991 resultados para reflectance


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Annually laminated (varved) sediments of proglacial Lake Silvaplana (46 ̊27’N, 9 ̊48’E, 1791 m a.s.l., Engadine, eastern Swiss Alps) provide an excellent archive for quantitative high-resolution (seasonal – annual) reconstruction of high- and lowfrequency climate signals back to AD 1580. The chronology of the core is based on varve counting, Cs-137, Pb-210 and event stratigraphy. In this study we present a reconstruction based on in-situ reflectance spectroscopy. In situ reflectance spectroscopy is known as a cost- and time-effective non destructtive method for semi-quantitative analysis of pigments (e.g., chlorines and carotenoids) and of lithoclastic sediment fractions. Reflectance-dependent absorption (RDA) was measured with a Gretac Macbeth spectrolino at 2 mm resolution. The spectral coverage ranges from 380 nm to 730 nm at 10 nm band resolution. In proglacial Lake Silvaplana, 99% of the sediment is lithoclastic prior to AD 1950. Therefore, we concentrate on absorption features that are characteristic for lithoclastic sediment fractions. In Lake Silvaplana, two significant correlations that are stable in time were found between RDA typical for lithoclastics and meteorological data: (1) the time series R 570 /R 630 (ratio between RDA at 570 nm and 630 nm) of varves in Lake Silvaplana and May to October temperatures at nearby station of Sils correlate highly significantly (calibration period AD 1864 – 1951, r = 0.74, p < 0.01 for 5ptsmoothed series; RMSE is 0.28 ̊C, RE = 0.41 and CE = 0.38), and (2) the minimum reflectance within the 690nm band (min690) data correlate with May to October (calibration period AD 1864 – 1951, r = 0.68, p < 0.01 for 5pt-smoothed series; RMSE = 0.22 ̊C, RE = 0.5, CE = 0.31). Both proxy series (min690nm and R 570 /R 630 values) are internally highly consistent (r = 0.8, p < 0.001). In proglacial Lake Silvaplana the largest amount of sediment is transported by glacial meltwater. The melting season spans approximately from May to October, which gives us a good understanding of the geophysical processes explaining the correlations between lithoclastic proxies and the meteorological data. The reconstructions were extended back to AD 1580 and show a broad corresponddence with fully independent reconstructions from tree rings and documentary data.

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We present a new approach to diffuse reflectance estimation for dynamic scenes. Non-parametric image statistics are used to transfer reflectance properties from a static example set to a dynamic image sequence. The approach allows diffuse reflectance estimation for surface materials with inhomogeneous appearance, such as those which commonly occur with patterned or textured clothing. Material editing is also possible by transferring edited reflectance properties. Material reflectance properties are initially estimated from static images of the subject under multiple directional illuminations using photometric stereo. The estimated reflectance together with the corresponding image under uniform ambient illumination form a prior set of reference material observations. Material reflectance properties are then estimated for video sequences of a moving person captured under uniform ambient illumination by matching the observed local image statistics to the reference observations. Results demonstrate that the transfer of reflectance properties enables estimation of the dynamic surface normals and subsequent relighting combined with material editing. This approach overcomes limitations of previous work on material transfer and relighting of dynamic scenes which was limited to surfaces with regions of homogeneous reflectance. We evaluate our approach for relighting 3D model sequences reconstructed from multiple view video. Comparison to previous model relighting demonstrates improved reproduction of detailed texture and shape dynamics.

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We have measured the bidirectional reflectance of spherical micrometer-sized water-ice particles in the visible spectral range over a wide range of incidence and emission angles. The small ice spheres were produced by spraying fine water droplets directly into liquid nitrogen. The resulting mean particle radii are 1.47 + 0.96 - 0.58 μm. Such a material shares many properties with ice in comets and at the surface of icy satellites. Measurements show that the fresh sample material is highly backscattering, contrasting with natural terrestrial snow and frost. The formation of agglomerates of particles during the sample production results in a noticeable variability of the photometric properties of the samples in their initial state. We have also observed significant temporal evolutions of the scattering behavior of the samples, shifting towards more forward scattering within some tens of hours, resulting most likely from sintering processes. All reflectance data are fitted by the Hapke photometric model (1993 and 2002 formulation) with a one/two/three-parameter Henyey-Greenstein phase function and the resulting Hapke parameters are provided. These parameters can be used to compare laboratory results with the observed photometric behaviors of astronomical objects. We show, in particular, that the optical properties of the fresh micrometer-sized ice samples can be used to reproduce the predominant backscattering in the phase curves of Enceladus and Europa.

