A semi-empirical backscattering model for estimation of leaf area index (LAI) of rice in southern China

Most paddy rice in southern China grows in warm, humid and rainy areas where it is hard to acquire optical remote sensing data. In this study, a semi-empirical backscattering model was proposed to estimate leaf area index (LAI) of rice in the area using ENVISAT Advanced Synthetic Aperture Radar (ASAR) alternating polarization data. Ground measurements of LAI, water content and height of rice in the test site were collected and the model fitted at the same time as the acquisition of ASAR data. LAI estimated from the model was compared with ground measurements to evaluate the accuracy of the model. The results showed that the model provides a promising alternative to optical remote sensing data for predicting LAI of rice in southern China.