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A modified vegetation backscattering model for leaf area index retrieval from SAR time series

Tao, Liangliang, Li, Jing, Jiang, Jinbao, Chen, Xi, Cai, Qingkong
International journal of remote sensing 2016 v.37 no.24 pp. 5884-5901
algorithms, leaf area index, models, remote sensing, soil, time series analysis, vegetation, water content, China
In this study, a semi-empirical modified vegetation backscattering model was developed to retrieve leaf area index (LAI) based on multi-temporal Radarsat-2 data and ground observations collected in China. This model combined the contribution of the vegetation and bare soil at the pixel level by adding vegetation coverage and the influence of bare soil on the total backscatter coefficients. Then, a lookup table algorithm was applied to calculate the value of vegetation water content and retrieve the LAI based on the linear relationship between the vegetation water content and LAI. The results indicated that the modified model was effective in evaluating and reproducing the total backscatter coefficients. Meanwhile, the LAI retrieval was well conducted with coefficient of determination (R ²) and root mean square error (RMSE) of 89% and 0.19 m ² m ⁻², respectively. Additionally, this method offers insight into the required application accuracy of LAI retrieval in the agricultural regions.