Deng Ruru

Research on remote sensing model for soil water content on rough surface

Roughness of soil surface not only performs a remarkable influence to the BRDF of ground, and it is variable as well. So it’s one of important factors that affect the precision of remote sensing for soil water content. In this paper, it is demonstrated that the relationship between soil reflected spectrum and the soil water content is about obey the Beer Law, and then the absorption coefficient curve of moisture in soil was measured. The conclusion also be reached that the essential cause of soil surface roughness effects the soil reflectance is the slant of sub slopes on clod surface which result in the increasing of the rate of multi-reflecting light. Through analyzing the physical process of soil surface reflecting under the inference of soil water, a geometrical BRDF model for soil water remote sensing on rough surface is put forward in this paper. The result of test data showed that the model has a satisfied precision.

The coupled model of atmosphere and ground for air pollution remote sensing and its application on Guangdong Province, China

The scattering and absorption of synthetic aerosol are the main represents of air pollution in remote sensing data. Synthetic aerosol is a referent of air pollution. In this paper, a Coupled Model of Atmosphere and Ground spectrum for Air Pollution Remote Sensing is put forward. In the model, ground reflected spectrum is generalized as the composition of some basic components, and then reflectance model of every pixel is built with the variables are the ratios of ground surface basic components and the turbidity of synthetic aerosol. Using the model, turbidity of synthetic aerosol in the atmosphere on every pixel of satellite image can be calculated with multi-spectral data. The model was applied in Guangdong Province of China and it is found that air pollution in the region is increasing quickly.