The ability of sensors to detect changes in the Earth’s environment is dependent on retrieving radiometrically consistent and calibrated measurements from its surface. Intercalibration provides consistency among satellite instruments and ensures fidelity of scientific information. Intercalibration is especially important for spaceborne satellites without any on-board calibration, as accuracy of instruments is significantly affected by changes that occur postlaunch. To better understand the key parameters that impact the intercalibration process, this paper describes a simulation environment that was developed to support the primary mission of the Algodones Dunes campaign. Specifically, measurements obtained from the campaign were utilized to create a synthetic landscape to assess the feasibility of using the Algodones Dunes system as an intercalibration site for spaceborne instruments. The impact of two key parameters (differing view-angles and temporal offsets between instruments) on the intercalibration process was assessed. Results of these studies indicate that although the accuracy of intercalibration is sensitive to these parameters, proper knowledge of their impact leads to situations that minimize their effect. This paper concludes with a case study that addresses the feasibility of performing intercalibration on the International Space Station’s platform to support NASA’s CLARREO, the climate absolute radiance and refractivity observatory, mission.
We compare field hyperspectral bidirectional reflectance distribution function (BRDF) measurements acquired by a hyperspectral goniometer system known as the goniometer of the Rochester Institute of Technology (GRIT) during an experiment in the Algodones Dunes system in March 2015 with NASA Goddard’s light detection and ranging, hyperspectral, and thermal imagery of the site acquired during the experiment. We augment our field spectral data collection with laboratory hyperspectral BRDF measurements of samples brought back from the Algodones Dunes site using GRIT and our second-generation goniometer GRIT-two (GRIT-T). In these laboratory experiments, we vary geophysical parameters such as sediment density and grain size distribution of the sediments that would typically impact observed BRDF with the goal of extending the range of applicability of our resulting BRDF spectral libraries. Geotechnical measurements on site confirm the variability of geophysical parameters such as density and grain size distributions within the dune system, and measurements with GRIT and GRIT-T demonstrate the impact on observed spectral variation. By augmenting field spectral libraries with laboratory BRDF, we show that a greater proportion of the dune system is more faithfully represented in the expanded spectral library. Beyond developing appropriate calibration data for airborne and satellite imagery of the Algodones Dunes, laboratory and field studies also support goals to develop reliable retrieval methods for geophysical quantities such as sediment density directly from spectral imagery. We consider approaches based on the Hapke model. Our approaches use the invariance of the observed functional forms of the single scattering phase function, which must be invariant to differences in the illumination geometry. Fill factor is retrieved and correlates with expected direct measurements of sediment density in a laboratory setting.
Magnetic resonance elastography (MRE) is a phase-contrast MRI based technique that allows quantitative, noninvasive assessment of the mechanical properties of tissues by the introduction of shear waves into the body and measurement of the resulting displacements. In MRE, the calculated stiffness values are affected by noise, which is amplified by the inversion process. It would be useful to know that beyond some SNR threshold, the stiffness values are accurate within some confidence limit. The most common methods to calculate SNR values in MRE are variations of displacement SNR, which estimate the noise in the measured displacement. However, the accuracy of stiffness determination depends not only on the displacement SNR, but also on the wavelength of the shear wave, in turn dependent on the stiffness of the underlying material. More recently, the SNR of the octahedral shear strain (OSS) has been proposed as a more appropriate measure, since shear deformation is the signal in MRE. We also propose here another measure based on the SNR of the Laplacian of the data, since this is the most noise sensitive quantity calculated when performing direct inversion of the Helmholtz equation. The three SNR measures were compared on simulated data for materials of different stiffness with varying amounts of noise using three inversion algorithms commonly used in MRE (phase gradient, local frequency estimation, and direct inversion). We demonstrate that the proper SNR measure for MRE depends on the inversion algorithm used, and, more precisely, on the order of derivatives used in the inversion process.