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This paper attempts to retrieve leaf water content (LWC) by developing new vegetation indices from the combination of the near-infrared (NIR) and middle-infrared (MIR) spectral reflectances. The expanded vegetation leaf model PROSPECT-VISIR and the widely validated four-stream scattering by arbitrarily inclined leaves (4SAIL) model are employed to simulate canopy reflectance in 0.4–5.7 μm region with...
This paper makes an attempt to establish a generalized neural network for simultaneously retrieving atmospheric profiles and surface temperature from hyperspectral thermal infrared data. To generate the simulated data covering the whole actual situations, the distributions of surface material, temperature and atmospheric profiles are elaborated carefully. The simulated at-sensor radiances are divided...
This paper makes an attempt to address the scaling problem of Leaf Area Index (LAI) and to analyze the propagation of scaling effect of LAI. On the basis of the Taylor series expansion and following the general scaling procedure, it is demonstrated that the magnitude of the scaling effect is the product of the degree of the non-linearity of the retrieval model and the spatial heterogeneity of input...
Land surface temperature, land surface emissivity and atmospheric profiles are all of great importance in many applications. As the at-sensor radiances are dependent on both the land surface parameters (temperature and emissivity) and atmospheric conditions, it is difficult to simultaneously retrieve these parameters with a high accuracy from multi-spectral radiances measured at satellite level. However,...
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