Full Resolution Spectra Research Articles

In situ hyperspectral characteristics and the discriminative ability of remote sensing to coral species in the South China Sea

ABSTRACT Knowledge about the optical features of benthic objects is essential for quantifying spectral signatures, remote sensing-based mapping, and ecological monitoring in coral reefs. However, the spectral identification of benthic species and the accurate measurement of the in situ reflectance spectra of relevant research objects remain underexplored. An underwater radiation measuring system suitable for coral reef environments was specifically designed to obtain in situ reflectance spectra and match benthic photographs of various substrate targets. This instrument has the advantages of obtaining hyperspectral, dual-channel simultaneous measurements, and automatically adjusting the integration time according to the light intensity. Based on in situ hyperspectral datasets, the linear discriminant analysis (LDA) was used for exploring and discriminating spectral characteristics from three taxonomic ranks, which include typical substrates of six community groups, nine coral families, and six Acroporidae species. In situ full-resolution (1-nm) spectra provided the best discrimination ability with mean accuracies of 97.5%, 90.9%, and 91.6% for typical substrates, coral families, and coral species, respectively. The spectral abilities of remote sensors were assessed by applying the spectral response functions of three multispectral sensors (Landsat 8 OLI, Sentinel-2A, and World View-2) to the full-resolution spectra. Discrimination analyses of the simulated spectra demonstrated that the spectral separations of typical substrates might be apparent, with overall classification accuracies of 89.6%, 88.2%, and 90.4% for the Landsat 8 OLI, Sentinel-2A, and World View-2 sensors, respectively. The spectral separation for different corals, however, may not be effective when using multispectral sensors. The discrimination analyses of families and species produced overall classification accuracies of 67.1% and 69.6%, respectively, for the Landsat 8 OLI, 56.0% and 56.0% for the Sentinel-2A sensor, and 64.5% and 61.8% for the World View-2 sensor. In summary, this method has the potential for identifing substrate targets in communities and taxonomic coral groups by applying in situ hyperspectral datasets. Furthermore, multispectral satellite sensors are currently inadequate for spectrally separate corals, while spectral discrimination is possible and practical for different substrate targets with visual spectral differences.

Merging spatial and spectral datasets to place olivine in stratigraphic context at Arruntia crater, a rare window into Vesta's northern hemispheric crust

A major goal of the Dawn mission to Vesta was to test and refine current models of the asteroid's formation by characterizing the distribution of mineral components on its surface. Detection of the mineral olivine by the Visible and Infrared Mapping spectrometer (VIR) and the Framing Camera (FC) onboard Dawn was a key milestone in this effort, and was expected to help resolve a debate regarding the dominant mode of Vesta's petrologic evolution (i.e., magma ocean vs. serial magmatism). However, the subtleties of the olivine spectral signature combined with the small size of individual olivine-rich exposures (tens of meters) prohibits detailed mapping of this petrologically significant mineral component when the data from either instrument are evaluated independently. As a result, the particular role of these olivine exposures in Vesta's geologic history remains largely unresolved.Here, we fully characterize the type locality of Vesta's olivine-rich materials, the northern hemisphere craters Bellicia and Arruntia, using a novel data fusion approach for linking the VIR and FC datasets. Specifically, we have leveraged a spectral mixture analysis framework to create a new dataset that maps, or “extrapolates”, full resolution spectra, derived from VIR data, onto the higher spatial resolution of FC. When used as an exploratory tool in conjunction with the original FC and VIR data, the new “extrapolated” dataset reveals important new details about the distribution of olivine around Bellicia and Arruntia craters.There are clear compositional distinctions between the exposures at the two craters, with a much stronger olivine component in the walls of Bellicia than Arruntia. The proximal Arruntia ejecta appear more consistent with high proportions of an evolved high‑calcium pyroxene (as in eucrites) than with an enhanced olivine component. Examples of diogenite-rich howardite also occur in the region. Further, we leverage Arruntia's role as the freshest large crater in the northern hemisphere, and thus a rare window into the Vesta's northern hemispheric crust, to suggest an overall stratigraphy for the region: a thin veneer of howardite overlies a sequence of diogenite-rich (near surface), olivine-rich (intermediate), and eucrite-rich materials (at depth). The manner of exposure of these various components in a marked stratification point to a plutonic model for emplacing these mineralogically unique components in the near surface of Vesta.

Stokes imaging spectropolarimeter based on channeled polarimetry with full-resolution spectra and aliasing reduction.

