945 resultados para mid-infrared sensors


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A year of satellite-borne lidar CALIOP data is analyzed and statistics on occurrence and distribution of bulk properties of cirri are provided. The relationship between environmental and cloud physical parameters and the shape of the backscatter profile (BSP) is investigated. It is found that CALIOP BSP is mainly affected by cloud geometrical thickness while only minor impacts can be attributed to other quantities such as optical depth or temperature. To fit mean BSPs as functions of geometrical thickness and position within the cloud layer, polynomial functions are provided. It is demonstrated that, under realistic hypotheses, the mean BSP is linearly proportional to the IWC profile. The IWC parameterization is included into the RT-RET retrieval algorithm, that is exploited to analyze infrared radiance measurements in presence of cirrus clouds during the ECOWAR field campaign. Retrieved microphysical and optical properties of the observed cloud are used as input parameters in a forward RT simulation run over the 100-1100 cm-1 spectral interval and compared with interferometric data to test the ability of the current single scattering properties database of ice crystal to reproduce realistic optical features. Finally a global scale investigation of cirrus clouds is performed by developing a collocation algorithm that exploits satellite data from multiple sensors (AIRS, CALIOP, MODIS). The resulting data set is utilized to test a new infrared hyperspectral retrieval algorithm. Retrieval products are compared to data and in particular the cloud top height (CTH) product is considered for this purpose. A better agreement of the retrieval with the CALIOP CTH than MODIS is found, even if some cases of underestimation and overestimation are observed.

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Biosensors find wide application in clinical diagnostics, bioprocess control and environmental monitoring. They should not only show high specificity and reproducibility but also a high sensitivity and stability of the signal. Therefore, I introduce a novel sensor technology based on plasmonic nanoparticles which overcomes both of these limitations. Plasmonic nanoparticles exhibit strong absorption and scattering in the visible and near-infrared spectral range. The plasmon resonance, the collective coherent oscillation mode of the conduction band electrons against the positively charged ionic lattice, is sensitive to the local environment of the particle. I monitor these changes in the resonance wavelength by a new dark-field spectroscopy technique. Due to a strong light source and a highly sensitive detector a temporal resolution in the microsecond regime is possible in combination with a high spectral stability. This opens a window to investigate dynamics on the molecular level and to gain knowledge about fundamental biological processes.rnFirst, I investigate adsorption at the non-equilibrium as well as at the equilibrium state. I show the temporal evolution of single adsorption events of fibrinogen on the surface of the sensor on a millisecond timescale. Fibrinogen is a blood plasma protein with a unique shape that plays a central role in blood coagulation and is always involved in cell-biomaterial interactions. Further, I monitor equilibrium coverage fluctuations of sodium dodecyl sulfate and demonstrate a new approach to quantify the characteristic rate constants which is independent of mass transfer interference and long term drifts of the measured signal. This method has been investigated theoretically by Monte-Carlo simulations but so far there has been no sensor technology with a sufficient signal-to-noise ratio.rnSecond, I apply plasmonic nanoparticles as sensors for the determination of diffusion coefficients. Thereby, the sensing volume of a single, immobilized nanorod is used as detection volume. When a diffusing particle enters the detection volume a shift in the resonance wavelength is introduced. As no labeling of the analyte is necessary the hydrodynamic radius and thus the diffusion properties are not altered and can be studied in their natural form. In comparison to the conventional Fluorescence Correlation Spectroscopy technique a volume reduction by a factor of 5000-10000 is reached.

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The subject of this study is to investigate the capability of spaceborne remote sensing data to predict ground concentrations of PM10 over the European Alpine region using satellite derived Aerosol Optical Depth (AOD) from the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and the polar-orbiting MODerate resolution Imaging Spectroradiometer (MODIS). The spatial and temporal resolutions of these aerosol products (10 km and 2 measurements per day for MODIS, ∼ 25 km and observation intervals of 15 min for SEVIRI) permit an evaluation of PM estimation from space at different spatial and temporal scales. Different empirical linear relationships between coincident AOD and PM10 observations are evaluated at 13 ground-based PM measurement sites, with the assumption that aerosols are vertically homogeneously distributed below the planetary Boundary Layer Height (BLH). The BLH and Relative Humidity (RH) variability are assessed, as well as their impact on the parameterization. The BLH has a strong influence on the correlation of daily and hourly time series, whilst RH effects are less clear and smaller in magnitude. Despite its lower spatial resolution and AOD accuracy, SEVIRI shows higher correlations than MODIS (rSEV∼ 0.7, rMOD∼ 0.6) with regard to daily averaged PM10. Advantages from MODIS arise only at hourly time scales in mountainous locations but lower correlations were found for both sensors at this time scale (r∼ 0.45). Moreover, the fraction of days in 2008 with at least one satellite observation was 27% for SEVIRI and 17% for MODIS. These results suggest that the frequency of observations plays an important role in PM monitoring, while higher spatial resolution does not generally improve the PM estimation. Ground-based Sun Photometer (SP) measurements are used to validate the satellite-based AOD in the study region and to discuss the impact of aerosols' micro-physical properties in the empirical models. A lower error limit of 30 to 60% in the PM10 assessment from space is estimated in the study area as a result of AOD uncertainties, variability of aerosols properties and the heterogeneity of ground measurement sites. It is concluded that SEVIRI has a similar capacity to map PM as sensors on board polar-orbiting platforms, with the advantage of a higher number of observations. However, the accuracy represents a serious limitation to the applicability of satellites for ground PM mapping, especially in mountainous areas.

