimation

A significant problem facing the optical satellite calibration community is limited knowledge of the uncertainties associated with fundamental measurements, such as surface reflectance, used to derive satellite radiometric calibration estimates. In addition, it is difficult to compare the capabilities of calibration teams around the globe, which leads to differences in the estimated calibration of optical satellite sensors. This paper reports on two recent field campaigns that were designed to isolate common uncertainties within and across calibration groups, particularly with respect to ground-based surface reflectance measurements. Initial results from these efforts suggest the uncertainties can be as low as 1.5% to 2.5%. In addition, methods for improving the cross-comparison of calibration teams are suggested that can potentially reduce the differences in the calibration estimates of optical satellite sensors.

reflectance measurements↗

Vicarious Calibration of the Long Near Infrared Band: Cross-Sensor Differences in Sensitivity

Numerous assumptions and approximations are employed when translating satellite-derived radiance to surface remote sensing reflectance (RRS) for ocean color applications. Among these is the vicarious calibration coefficient (g) of the ‘long’ near infrared band (NIRL) used for atmospheric correction. For this band, the pre-launch calibration has always been deemed sufficient [thus g(NIRL) = 1.00] as long as other bands are vicariously calibrated. Recent research, however, suggests that MODIS/Aqua RRS time series are quite sensitive to g(NIRL) (and associated vicarious gains in other bands). In this work, we assessed the sensitivity of VIIRS/SNPP RRS to NIRL calibration, and compared our results to previous MODIS/Aqua and SeaWiFS/OrbView2 analysis. In doing so, we note g(NIRL) sensitivities of mission-averaged RRS timeseries are lower for VIIRS and SeaWiFS, relative to MODIS. At the scale of monthly climatologies, however, all sensors show prominent g(NIRL) sensitivity, with that of SeaWiFS being the most substantial. These findings informed simulation analyses, whereby we identified signal-to-noise ratio (SNR) and radiant path geometry, as well as their interaction, as having notable impacts on g(NIRL) sensitivity. As such, g(NIRL) sensitivity is a necessary consideration for reflectance uncertainty budgets, especially for sensors with higher NIR SNR or particular prevailing radiant path geometries. Given the geometry components embedded within g(NIRL) sensitivity, such studies should be coupled with cross-sensor intercalibrations (e.g., using simultaneous same view measurements) toward minimizing NIRL errors between satellite instruments, but such efforts will not completely remediate remaining cross-sensor biases in RRS.

Brian B Barnes↗

Aerosol and Cloud Observations and Data Products by the GLAS Polar Orbiting Lidar Instrument

The Geoscience Laser Altimeter System (GLAS) launched in 2003 is the first polar orbiting satellite lidar. The instrument was designed for high performance observations of the distribution and optical scattering cross sections of clouds and aerosol. The backscatter lidar operates at two wavelengths, 532 and 1064 nm. Both receiver channels meet and exceed their design goals, and beginning with a two month period through October and November 2003, an excellent global lidar data set now exists. The data products for atmospheric observations include the calibrated, attenuated backscatter cross section for cloud and aerosol; height detection for multiple cloud layers; planetary boundary layer height; cirrus and aerosol optical depth and the height distribution of aerosol and cloud scattering cross section profiles. The data sets are now in open release through the NASA data distribution system. The initial results on global statistics for cloud and aerosol distribution has been produced and in some cases compared to other satellite observations. The sensitivity of the cloud measurements is such that the 70% global cloud coverage result should be the most accurate to date. Results on the global distribution of aerosol are the first that produce the true height distribution for model inter-comparison.

