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D Tanre - One of the best experts on this subject based on the ideXlab platform.
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atmospheric correction of visible to middle infrared eos modis data over land Surfaces background operational algorithm and validation
Journal of Geophysical Research, 1997Co-Authors: Eric F Vermote, El N Saleous, C O Justice, Yoram J Kaufman, J L Privette, Lorraine A Remer, Jeanclaude Roger, D TanreAbstract:The NASA moderate resolution imaging spectroradiometer (MODIS) instrument will provide a global and improved source of information for the study of land Surfaces with a spatial resolution of up to 250 m. Prior to the derivation of various biophysical parameters based on Surface reflectances, the top of the atmosphere signals need to be radiometrically calibrated and corrected for atmospheric effects. The present paper describes in detail the state of the art techniques that will be used for atmospheric correction of MODIS bands 1 through 7, centered at 648, 858, 470, 555, 1240, 1640, and 2130 nm, respectively. Previous operational correction schemes have assumed a standard atmosphere with zero or constant aerosol loading and a uniform, Lambertian Surface. The MODIS operational atmospheric correction algorithm, reported here, uses aerosol and water vapor information derived from the MODIS data, corrects for adjacency effects and takes into account the directional properties of the observed Surface. This paper also describes the operational implementation of these techniques and its optimization. The techniques are applied to remote sensing data from the Landsat Thematic Mapper (TM), the NOAA advanced very high resolution radiometer (AVHRR), and the MODIS airborne simulator (MAS) and validated against ground-based measurements from the Aerosol Robotic Network (AERONET).
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second simulation of the satellite signal in the solar spectrum 6s an overview
IEEE Transactions on Geoscience and Remote Sensing, 1997Co-Authors: Eric F Vermote, D Tanre, M Herman, J L Deuze, J J MorcetteAbstract:Remote sensing from satellite or airborne platforms of land or sea Surfaces in the visible and near infrared is strongly affected by the presence of the atmosphere along the path from Sun to target (Surface) to sensor. This paper presents 6S (Second Simulation of the Satellite Signal in the Solar Spectrum), a computer code which can accurately simulate the above problems. The 6S code is an improved version of 5S (Simulation of the Satellite Signal in the Solar Spectrum), developed by the Laboratoire d'Optique Atmospherique ten years ago. The new version now permits calculations of near-nadir (down-looking) aircraft observations, accounting for target elevation, non Lambertian Surface conditions, and new absorbing species (CH/sub 4/, N/sub 2/O, CO). The computational accuracy for Rayleigh and aerosol scattering effects has been improved by the use of state-of-the-art approximations and implementation of the successive order of scattering (SOS) algorithm. The step size (resolution) used for spectral integration has been improved to 2.5 nm. The goal of this paper is not to provide a complete description of the methods used as that information is detailed in the 6S manual, but rather to illustrate the impact of the improvements between 5S and 6S by examining some typical remote sensing situations. Nevertheless, the 6S code has still limitations. It cannot handle spherical atmosphere and as a result, it cannot be used for limb observations. In addition, the decoupling the authors are using for absorption and scattering effects does not allow to use the code in presence of strong absorption bands.
Jochen Landgraf - One of the best experts on this subject based on the ideXlab platform.