A Stokes channeled interference imaging spectropolarimeter with full-resolution spectra and aliasing reduction is presented. The sensor uses a Wollaston prism, a Savart polariscope, and a linear analyzer as a birefringent interferometer, along with two high-order retarders to incorporate channeled polarimetry employing a tempo-spatially mixed modulated mode with no internal moving parts and offering a robust system. The performance of the system is verified through laboratory tests. Compared with the previous sensors, the most significant advantage of the described instrument is that the reconstructed spectra retain the resolution of the interferometer, and the errors in the reconstructed spectral resolved polarization state caused by aliasing between the interference channels are suppressed effectively. Additionally, the advantages of the interferometer are maintained, such as compact structure and high optical throughput.

MetaboID: A graphical user interface package for assignment of 1H NMR spectra of bodyfluids and tissues

Nuclear magnetic resonance based measurements of small molecule mixtures continues to be confronted with the challenge of spectral assignment. While multi-dimensional experiments are capable of addressing this challenge, the imposed time constraint becomes prohibitive, particularly with the large sample sets commonly encountered in metabolomic studies. Thus, one-dimensional spectral assignment is routinely performed, guided by two-dimensional experiments on a selected sample subset; however, a publicly available graphical interface for aiding in this process is currently unavailable. We have collected spectral information for 360 unique compounds from publicly available databases including chemical shift lists and authentic full resolution spectra, supplemented with spectral information for 25 compounds collected in-house at a proton NMR frequency of 900MHz. This library serves as the basis for MetaboID, a Matlab-based user interface designed to aid in the one-dimensional spectral assignment process. The tools of MetaboID were built to guide resonance assignment in order of increasing confidence, starting from cursory compound searches based on chemical shift positions to analysis of authentic spike experiments. Together, these tools streamline the often repetitive task of spectral assignment. The overarching goal of the integrated toolbox of MetaboID is to centralize the one dimensional spectral assignment process, from providing access to large chemical shift libraries to providing a straightforward, intuitive means of spectral comparison. Such a toolbox is expected to be attractive to both experienced and new metabolomic researchers as well as general complex mixture analysts.

Global stratospheric hydrogen peroxide distribution from MIPAS-Envisat full resolution spectra compared to KASIMA model results

Abstract. MIPAS-ENVISAT full resolution spectra were analyzed to obtain a global distribution of hydrogen peroxide (H2O2) in the stratosphere. H2O2 acts as reservoir gas for the HOx family (= H+OH+HO2) and thus, observations of H2O2 provide a better understanding of the HOx chemistry in the atmosphere. A retrieval approach based on constrained least squares fitting was developed and applied to small dedicated spectral analysis windows with maximum H2O2 information and minimum contribution of interfering gases. Due to a low signal to noise ratio in the measured spectra single profiles cannot be used for scientific interpretation and about 100 profiles have to be averaged temporally or spatially. Our retrievals of H2O2 from MIPAS measurements provide meaningful results between approximately 20 and 60 km. A possible impact by the high uncertainty of the reaction rate constant for HO2 + HO2→H2O2 + O2 in our 3D-CTM KASIMA is discussed. We find best agreement between model and observations for applying rate constants according to Christensen et al. (2002) however, a mismatch in vertical profile shape remains. The observations were compared to the model results of KASIMA focusing on low to mid latitudes. Good agreement in spatial distribution and in temporal evolution was found. Highest vmr of H2O2 in the stratosphere were observed and modeled in low latitudes shortly after equinox at about 30 km. The modelled diurnal cycle with lowest vmr shortly after sunrise and highest vmr in the afternoon is confirmed by the MIPAS observations.

Spectroscopic characterization of oils yielded from Brazilian offshore basins: Potential applications of remote sensing

Spectroscopy is the basis to detect and characterize offshore hydrocarbon (HC) seeps through optical remote sensing. Diagnostic spectral features of HCs are linked to their chemical composition and fundamental molecular vibrations (SWIR-TIR features), as well as overtones and combinations of these vibrations (VNIR-SWIR). These features allow for the characterization of oil, oil on water and emulsified oil. This work shows the results of lab and field spectral measurements of 17 petroleum samples yielded from key, oil-rich sedimentary basins in Brazil. Measurements comprised reflectance data (VNIR- SWIR), Attenuated Total Reflectance (ATR), Directional Hemispherical Reflectance (DHR), and emissivity data (TIR). These spectra were analyzed by multivariate techniques, such as Principal Components Analysis (PCA) and Partial Least-Square analysis (PLS). The experimental results indicate that for the VNIR-SWIR range: (i) spectral features can be recognized for crude oil, emulsified oil and oil on ocean water; (ii) different oil types can be qualitatively distinguished based on these features (i.e. light or heavy), even considering oil on water; (iii) the same applies for oil measurements simulated at the spectral resolution of hyperspectral (357-bands/ProSpecTIR) and multispectral (9-bands/ASTER) sensors. Within TIR wavelengths (3–14 μm), typical HC spectral features can also be resolved and oil types qualitatively discriminated using PCA/PLS, including both full-resolution spectra and spectra resampled to hyperspectral sensor (128-bands/SEBASS). However, despite the fact that oil emissivity is always lower than that of water, such separation seems unfeasible using 8–12 μm TIR features only; emissivity spectra are essentially flat for all samples in this interval. This research demonstrated that oil can be qualitatively distinguished based on both VNIR-SWIR and TIR spectroscopy data, with important implications for remote off-shore oil exploration and classification of oil leakages.

