[Effects of multi-angle hyperspectral polarized reflection by forest soil].

In the present study, the authors measured samples of typical forest soils in different states with multi-angle hyperspectral polarized reflections. The authors analyzed multi-angle hyperspectral polarized reflections of soil data with various viewing zenith angles, incidence angles, relative azimuth angles, polarized states, soil water content and soil granule. The authors found that those factors affected the reflectance values of forest soils but not the spectral feature. The conclusions included that the larger the incidence angles and viewing zenith angles are, the bigger the polarized reflectance values of the surface of the forest soil. When the forest soil was dry, the surface had phenomenon of diffuse reflection and the polarized light reflection did not take place. When the soil moisture content reached a certain level, the polarized reflection appeared. The more the moisture content of the forest soil was, the smaller the polarized reflectance of the surface. The bigger the soil granule was and the rougher the soil surface was, the smaller the surface polarized reflectance. The results and conclusions suggested that the spectral characteristics of the ground target need to be considered adequately in order to design the best mode for sensor systems by remote sensing technology. The authors suggest that the incidence angle and viewing zenith angle be selected on the basis of factual instance. The authors suggest using larger viewing zenith angles and that the incidence angle should be equal to the viewing zenith angle. In the meantime, the effects of sheltering by ground targets need to be considered and the proper state of polarization should be chosen while keeping relative zenith angle at 180 degrees. This study not only helps find a new way for detection of soil characters, but also provides a theoretical basis for further research on multi-angle hyperspectral polarized reflection for detecting characteristic spectrum and best states in measuring forest soil.

[Study on the main influencing factors of mixed-pixel spectral characteristics].

Hyperspectral remote sensing can improve the identification and classification of surface features through the spectrum comparing and matching to achieve classification and recognition. Because of the spatial resolution of the sensor as well as the difference in complexity and diversity on the ground, mixed pixels in the image are prevalent in remote sensing. The problem of subpixel unmixing is a prominent issue in the quantitative application of remote sensing. How to effectively interpret the mixed-pixel is one of the key issues in the application of remote sensing. In the present paper, the hyperspectral reflectance characteristics of the mixed-pixels formed with two kinds of materials whose area ratios have always been 1 : 1 were studied at different incident zenith angles and different topology location distribution, which provides a theoretical basis for the mixed pixel classification accuracy improvement.