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insights into tikhonov regularization application to trace gas column retrieval and the efficient calculation of total column averaging kernels
Atmospheric Measurement Techniques, 2014Co-Authors: Tobias Borsdorff, O P Hasekamp, A Wassmann, Jochen LandgrafAbstract:Abstract. Insights are given into Tikhonov regularization and its application to the retrieval of vertical column densities of atmospheric trace gases from remote sensing measurements. The study builds upon the equivalence of the least-squares profile-scaling approach and Tikhonov regularization method of the first kind with an infinite regularization strength. Here, the vertical profile is expressed relative to a reference profile. On the basis of this, we propose a new algorithm as an extension of the least-squares profile scaling which permits the calculation of total column averaging kernels on arbitrary vertical grids using an analytic expression. Moreover, we discuss the effective null space of the retrieval, which comprises those parts of a vertical trace gas distribution which cannot be inferred from the measurements. Numerically the algorithm can be implemented in a robust and efficient manner. In particular for operational data processing with challenging demands on processing time, the proposed inversion method in combination with highly efficient forward models is an asset. For demonstration purposes, we apply the algorithm to CO column retrieval from simulated measurements in the 2.3 μm spectral region and to O3 column retrieval from the UV. These represent ideal measurements of a series of spaceborne spectrometers such as SCIAMACHY, TROPOMI, GOME, and GOME-2. For both spectral ranges, we consider clear-sky and cloudy scenes where clouds are modelled as an elevated Lambertian Surface. Here, the smoothing error for the clear-sky and cloudy atmosphere is significant and reaches several percent, depending on the reference profile which is used for scaling. This underlines the importance of the column averaging kernel for a proper interpretation of retrieved column densities. Furthermore, we show that the smoothing due to regularization can be underestimated by calculating the column averaging kernel on a too coarse vertical grid. For both retrievals, this effect becomes negligible for a vertical grid with 20–40 equally thick layers between 0 and 50 km.
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a linearized radiative transfer model for ozone profile retrieval using the analytical forward adjoint perturbation theory approach
Journal of Geophysical Research, 2001Co-Authors: Jochen Landgraf, Otto Hasekamp, Michael A Box, Thomas TrautmannAbstract:For the retrieval of ozone profiles from space-borne radiance measurements, a new linearized radiative transfer model LIRA is presented. The model enables an effective linearization of the reflectance at the top of the atmosphere with respect to both the ozone density in the different layers of the model atmosphere and the Lambertian Surface albedo in the UV of the solar spectrum. The linearization of the model is based on the forward-adjoint perturbation theory, where the forward and adjoint solution of the scalar radiative transfer equation in its plane-parallel form are achieved by employing the Gauss-Seidel iteration technique. For clear sky and aerosol-loaded atmospheres the model provides the reflectance as well as its derivatives with respect to ozone density with an accuracy of better than 0.02%. The derivatives with respect to Surface reflection can be calculated with an error of less than 0.05%. The suitability of the model for ozone profile retrieval is demonstrated. Therefore ozone profiles are retrieved from 156 modeled radiance measurements, simulating real radiance measurements of the Global Ozone Monitoring Experiment (GOME) spectrometer in the UV. The comparison of the retrieved profiles using the proposed model LIRA with a reference retrieval shows small deviations in the stratosphere and upper troposphere of less than 1% and tolerable differences in the middle and lower troposphere of up to 10% in the mean profile at ground level.
Eric F Vermote - One of the best experts on this subject based on the ideXlab platform.
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atmospheric correction of visible to middle infrared eos modis data over land Surfaces background operational algorithm and validation
Journal of Geophysical Research, 1997Co-Authors: Eric F Vermote, El N Saleous, C O Justice, Yoram J Kaufman, J L Privette, Lorraine A Remer, Jeanclaude Roger, D TanreAbstract:The NASA moderate resolution imaging spectroradiometer (MODIS) instrument will provide a global and improved source of information for the study of land Surfaces with a spatial resolution of up to 250 m. Prior to the derivation of various biophysical parameters based on Surface reflectances, the top of the atmosphere signals need to be radiometrically calibrated and corrected for atmospheric effects. The present paper describes in detail the state of the art techniques that will be used for atmospheric correction of MODIS bands 1 through 7, centered at 648, 858, 470, 555, 1240, 1640, and 2130 nm, respectively. Previous operational correction schemes have assumed a standard atmosphere with zero or constant aerosol loading and a uniform, Lambertian Surface. The MODIS operational atmospheric correction algorithm, reported here, uses aerosol and water vapor information derived from the MODIS data, corrects for adjacency effects and takes into account the directional properties of the observed Surface. This paper also describes the operational implementation of these techniques and its optimization. The techniques are applied to remote sensing data from the Landsat Thematic Mapper (TM), the NOAA advanced very high resolution radiometer (AVHRR), and the MODIS airborne simulator (MAS) and validated against ground-based measurements from the Aerosol Robotic Network (AERONET).
