- M. Reyniers (1)
- M.S. Salama (1)
- M.E. Schaepman (1)
- F.C. Seidel (1)
- F. Shen (1)
- F. Spada (1)
- P. Stammes (1)
- Z. Su (1)
- W. Verhoef (2)
- D.J.J. Walvoort (1)
- Q. Xiao (1)
- Y. Zhou (1)
Fast and simple model for atmospheric radiative transfer
Seidel, F.C. ; Kokhanovsky, A.A. ; Schaepman, M.E. - \ 2010
Atmospheric Measurement Techniques 3 (2010). - ISSN 1867-1381 - p. 1129 - 1141.
aerosol retrieval - transfer code - scattering - polarization - reflectance - quantities - intensity - radiance - light - 6s
Radiative transfer models (RTMs) are of utmost importance for quantitative remote sensing, especially for compensating atmospheric perturbation. A persistent trade-off exists between approaches that prefer accuracy at the cost of computational complexity, versus those favouring simplicity at the cost of reduced accuracy. We propose an approach in the latter category, using analytical equations, parameterizations and a correction factor to efficiently estimate the effect of molecular multiple scattering. We discuss the approximations together with an analysis of the resulting performance and accuracy. The proposed Simple Model for Atmospheric Radiative Transfer (SMART) decreases the calculation time by a factor of more than 25 in comparison to the benchmark RTM 6S on the same infrastructure. The relative difference between SMART and 6S is about 5% for spaceborne and about 10% for airborne computations of the atmospheric reflectance function. The combination of a large solar zenith angle (SZA) with high aerosol optical depth (AOD) at low wavelengths lead to relative differences of up to 15%. SMART can be used to simulate the hemispherical conical reflectance factor (HCRF) for spaceborne and airborne sensors, as well as for the retrieval of columnar AOD
Satellite estimates of wide-range suspended sediment concentrations in Changjiang (Yangtze) estuary using MERIS data
Shen, F. ; Verhoef, W. ; Zhou, Y. ; Salama, M.S. ; Liu, X. - \ 2010
Estuaries and coasts 33 (2010)6. - ISSN 1559-2723 - p. 1420 - 1429.
remote-sensing reflectance - coastal waters - matter - algorithm - seawifs - images - ocean - retrieval - dynamics - radiance
The Changjiang (Yangtze) estuarine and coastal waters are characterized by suspended sediments over a wide range of concentrations from 20 to 2,500 mg l-1. Suspended sediment plays important roles in the estuarine and coastal system and environment. Previous algorithms for satellite estimates of suspended sediment concentration (SSC) showed a great limitation in that only low to moderate concentrations (up to 50 mg l-1) could be reliably estimated. In this study, we developed a semi-empirical radiative transfer (SERT) model with physically based empirical coefficients to estimate SSC from MERIS data over turbid waters with a much wider range of SSC. The model was based on the Kubelka–Munk two-stream approximation of radiative transfer theory and calibrated using datasets from in situ measurements and outdoor controlled tank experiments. The results show that the sensitivity and saturation level of remote-sensing reflectance to SSC are dependent on wavelengths and SSC levels. Therefore, the SERT model, coupled with a multi-conditional algorithm scheme adapted to satellite retrieval of wide-range SSC, was proposed. Results suggest that this method is more effective and accurate in the estimation of SSC over turbid waters
Unified optical-thermal four-stream radiative transfer theory for homogeneous vegetation canopies
Verhoef, W. ; Xiao, Q. ; Jia, L. ; Su, Z. - \ 2007
IEEE Transactions on Geoscience and Remote Sensing 45 (2007)6. - ISSN 0196-2892 - p. 1808 - 1822.