Spinhirne, J. D.↗

Extraction of quantitative surface characteristics from AIRSAR data for Death Valley, California

Polarimetric Airborne Synthetic Aperture Radar (AIRSAR) data were collected for the Geologic Remote Sensing Field Experiment (GRSFE) over Death Valley, California, USA, in Sep. 1989. AIRSAR is a four-look, quad-polarization, three frequency instrument. It collects measurements at C-band (5.66 cm), L-band (23.98 cm), and P-band (68.13 cm), and has a GIFOV of 10 meters and a swath width of 12 kilometers. Because the radar measures at three wavelengths, different scales of surface roughness are measured. Also, dielectric constants can be calculated from the data. The AIRSAR data were calibrated using in-scene trihedral corner reflectors to remove cross-talk; and to calibrate the phase, amplitude, and co-channel gain imbalance. The calibration allows for the extraction of accurate values of rms surface roughness, dielectric constants, sigma(sub 0) backscatter, and polarization information. The radar data sets allow quantitative characterization of small scale surface structure of geologic units, providing information about the physical and chemical processes that control the surface morphology. Combining the quantitative information extracted from the radar data with other remotely sensed data sets allows discrimination, identification and mapping of geologic units that may be difficult to discern using conventional techniques.

Kierein-Young, K. S.↗

External calibration of SIR-B imagery with area-extended and point targets

Data-takes on two ascending orbits of the Shuttle Imaging Radar-B (SIR-B) over an agricultural test site in west-central Illinois were used to establish end-to-end transfer functions for conversion of the digital numbers on the 8-bit image to values of the radar backscattering coefficient sigma sup 0 (sq m/sq. m) in dB. The transfer function for each data-take was defined by the SIR-B response to an array of six calibrated point targets of known radar cross-section (transponders) and to a large number of area-extended targets also with known radar cross-section as measured by externally calibrated, truck-mounted scatterometers. The radar cross-section of each transponder at the SIR-B center frequency was measured on an antenna range as a function of local angle of incidence. Two truck-mounted scatterometers observed 20 to 80 agricultural fields daily at 1.6 GHz with HH polarization and at azimuth viewing angles and incidence angles equivalent to those of the SIR-B. The form of the transfer function is completely defined by the SIR-B receiver and the incoherent averaging procedure incorporated into production of the standard SIR-B image product.

Dobson, M. C.↗

Constraints on Future Analysis Metadata Systems in High Energy Physics

In high energy physics (HEP), analysis metadata comes in many forms—from theoretical cross-sections, to calibration corrections, to details about file processing. Correctly applying metadata is a crucial and often time-consuming step in an analysis, but designing analysis metadata systems has historically received little direct attention. Among other considerations, an ideal metadata tool should be easy to use by new analysers, should scale to large data volumes and diverse processing paradigms, and should enable future analysis reinterpretation. This document, which is the product of community discussions organised by the HEP Software Foundation, categorises types of metadata by scope and format and gives examples of current metadata solutions. Important design considerations for metadata systems, including sociological factors, analysis preservation efforts, and technical factors, are discussed. A list of best practices and technical requirements for future analysis metadata systems is presented. These best practices could guide the development of a future cross-experimental effort for analysis metadata tools.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Validation of Long Bone Mechanical Properties from Densitometry

The objective of this study was to assess whether cross-sectional areal properties, calculated from densitometry, correlate to the true flexural properties. Right and left male embalmed tibiae were used in the study. Prior to scanning, the proximal end of each tibia was potted in a fixture with registration pins, flushed thoroughly with water under pressure to remove trapped air, and then placed in a constant thickness water bath attached to a precision indexer. Two sets of three scans of the entire tibia were taken with an Hologic QDR 1000/W densitometer at rotations of 0, 45, and 90 degrees about the tibia long axis. An aluminum step phantom and a bone step phantom, machined from bovine cortical bone, were also in the bath and scanned separately. Pixel attenuation data from the two sets of scans were averaged to reduce noise. Pixel data from the high energy beam were then converted to equivalent thicknesses using calibration equations. Cross-sectional areal properties (centroid, principal area moments and principal angle) along the length were computed from the three registered scans using methods developed in our laboratory. Flexural rigidities. Four strain gages were bonded around the circumference of each of 5 cross-sections encompassing the entire diaphysis. A known transverse load was then applied to the distal end and the bone was rotated 360 degrees in eight increments of 45 degrees each. Strains from the eight orientations were analyzed along with the known applied bending moments at each section to compute section centroids, curvatures, principal flexural rigidities and principal angle. Reference axes between the two methods were maintained within +/- 0.5 degrees using an electronic inclinometer. Principal angles (flexural - areal) differed by -2.0 +/- 4.0 degrees, and 1.0 +/- 2.5 degrees for the right and left tibia, respectively. Section principal flexural rigidities were highly correlated to principal areal moments (right: r(sup 2)= 0.997; left: r(sup 2)= 0.978) indicating a nearly constant effective flexural modulus. Right and left tibia exhibited a very high degree of symmetry when comparing either flexural or areal properties. To our knowledge this is the first study to validate the use of densitometry (DXA) to predict three dimensional structural properties of long bones. Our initial results support the conclusion that bone mineral and its distribution are the primary determinants of flexural modulus and rigidity.

