Many ultra-diffuse galaxies (UDGs) have been discovered in the Coma cluster, and there is evidence that some, notably Dragonfly 44, have Milky Way-like dynamical masses despite dwarf-like stellar masses. We used X-ray, UV, and optical data to investigate the star formation and nuclear activity in the Coma UDGs, and we obtained deep UV and X-ray data (Swift and XMM-Newton) for Dragonfly 44 to search for low-level star formation, hot circumgalactic gas, and the integrated emission from X-ray binaries. Among the Coma UDGs, we find UV luminosities consistent with quiescence but NUV−r colors indicating star formation in the past Gyr. This indicates that the UDGs were recently quenched. The r-band luminosity declines with projected distance from the Coma core. The Dragonfly 44 UV luminosity is also consistent with quiescence, with SFR 10⁸M_⊙ within the virial radius, which would normally be expected for a dynamically massive galaxy. The absence of bright, low mass X-ray binaries is consistent with the expectation from the galaxy total stellar mass, but it is unlikely if most low-mass X-ray binaries form in globular clusters, as Dragonfly 44 has a very large population. Based on the UV and X-ray analysis, the Coma UDGs are consistent with quenched dwarf galaxies, although we cannot rule out a dynamically massive population.

Polarization provides useful quantitative information about scattering surfaces. In hyperspectral remote sensing of natural surfaces composed of granular materials, there are relatively few studies of polarization. Most earlier remote sensing studies of polarization have been based on multi-spectral data, and the majority focused on the negative branch of polarization, which typically appears at phase angles less than 20 degrees, using models with limited accuracy. Models of the positive branch have also shown limitations, particularly at longer phase angles. We review these earlier studies by Hapke and Shkuratov and present the results of our laboratory study using hyperspectral polarization imagery of particulate surfaces. Although the linear polarization ratio is typically a nonlinear function of phase angle, our results show that in an approximately linear region of the polarization curve, there is a correlation between the slope of the linear polarization ratio and the average grain size.

We present a comprehensive hyperspectral bi-directional reflectance model for a pristine optical-grade white Spectralon® panel with full azimuthal coverage, a wide range of view zenith angles and incident illumination zenith angles, throughout ultraviolet, visible, near infrared and shortwave infrared wavelengths (350–2500 nm). Measurements were acquired using the Goniometer of the Rochester Institute of Technology-Two, which incorporates Analytical Spectral Device FieldSpec FR4 spectroradiometers. Residual plots show that the empirical model is accurate to within 1–2% reflectance within most of the observing hemisphere. We demonstrate an application of the Spectralon® panel model to hyperspectral imagery acquired during a field experiment at the RIT Tait Preserve where a pair of field Spectralon® panels was imaged from various view geometries from both drone and mast-mounted hyperspectral imaging systems.

We characterized the bi‐directional spectro‐polarimetry of olivine sands of varying grain size distributions for a comprehensive set of measurement and illumination angles over a wavelength range of 350–2,500 nm. Our laboratory instrumentation included a hyperspectral goniometer, a broadband linear polarizer, and a tungsten‐halogen illumination source. Three distinct grain size distributions of olivine sand samples were used in our experiments. As a function of azimuth, we measured a significant degree of anisotropic scattering, that depends directly on polarization angles, resulting in a distribution that cannot be accurately described solely using phase angle. For media of uniform or similar composition, we observed robust separability of grain size distributions using spectro‐polarimetry. We compared Hapke's polarimetric model for semi‐infinite granular media with a new empirical polarimetric model that we developed. This empirical model more accurately replicates the scattering of unpolarized incident light as a function of all view azimuth, view zenith, and polarization angles for all incident zenith angles. Parameters of our empirical polarimetric model that determine the magnitude of polarization correlate linearly with the inverse diffuse reflectances of the olivine sand samples, exhibiting phenomenology that is most likely due to the Umov effect. Because of the linearity of the correlations, our results show that polarimetry can be used to retrieve medium parameters, such as grain size distributions. We provide our data online and freely available in a Zenodo/GitHub repository.

Hyperspectral imaging (HSI), or imaging spectroscopy, is applicable to many fields and topics. In Earth remote sensing, these can include automatic classification applications^{1 – 3} as well as abundance maps based on endmember decomposition.^{4 – 7} If paired with radiative transfer models or band selection algorithms, HSI enables remote sensing retrievals of biophysical and geophysical parameters of interest within the scene such as soil moisture content^{8 – 10} and sediment filling factor;^11,12 vegetation parameters such as biomass, leaf area index, and pigment concentrations;^{13 – 16} or concentration of bio-optical constituents in the water column.^{17 – 22} However, because of the “pushbroom” imaging architecture commonly employed in hyperspectral image acquisition, in which the along-track spatial dimension is achieved through the motion of the imaging platform, hyperspectral remote sensing imagery most often consists of either single images of a scene, or alternatively, several images separated by intervals of minutes, hours or longer time intervals.

Plant leaves frequently absorb more photons than can be instantaneously used to power photosynthetic electron transport, and some excess photons are re-emitted as sun-induced chlorophyll fluorescence (SIF). SIF has become a commonly used signal for remotely monitoring gross primary productivity (GPP) from both satellite-based detectors and proximal platforms nearer to the Earth’s surface. There is wide variability in the configuration of proximal SIF-measuring instrument systems and in the magnitude of retrieved SIF values from these systems, suggesting important sensitivities to calibration and characterization of SIF-measuring instrumentation. We present the results of laboratory radiometric calibrations, detector and optical hardware characterizations, wavelength calibrations, and quantifications of the effects of key corrections needed for SIF retrievals in field settings. Notably, these characterizations included variable discrepancies between nominal and measured wavelength positions that, if left uncorrected, result in retrieving artificially large SIF values. Error and uncertainty distributions determined from laboratory testing were used as inputs to a Monte Carlo uncertainty quantification framework, which simulated the effects of each component or correction on retrieved SIF values. This framework showed that SIF retrievals are highly sensitive to hardware specifications that determine system throughput, such as lens tube size and fiber optic cable alignment, and to effects that contribute to artificial in-filling in the absorption features used for SIF retrievals, such as electronic dark current and atmospheric corrections. Our findings suggest that variability in proximal SIF measurement system configurations, calibration methods, and corrections applied during SIF retrieval may contribute to variability of published SIF values.