gap probability model - bidirectional reflectance - nonisothermal surfaces - light-scattering - forest canopy - temperature - emissivity - radiance - soil
Foliage and soil temperatures are key variables for assessing the exchanges of turbulent heat fluxes between vegetated land and the atmosphere. Using multiple-view-angle thermal-infrared (TIR) observations, the temperatures of soil and vegetation may be retrieved. However, particularly for sparsely vegetated areas, the soil and vegetation component temperatures in the sun and in the shade may be very different depending on the solar radiation, the physical properties of the surface, and the meteorological conditions. This may interfere with a correct retrieval of component temperatures, but it might also yield extra information related to canopy structure. Both are strong reasons to investigate this phenomenon in some more detail. To this end, the relationship between the TIR radiance directionality and the component temperatures has been analyzed. In this paper, we extend the four-stream radiative transfer (RT) formalism of the Scattering by Arbitrarily Inclined Leaves model family to the TIR domain. This new approach enables us to simulate the multiple scattering and emission inside a geometrically homogenous but thermodynamically heterogeneous canopy for optical as well as thermal radiation using the same modeling framework. In this way top-of-canopy thermal radiances observed under multiple viewing angles can be related to the temperatures of sunlit and shaded soil and sunlit and shaded leaves. In this paper, we describe the development of this unified optical-thermal RT theory and demonstrate its capabilities. A preliminary validation using an experimental data set collected in the Shunyi remote sensing field campaign in China is briefly addressed
McSCIA: application of the equivalence theorem in a Monte Carlo radiative transfer model for spherical shell atmospheres
Spada, F. ; Krol, M.C. ; Stammes, P. - \ 2006
Atmospheric Chemistry and Physics 6 (2006)12. - ISSN 1680-7316 - p. 4823 - 4842.
molecular line absorption - ozone monitoring instrument - scattering atmosphere - part i - sciamachy - satellite - profiles - objectives - radiance - geometry
A new multiple-scatteringMonte Carlo 3-D radiative transfer model named McSCIA (Monte Carlo for SCIA-machy) is presented. The backward technique is used to efficiently simulate narrow field of view instruments. The McSCIA algorithm has been formulated as a function of the Earth's radius, and can thus perform simulations for both plane-parallel and spherical atmospheres. The latter geometry is essential for the interpretation of limb satellite measurements, as performed by SCIAMACHY on board of ESA's Envisat. The model can simulate UV-vis-NIR radiation. First the ray-tracing algorithm is presented in detail, and then successfully validated against literature references, both in plane-parallel and in spherical geometry. A simple 1-D model is used to explain two different ways of treating absorption. One method uses the single scattering albedo while the other uses the equivalence theorem. The equivalence theorem is based on a separation of absorption and scattering. It is shown that both methods give, in a statistical way, identical results for a wide variety of scenarios. Both absorption methods are included in McSCIA, and it is shown that also for a 3-D case both formulations give identical results. McSCIA limb profiles for atmospheres with and without absorption compare well with the one of the state of the art Monte Carlo radiative transfer model MCC++. A simplification of the photon statistics may lead to very fast calculations of absorption features in the atmosphere. However, these simplifications potentially introduce biases in the results. McSCIA does not use simplifications and is therefore a relatively slow implementation of the equivalence theorem.
A linear model to predict with a multi-spectral radiometer the amount of nitrogen in winter wheat
Reyniers, M. ; Walvoort, D.J.J. ; Baardemaaker, J. De - \ 2006
International Journal of Remote Sensing 27 (2006)19. - ISSN 0143-1161 - p. 4159 - 4179.
spectral reflectance - vegetation - indexes - leaves - water - corn - experience - radiance - biomass - canopy
The objective was to develop an optimal vegetation index (VIopt) to predict with a multi-spectral radiometer nitrogen in wheat crop (kg[N] ha-1). Optimality means that nitrogen in the crop can be measured accurately in the field during the growing season. It also means that the measurements are stable under changing light conditions and vibrations of the measurement platform. Different fields, on which various nitrogen application rates and seeding densities were applied in experimental plots, were measured optically during the growing season. These measurements were performed over three years. Optical measurements on eight dates were related to calibration measurements of nitrogen in the crop (kg[N] ha-1) as measured in the laboratory. By making combinations of the wavelength bands, and whether or not the soil factor was taken into account, numerous vegetation indices (VIs) were examined for their accuracy in predicting nitrogen in wheat. The effect of changing light conditions in the field and vibrations of the measurement platform on the VIs were determined based on tests in the field. VIopt ((1+L)*(R2NIR+1)/(Rred+L) with L=0.45), the optimal vegetation index found, was best in predicting nitrogen in grain crop. The root mean squared error (RMSE), determined by means of cross-validation, was 16.7 kg[N] ha-1. The RMSE was significantly lower compared to other frequently used VIs such as NDVI, RVI, DVI, and SAVI. The L-value can change between 0.16 and 1.6 without deteriorating the RMSE of prediction. Besides being the best predictor for nitrogen, VIopt had the advantage of being a stable vegetation index under circumstances of changing light conditions and platform vibrations. In addition, VIopt also had a simple structure of physically meaningful bands.