2 resultados para calibration transfer
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
Titan's optical and near-IR spectra result primarily from the scattering of sunlight by haze and its absorption by methane. With a column abundance of 92 km amagat (11 times that of Earth), Titan's atmosphere is optically thick and only similar to 10% of the incident solar radiation reaches the surface, compared to 57% on Earth. Such a formidable atmosphere obstructs investigations of the moon's lower troposphere and surface, which are highly sensitive to the radiative transfer treatment of methane absorption and haze scattering. The absorption and scattering characteristics of Titan's atmosphere have been constrained by the Huygens Probe Descent Imager/Spectral Radiometer (DISR) experiment for conditions at the probe landing site (Tomasko, M.G., Bezard, B., Doose, L., Engel, S., Karkoschka, E. 120084 Planet. Space Sci. 56, 624-247: Tomasko, M.G. et al. [2008b] Planet. Space Sci. 56, 669-707). Cassini's Visual and Infrared Mapping Spectrometer (VIMS) data indicate that the rest of the atmosphere (except for the polar regions) can be understood with small perturbations in the high haze structure determined at the landing site (Penteado, P.F., Griffith, CA., Tomasko, M.G., Engel, S., See, C., Doose, L, Baines, K.H., Brown, R.H., Buratti, B.J., Clark, R., Nicholson, P., Sotin, C. [2010]. Icarus 206, 352-365). However the in situ measurements were analyzed with a doubling and adding radiative transfer calculation that differs considerably from the discrete ordinates codes used to interpret remote data from Cassini and ground-based measurements. In addition, the calibration of the VIMS data with respect to the DISR data has not yet been tested. Here, VIMS data of the probe landing site are analyzed with the DISR radiative transfer method and the faster discrete ordinates radiative transfer calculation; both models are consistent (to within 0.3%) and reproduce the scattering and absorption characteristics derived from in situ measurements. Constraints on the atmospheric opacity at wavelengths outside those measured by DISR, that is from 1.6 to 5.0 mu m, are derived using clouds as diffuse reflectors in order to derive Titan's surface albedo to within a few percent error and cloud altitudes to within 5 km error. VIMS spectra of Titan at 2.6-3.2 mu m indicate not only spectral features due to CH4 and CH3D (Rannou, P., Cours, T., Le Mouelic, S., Rodriguez, S., Sotin, C., Drossart, P., Brown, R. [2010]. Icarus 208, 850-867), but also a fairly uniform absorption of unknown source, equivalent to the effects of a darkening of the haze to a single scattering albedo of 0.63 +/- 0.05. Titan's 4.8 mu m spectrum point to a haze optical depth of 0.2 at that wavelength. Cloud spectra at 2 mu m indicate that the far wings of the Voigt profile extend 460 cm(-1) from methane line centers. This paper releases the doubling and adding radiative transfer code developed by the DISR team, so that future studies of Titan's atmosphere and surface are consistent with the findings by the Huygens Probe. We derive the surface albedo at eight spectral regions of the 8 x 12 km(2) area surrounding the Huygens landing site. Within the 0.4-1.6 mu m spectral region our surface albedos match DISR measurements, indicating that DISR and VIMS measurements are consistently calibrated. These values together with albedos at longer 1.9-5.0 mu m wavelengths, not sampled by DISR, resemble a dark version of the spectrum of Ganymede's icy leading hemisphere. The eight surface albedos of the landing site are consistent with, but not deterministic of, exposed water ice with dark impurities. (C) 2011 Elsevier Inc. All rights reserved.
Resumo:
The leaf area index (LAI) is a key characteristic of forest ecosystems. Estimations of LAI from satellite images generally rely on spectral vegetation indices (SVIs) or radiative transfer model (RTM) inversions. We have developed a new and precise method suitable for practical application, consisting of building a species-specific SVI that is best-suited to both sensor and vegetation characteristics. Such an SVI requires calibration on a large number of representative vegetation conditions. We developed a two-step approach: (1) estimation of LAI on a subset of satellite data through RTM inversion; and (2) the calibration of a vegetation index on these estimated LAI. We applied this methodology to Eucalyptus plantations which have highly variable LAI in time and space. Previous results showed that an RTM inversion of Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared and red reflectance allowed good retrieval performance (R-2 = 0.80, RMSE = 0.41), but was computationally difficult. Here, the RTM results were used to calibrate a dedicated vegetation index (called "EucVI") which gave similar LAI retrieval results but in a simpler way. The R-2 of the regression between measured and EucVI-simulated LAI values on a validation dataset was 0.68, and the RMSE was 0.49. The additional use of stand age and day of year in the SVI equation slightly increased the performance of the index (R-2 = 0.77 and RMSE = 0.41). This simple index opens the way to an easily applicable retrieval of Eucalyptus LAI from MODIS data, which could be used in an operational way.