Retrieval of ice cloud properties using passive terahertz wave radiometer from space has gained increasing attention currently. A multi-channel regression inversion method for passive remote sensing of ice water path (IWP) in the terahertz band is presented. The characteristics of the upward terahertz radiation in the clear-sky and cloudy-sky are first analyzed using the Atmospheric Radiative Transfer Simulator (ARTS). Nine representative center frequencies with different offsets are selected to study the changes of terahertz radiation caused by microphysical parameters of ice clouds. Then, multiple linear regression method is applied to the inversion of IWP. Combinations of different channels are selected for regression to eliminate the influence of other factors (i.e., particle size and cloud height). The optimal fitting equation are obtained by the stepwise regression method using two oxygen absorption channels (118.75 ± 1.1 GHz, 118.75 ± 3.0 GHz), two water vapor absorption channels (183.31 ± 1.0 GHz, 183.31 ± 7.0 GHz), and two window channels (243.20 ± 2.5 GHz, 874.4 ± 6.0 GHz). Finally, the errors of the proposed inversion method are evaluated. The simulation results show that the absolute errors of this method for the low IWP cases are below 7 g/m2, and the relative errors for the high IWP cases are generally ranging from 10 to 30%, indicating that the multi-channel regression inversion method can achieve satisfactory accuracy.

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Crop and soil information products derived from data acquired by airborne and satellite sensors could provide valuable input for precision farming. The Canada Centre for Remote Sensing is actively pursuing the development of information products from both hyperspectral and polarimetric radar sensors. Preliminary results suggest that crop physical parameters including Leaf Area Index, canopy water content, chlorophyll and percent crop cover can be derived from hyperspectral imagery. Patterns related to soil and crop conditions are visible on radar imagery. Ground data collected coincident with hyperspectral and radar acquisitions are currently being used to validate these image products.

Heavy distortion of elements in finite element simulation of metal forming requires many times of remeshing during the computation. These remeshings should be performed automatically for both saving computation time and convenience. In this study, a fully automatic remeshing algorithm for two dimensional (2D) quadrilateral elements has been well established. A 2D rigid-plastic FEM code facilitated with the remeshing and refinement algorithm has been developed and applied to a two stage forging process. The system exhibited good performance during the simulation.

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