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Images of an object under different illumination are known to provide strong cues about the object surface. A mathematical formalization of how to recover the normal map of such a surface leads to the so-called uncalibrated photometric stereo problem. In the simplest instance, this problem can be reduced to the task of identifying only three parameters: the so-called generalized bas-relief (GBR) ambiguity. The challenge is to find additional general assumptions about the object, that identify these parameters uniquely. Current approaches are not consistent, i.e., they provide different solutions when run multiple times on the same data. To address this limitation, we propose exploiting local diffuse reflectance (LDR) maxima, i.e., points in the scene where the normal vector is parallel to the illumination direction (see Fig. 1). We demonstrate several noteworthy properties of these maxima: a closed-form solution, computational efficiency and GBR consistency. An LDR maximum yields a simple closed-form solution corresponding to a semi-circle in the GBR parameters space (see Fig. 2); because as few as two diffuse maxima in different images identify a unique solution, the identification of the GBR parameters can be achieved very efficiently; finally, the algorithm is consistent as it always returns the same solution given the same data. Our algorithm is also remarkably robust: It can obtain an accurate estimate of the GBR parameters even with extremely high levels of outliers in the detected maxima (up to 80 % of the observations). The method is validated on real data and achieves state-of-the-art results.

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The surfaces of many objects in the Solar System comprise substantial quantities of water ice sometimes mixed with minerals and/or organic molecules. The sublimation of the ice changes the structural and optical properties of these objects. We present laboratory data on the evolution of the structure and the visible and near-infrared spectral reflectance of icy surface analogues of cometary ices, made of water ice, complex organic matter (tholins) and silicates, as they undergo sublimation under low temperature (<-70°C) and pressure (10-⁵mbar) conditions inside the SCITEAS simulation chamber. As the water ice sublimated, we observed in situ the formation of a porous sublimation lag deposit, or sublimation mantle, at the top of the ice. This mantle is a network of filaments made of the non-volatile particles. Organics or phyllosilicates grains, able to interact via stronger inter-particulate forces than olivine grains, can form a foam-like structure having internal cohesiveness, holding olivine grains together. As this mantle builds-up, the band depths of the sub-surface water ice are attenuated until complete extinction under only few millimeters of mantle. Optically thick sublimation mantles are mainly featureless in the near infrared. The absorption bands of the minerals present in the mantle are weak, or even totally absent if minerals are mixed with organics which largely dominate the VIS–NIR reflectance spectrum. During sublimation, ejections of large fragments of mantle, triggered by the gas flow, expose ice particles to the surface. The contrast of brightness between mantled and ice-exposed areas depends on the wavelength range and the dust/ice ratio considered. We describe how the chemical nature of the non-volatiles, the size of their particles, the way they are mixed with the ice and the dust/ice mass ratio influence the texture, activity and spectro-photometric properties of the sublimation mantles. These data provide useful references for interpreting remote-sensing observations of comets and also icy satellites or trans-neptunian objects.

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Permanently shadowed regions at the poles of the Moon and Mercury have been pointed out as candidates for hosting water ice at their surface. We have measured in the laboratory the visible and near infrared spectral range (VIS-NIR) bidirectional reflectance of intimate mixtures of water ice and the JSC-1AF lunar simulant for different ice concentrations, particle sizes, and measurement geometries. The nonlinearity between the measured reflectance and the amount of ice in the mixture can be reproduced to some extent by the mixing formulas of standard reflectance models, in particular, those of Hapke and Hiroi, which are tested here. Estimating ice concentrations from reflectance data without knowledge of the mixing coefficientsstrongly dependent on the size/shape of the grainscan result in large errors. According to our results, it is possible that considerable amounts of water ice might be intimately mixed in the regolith of the Moon and Mercury without producing noticeable photometric signatures.

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Nutrient leaching studies are expensive and require expertise in water collection and analyses. Less expensive or easier methods that estimate leaching losses would be desirable. The objective of this study was to determine if anion-exchange membranes (AEMs) and reflectance meters could predict nitrate (NO3-N) leaching losses from a cool-season lawn turf. A two-year field study used an established 90% Kentucky bluegrass (Poa pratensis L.)-10% creeping red fescue (Festuca rubra L.) turf that received 0 to 98 kg N ha-1 month-1, from May through November. Soil monolith lysimeters collected leachate that was analyzed for NO3-N concentration. Soil NO3-N was estimated with AEMs. Spectral reflectance measurements of the turf were obtained with chlorophyll and chroma meters. No significant (p > 0.05) increase in percolate flow-weighted NO3-N concentration (FWC) or mass loss occurred when AEM desorbed soil NO3-N was below 0.84 µg cm-2 d-1. A linear increase in FWC and mass loss (p < 0.0001) occurred, however, when AEM soil NO3-N was above this value. The maximum contaminant level (MCL) for drinking water (10 mg L-1 NO3-N) was reached with an AEM soil NO3-N value of 1.6 µg cm-2 d-1. Maximum meter readings were obtained when AEM soil NO3 N reached or exceeded 2.3 µg cm-2 d-1. As chlorophyll index and hue angle (greenness) increased, there was an increased probability of exceeding the NO3-N MCL. These data suggest that AEMs and reflectance meters can serve as tools to predict NO3-N leaching losses from cool-season lawn turf, and to provide objective guides for N fertilization.