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second simulation of the satellite signal in the solar spectrum 6s an overview
IEEE Transactions on Geoscience and Remote Sensing, 1997Co-Authors: Eric F Vermote, D Tanre, M Herman, J L Deuze, J J MorcetteAbstract:Remote sensing from satellite or airborne platforms of land or sea Surfaces in the visible and near infrared is strongly affected by the presence of the atmosphere along the path from Sun to target (Surface) to sensor. This paper presents 6S (Second Simulation of the Satellite Signal in the Solar Spectrum), a computer code which can accurately simulate the above problems. The 6S code is an improved version of 5S (Simulation of the Satellite Signal in the Solar Spectrum), developed by the Laboratoire d'Optique Atmospherique ten years ago. The new version now permits calculations of near-nadir (down-looking) aircraft observations, accounting for target elevation, non Lambertian Surface conditions, and new absorbing species (CH/sub 4/, N/sub 2/O, CO). The computational accuracy for Rayleigh and aerosol scattering effects has been improved by the use of state-of-the-art approximations and implementation of the successive order of scattering (SOS) algorithm. The step size (resolution) used for spectral integration has been improved to 2.5 nm. The goal of this paper is not to provide a complete description of the methods used as that information is detailed in the 6S manual, but rather to illustrate the impact of the improvements between 5S and 6S by examining some typical remote sensing situations. Nevertheless, the 6S code has still limitations. It cannot handle spherical atmosphere and as a result, it cannot be used for limb observations. In addition, the decoupling the authors are using for absorption and scattering effects does not allow to use the code in presence of strong absorption bands.
Thomas Trautmann - One of the best experts on this subject based on the ideXlab platform.
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a linearized radiative transfer model for ozone profile retrieval using the analytical forward adjoint perturbation theory approach
Journal of Geophysical Research, 2001Co-Authors: Jochen Landgraf, Otto Hasekamp, Michael A Box, Thomas TrautmannAbstract:For the retrieval of ozone profiles from space-borne radiance measurements, a new linearized radiative transfer model LIRA is presented. The model enables an effective linearization of the reflectance at the top of the atmosphere with respect to both the ozone density in the different layers of the model atmosphere and the Lambertian Surface albedo in the UV of the solar spectrum. The linearization of the model is based on the forward-adjoint perturbation theory, where the forward and adjoint solution of the scalar radiative transfer equation in its plane-parallel form are achieved by employing the Gauss-Seidel iteration technique. For clear sky and aerosol-loaded atmospheres the model provides the reflectance as well as its derivatives with respect to ozone density with an accuracy of better than 0.02%. The derivatives with respect to Surface reflection can be calculated with an error of less than 0.05%. The suitability of the model for ozone profile retrieval is demonstrated. Therefore ozone profiles are retrieved from 156 modeled radiance measurements, simulating real radiance measurements of the Global Ozone Monitoring Experiment (GOME) spectrometer in the UV. The comparison of the retrieved profiles using the proposed model LIRA with a reference retrieval shows small deviations in the stratosphere and upper troposphere of less than 1% and tolerable differences in the middle and lower troposphere of up to 10% in the mean profile at ground level.
Chandra Kambhamettu - One of the best experts on this subject based on the ideXlab platform.
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estimation of illuminant direction and intensity of multiple light sources
European Conference on Computer Vision, 2002Co-Authors: Wei Zhou, Chandra KambhamettuAbstract:This paper presents a novel scheme for locating multiple light sources and estimating their intensities from a pair of stereo images of a sphere. No prior knowledge of the location and radius of the sphere is necessary. The sphere Surface is not assumed to be a pure Lambertian Surface, instead, it has both Lambertian and specular properties. The light source locating algorithm is based on the fact that the Lambertian intensity is not dependent on the direction of viewp oint, while the specular intensity is highly dependent on the direction of the view point. From this fact, we can use a pair of stereo images whose view point changes can be utilized to separate the image of the sphere into two images, one with Lambertian intensities, and the other with specular intensities. The specular image is used to find the directions of the light sources, and then Lambertian image model is used to find the intensities of the light sources. Experiments on both synthetic and real images show that the scheme is successful and robust in finding the directions of the light sources accurately with accurate intensity estimation.
