Study on estimation of Leaf area index (LAI) of paddy rice using ENVISAT ASAR data
Principal Investigator: Dr. Chen Jinsong
Most paddy rice in southern China grows in warm, humid and rainy areas where it is hard to acquire optical remote sensing data. The proposed research plans to take rice growing area in Zhu Jiang river delta as test site. Temporal ASAR data Backscatter behavior of Rice are researched to find better combination of ASAR data of different imaging parameters to map the acreage of rice growth. The ground measurements are also collected at the same time during the acquisition of ASAR data, including bio-physical parameters of rice. And then a semi-empirical backscattering model is designed to calculate leaf area index (LAI) of rice in the area using ASAR data so that the model can be used indirectly to estimate rice yield. The research outcome will provide a systemic method to estimate rice growth acreage and yield using ENVISAT ASAR data in cloudy and rainy area. Because rice is also the staple grain in southeastern Asia, the research result could be used in this area.