Hierarchical Alignment and Full Resolution Pattern Recognition of 2D NMR Spectra: Application to Nematode Chemical Ecology

Nuclear magnetic resonance (NMR) is the most widely used nondestructive technique in analytical chemistry. In recent years, it has been applied to metabolic profiling due to its high reproducibility, capacity for relative and absolute quantification, atomic resolution, and ability to detect a broad range of compounds in an untargeted manner. While one-dimensional (1D) 1H NMR experiments are popular in metabolic profiling due to their simplicity and fast acquisition times, two-dimensional (2D) NMR spectra offer increased spectral resolution as well as atomic correlations, which aid in the assignment of known small molecules and the structural elucidation of novel compounds. Given the small number of statistical analysis methods for 2D NMR spectra, we developed a new approach for the analysis, information recovery, and display of 2D NMR spectral data. We present a native 2D peak alignment algorithm we term HATS, for hierarchical alignment of two-dimensional spectra, enabling pattern recognition (PR) using full-resolution spectra. Principle component analysis (PCA) and partial least squares (PLS) regression of full resolution total correlation spectroscopy (TOCSY) spectra greatly aid the assignment and interpretation of statistical pattern recognition results by producing back-scaled loading plots that look like traditional TOCSY spectra but incorporate qualitative and quantitative biological information of the resonances. The HATS-PR methodology is demonstrated here using multiple 2D TOCSY spectra of the exudates from two nematode species: Pristionchus pacificus and Panagrellus redivivus. We show the utility of this integrated approach with the rapid, semiautomated assignment of small molecules differentiating the two species and the identification of spectral regions suggesting the presence of species-specific compounds. These results demonstrate that the combination of 2D NMR spectra with full-resolution statistical analysis provides a platform for chemical and biological studies in cellular biochemistry, metabolomics, and chemical ecology.

Validation of water vapour profiles (version 13) retrieved by the IMK/IAA scientific retrieval processor based on full resolution spectra measured by MIPAS on board Envisat

Abstract. Vertical profiles of stratospheric water vapour measured by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) with the full resolution mode between September 2002 and March 2004 and retrieved with the IMK/IAA scientific retrieval processor were compared to a number of independent measurements in order to estimate the bias and to validate the existing precision estimates of the MIPAS data. The estimated precision for MIPAS is 5 to 10% in the stratosphere, depending on altitude, latitude, and season. The independent instruments were: the Halogen Occultation Experiment (HALOE), the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), the Improved Limb Atmospheric Spectrometer-II (ILAS-II), the Polar Ozone and Aerosol Measurement (POAM III) instrument, the Middle Atmospheric Water Vapour Radiometer (MIAWARA), the Michelson Interferometer for Passive Atmospheric Sounding, balloon-borne version (MIPAS-B), the Airborne Microwave Stratospheric Observing System (AMSOS), the Fluorescent Stratospheric Hygrometer for Balloon (FLASH-B), the NOAA frostpoint hygrometer, and the Fast In Situ Hygrometer (FISH). For the in-situ measurements and the ground based, air- and balloon borne remote sensing instruments, the measurements are restricted to central and northern Europe. The comparisons to satellite-borne instruments are predominantly at mid- to high latitudes on both hemispheres. In the stratosphere there is no clear indication of a bias in MIPAS data, because the independent measurements in some cases are drier and in some cases are moister than the MIPAS measurements. Compared to the infrared measurements of MIPAS, measurements in the ultraviolet and visible have a tendency to be high, whereas microwave measurements have a tendency to be low. The results of χ2-based precision validation are somewhat controversial among the comparison estimates. However, for comparison instruments whose error budget also includes errors due to uncertainties in spectrally interfering species and where good coincidences were found, the χ2 values found are in the expected range or even below. This suggests that there is no evidence of systematically underestimated MIPAS random errors.