Whalen, R.↗

External calibration of SIR-B Imagery with area-extended and point targets

Data collected by the Shuttle Imaging Radar-B (SIR-B) on two ascending orbits over a site in west-central Illinois were used to establish end-to-end transfer functions for conversion of the digital numbers on the eight-bit image to values of the radar backscattering coefficient, sigma(0). The transfer function for each data take was defined by the SIR response to an array of six calibrated point targets of known radar cross section and to a large number of area-extended targets, also with a known cross section, as measured by externally calibrated, truck-mounted scatterometers. In spite of variance in the SIR transmit power, end-to-end transfer functions generated from either point targets or area-extended targets were found to yield close agreement for a given pass, indicating that targets of known radar cross section can be used to provide transfer functions for orbital SAR. Although the use of area-extended targets yielded the most satisfactory results, the use of point targets is far simpler and may be the preferred alternative for many situations.

Dobson, M. C.↗

Self-calibrating optical galaxy cluster selection bias using cluster, galaxy, and shear cross-correlations

ABSTRACT The clustering signals of galaxy clusters are powerful tools for self-calibrating the mass–observable relation and are complementary to cluster abundance and lensing. In this work, we explore the possibility of combining three correlation functions – cluster lensing, the cluster–galaxy cross-correlation function, and the galaxy autocorrelation function – to self-calibrate optical cluster selection bias, the boosted clustering and lensing signals in a richness-selected sample mainly caused by projection effects. We develop mock catalogues of redMaGiC-like galaxies and redMaPPer-like clusters by applying halo occupation distribution models to N-body simulations and using counts-in-cylinders around massive haloes as a richness proxy. In addition to the previously known small-scale boost in projected correlation functions, we find that the projection effects also significantly boost three-dimensional correlation functions to scales of 100 $h^{-1} \, \rm Mpc$. We perform a likelihood analysis assuming survey conditions similar to the Dark Energy Survey and show that the selection bias can be self-consistently constrained at the 10 per cent level. We discuss strategies for applying this approach to real data. We expect that expanding the analysis to smaller scales and using deeper lensing data would further improve the constraints on cluster selection bias.

Astronomy & Astrophysics↗

Mojave remote sensing field experiment

The Mojave Remote Sensing Field Experiment (MFE), conducted in June 1988, involved acquisition of Thermal Infrared Multispectral Scanner (TIMS); C, L, and P-band polarimetric radar (AIRSAR) data; and simultaneous field observations at the Pisgah and Cima volcanic fields, and Lavic and Silver Lake Playas, Mojave Desert, California. A LANDSAT Thematic Mapper (TM) scene is also included in the MFE archive. TM-based reflectance and TIMS-based emissivity surface spectra were extracted for selected surfaces. Radiative transfer procedures were used to model the atmosphere and surface simultaneously, with the constraint that the spectra must be consistent with field-based spectral observations. AIRSAR data were calibrated to backscatter cross sections using corner reflectors deployed at target sites. Analyses of MFE data focus on extraction of reflectance, emissivity, and cross section for lava flows of various ages and degradation states. Results have relevance for the evolution of volcanic plains on Venus and Mars.