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We have measured high-precision infrared parallaxes with the Canada-France-Hawaii Telescope for a large sample of candidate young (approximate to 10-100 Myr) and intermediate-age (approximate to 100-600 Myr) ultracool dwarfs, with spectral types ranging from M8 to T2.5. These objects are compelling benchmarks for substellar evolution and ultracool atmospheres at lower surface gravities (i.e., masses) than most of the field population. We find that the absolute magnitudes of our young sample can be systematically offset from ordinary (older) field dwarfs, with the young late-M objects being brighter and the young/dusty mid-L (L3-L6.5) objects being fainter, especially at J band. Thus, we conclude the "underluminosity" of the young planetary-mass companions HR 8799b and 2MASS J1207-39b compared to field dwarfs is also manifested in young free-floating brown dwarfs, though the effect is not as extreme. At the same time, some young objects over the full spectral type range of our sample are similar to field objects, and thus a simple correspondence between youth and magnitude offset relative to the field population appears to be lacking. Comparing the kinematics of our sample to nearby stellar associations and moving groups, we identify several new moving group members, including the first free-floating L dwarf in the AB Dor moving group, 2MASS J0355+11. Altogether, the effects of surface gravity (age) and dust content on the magnitudes and colors of substellar objects appear to be degenerate. (C) 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

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Time-averaged discharge rates (TADR) were calculated for five lava flows at Pacaya Volcano (Guatemala), using an adapted version of a previously developed satellite-based model. Imagery acquired during periods of effusive activity between the years 2000 and 2010 were obtained from two sensors of differing temporal and spatial resolutions; the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Geostationary Operational Environmental Satellites (GOES) Imager. A total of 2873 MODIS and 2642 GOES images were searched manually for volcanic “hot spots”. It was found that MODIS imagery, with superior spatial resolution, produced better results than GOES imagery, so only MODIS data were used for quantitative analyses. Spectral radiances were transformed into TADR via two methods; first, by best-fitting some of the parameters (i.e. density, vesicularity, crystal content, temperature change) of the TADR estimation model to match flow volumes previously estimated from ground surveys and aerial photographs, and second by measuring those parameters from lava samples to make independent estimates. A relatively stable relationship was defined using the second method, which suggests the possibility of estimating lava discharge rates in near-real-time during future volcanic crises at Pacaya.

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The use of infrared thermography for the identification of lameness in cattle has increased in recent years largely because of its non-invasive properties, ease of automation and continued cost reductions. Thermography can be used to identify and determine thermal abnormalities in animals by characterizing an increase or decrease in the surface temperature of their skin. The variation in superficial thermal patterns resulting from changes in blood flow in particular can be used to detect inflammation or injury associated with conditions such as foot lesions. Thermography has been used not only as a diagnostic tool, but also to evaluate routine farm management. Since 2000, 14 peer reviewed papers which discuss the assessment of thermography to identify and manage lameness in cattle have been published. There was a large difference in thermography performance in these reported studies. However, thermography was demonstrated to have utility for the detection of contralateral temperature difference and maximum foot temperature on areas of interest. Also apparent in these publications was that a controlled environment is an important issue that should be considered before image scanning.

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At the mid-latitudes of Utopia Planitia (UP), Mars, a suite of spatially-associated landforms exhibit geomorphological traits that, on Earth, would be consistent with periglacial processes and the possible freeze-thaw cycling of water. The suite comprises small-sized polygonally-patterned ground, polygon-junction and -margin pits, and scalloped, rimless depressions. Typically, the landforms incise a dark-toned terrain that is thought to be ice-rich. Here, we investigate the dark-toned terrain by using high resolution images from the HiRISE as well as near-infrared spectral-data from the OMEGA and CRISM. The terrain displays erosional characteristics consistent with a sedimentary nature and near-infrared spectra characterised by a blue slope similar to that of weathered basaltic-tephra. We also describe volcanic terrain that is dark-toned and periglacially-modified in the Kamchatka mountain-range of eastern Russia. The terrain is characterised by weathered tephra inter-bedded with snow, ice-wedge polygons and near-surface excess ice. The excess ice forms in the pore space of the tephra as the result of snow-melt infiltration and, subsequently, in-situ freezing. Based on this possible analogue, we construct a three-stage mechanism that explains the possible ice-enrichment of a broad expanse of dark-toned terrain at the mid-latitudes of UP: (1) the dark-toned terrain accumulates and forms via the regional deposition of sediments sourced from explosive volcanism; (2) the volcanic sediments are blanketed by atmospherically-precipitated (H2O) snow, ice or an admixture of the two, either concurrent with the volcanic-events or between discrete events; and, (3) under the influence of high obliquity or explosive volcanism, boundary conditions tolerant of thaw evolve and this, in turn, permits the migration, cycling and eventual formation of excess ice in the volcanic sediments. Over time, and through episodic iterations of this scenario, excess ice forms to decametres of depth. (C) 2015 Elsevier B.V. All rights reserved.

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We present and examine a multi-sensor global compilation of mid-Holocene (MH) sea surface temperatures (SST), based on Mg/Ca and alkenone palaeothermometry and reconstructions obtained using planktonic foraminifera and organic-walled dinoflagellate cyst census counts. We assess the uncertainties originating from using different methodologies and evaluate the potential of MH SST reconstructions as a benchmark for climate-model simulations. The comparison between different analytical approaches (time frame, baseline climate) shows the choice of time window for the MH has a negligible effect on the reconstructed SST pattern, but the choice of baseline climate affects both the magnitude and spatial pattern of the reconstructed SSTs. Comparison of the SST reconstructions made using different sensors shows significant discrepancies at a regional scale, with uncertainties often exceeding the reconstructed SST anomaly. Apparent patterns in SST may largely be a reflection of the use of different sensors in different regions. Overall, the uncertainties associated with the SST reconstructions are generally larger than the MH anomalies. Thus, the SST data currently available cannot serve as a target for benchmarking model simulations.