The linear polarization of light reflected from soil surfaces was measured by an instrument composed of a semi-automatic goniometer and an ASD spectroradiometer under a direct lamp to determine its potential to detect differences in different particle size. In this paper we tested and analyzed the polarization spectra of soils to determine the spectral response and changes in soil particle size, and to establish models of the relationship between spectral data and soil particle size. An orthogonal test was also designed for the various factors that affect soil spectral polarization characteristics and their interactions. All above measurements were carried out in the laboratory where the atmospheric contribution was ignored. The results show that particle size is one of the most important parameter affecting soil spectra, and is critical to soil remote sensing band selection and image interpretation. It also provides information required for soil investigation and analysis of physical and chemical properties.
Monitoring heavy metal stress on rice is of great significance for food security. In this paper, we used NDVI time series during the whole growing period of rice to identifying the rice growing differences under varied heavy metal stress. Here the NDVI time series were with high spatial-temporal resolution and obtained by blending MODIS and Landsat NDVI data. We extracted two kinds of features: Max NDVI value and time-integrated NDVI and use Fisher discrimination to explore the rice phonological differences under mild and severe stress levels. Results indicates that under severe stress the values of the metrics for presenting rice phonological differences in the experimental areas of heavy metal stress were smaller than the ones under mild stress. This means using the phenology differences can help to monitoring the heavy metal contamination.