Arvidson, Raymond E.↗

Analysis of the GOES 6.7 micrometer channel observations during FIRE 2

Clouds form in moist environments. FIRE Phase II Cirrus Implementation Plan (August, 1990) noted the need for mesoscale measurements of upper tropospheric water vapor content. These measurements are needed for initializing and verifying numerical weather prediction models and for describing the environment in which cirrus clouds develop and dissipate. Various instruments where deployed to measure the water vapor amounts of the upper troposphere during FIRE II (e.g. Raman lidar, CLASS sonds and new cryogenic frost hygrometer on-board aircraft). The formation, maintenance and dissipation of cirrus clouds involve the time variation of the water budget of the upper troposphere. The GOES 6.7 mu m radiance observations are sensitive to the upper tropospheric relative humidity, and therefore proved extremely valuable in planning aircraft missions during the field phase of FIRE II. Warm 6.7 mu m equivalent black body temperatures indicate a relatively dry upper troposphere and were associated with regions generally free of cirrus clouds. Regions that were colder, implying more moisture was available may or may not have had cirrus clouds present. Animation of a time sequence of 6.7 mu m images was particularly useful in planning various FIRE missions. The 6.7 mu m observations can also be very valuable in the verification of model simulations and describing the upper tropospheric synoptic conditions. A quantitative analysis of the 6.7 mu m measurement is required to successfully incorporate these satellite observations into describing the upper tropospheric water vapor budget. Recently, Soden and Bretherton (1993) have proposed a method of deriving an upper tropospheric humidity based on observations from the GOES 6.7 mu m observations. The method is summarized in the next section. In their paper they compare their retrieval method to radiance simulations. Observations were also compared to ECMWF model output to assess the model performance. The FIRE experiment provides a unique opportunity to further verify the GOES upper tropospheric relative humidity retrieval scheme by providing (1) aircraft observations to cross-validate the calibration of the GOES 6.7 mu m channel, (2) accurate upper tropospheric water vapor concentrations for verification, and (3) veritical variability of upper tropospheric water vapor.

Soden, B. J.↗

The NASA/JPL Airborne Synthetic Aperture Radar System

In this paper we will briefly describe the instrument characteristics, the evolution of various radar modes, the instrument performance and improvement in the knowledge of the positioning and attitude information of the NASA/JPL airborne synthetic aperture radar (SAR). This system operates in the fully polarimetric mode in the P, L, and C band simultaneously or in the interferometric mode in both the L and C band simultaneously. We also summarize the progress of the data processing effort, especially in the interferometry processing and we address the issue of processing and calibrating the cross-track interferometry data.

Lou, Yunling↗

The NASA/JPL Airborne Synthetic Aperture Radar System

The NASA/JPL airborne SAR (AIRSAR) system operates in the fully polarimetric mode at P-, L- and C-band simultaneously or in the interferometric mode in both L- and C-band simultaneously. The system became operational in late 1987 and flew its first mission aboard a DC-8 aircraft operated by NASA's Ames Research Center in Mountain View, California. Since then, the AIRSAR has flown missions every year and acquired images in North, Central and South America, Europe and Australia. In this paper, we will briefly describe the instrument characteristics, the evolution of the various radar modes, the instrument performance, and improvement in the knowledge of the positioning and attitude information of the radar. In addition, we will summarize the progress of the data processing effort especially in the interferometry processing. Finally, we will address the issue of processing and calibrating the cross-track interferometry (XTI) data.

Kim, Yun-Jin↗

Cloud Algorithm Design and Performance for the 2002 Geoscience Laser Altimeter System Mission

A satellite borne lidar instrument, the Geoscience Laser Altimeter System (GLAS), is to be launched in late 2002 and will provide continuous profiling of atmospheric clouds and aerosol on a global basis. Data processing algorithms have been developed to provide operational data products in near real time. Basic data products for cloud observations are the height of the top and bottom of single to multiple cloud layers and the lidar calibrated observed backscatter cross section up to the level of signal attenuation. In addition the optical depth and vertical profile of visible extinction cross section of many transmissive cloud layers and most haze layers are to be derived. The optical thickness is derivable in some cases from the attenuation of the molecular scattering below cloud base. In other cases an assumption of the scattering phase function is required. In both cases a estimated correction for multiple scattering is required. The data processing algorithms have been tested in part from aircraft measurements used to simulated satellite data. The GLAS lidar observations will be made from an orbit that will allow inter comparison with all other existing satellite cloud measurements.

Spinhirne, J. D.↗