Comparison of Forest Leaf Area Index Retrieval Based on Simple Ratio and Reduced Simple Ratio

Leaf Area Index (LAI) is an essential parameter for process-based ecological and climate models. Spectral vegetation indices calculated from remote sensing data are widely used for LAI retrieval at large scales. The applicability of two vegetation indices, namely Simple Ratio (SR) and Reduced Simple Ration (RSR), for retrieving LAI at Maoershan mountain in Heilongjiang province of China was investigated through analyzing the correlations of SR and RSR calculated from Landsat-5 TM data acquired on 24 June, 2009 with LAI measured at 23 typical plots with Li-Cor LAI-2000 during 12 to 20 July, 2009. The fitted model with SR as the predator captured 54.7% of variations of LAI among these 23 plots while the variations of LAI explained by the fitted model with RSR as the predictor increased to 75.4%, indicating the better performance of RSR over SR in retrieving forest LAI in the study area owing to the ability of RSR to reduce the influence of soil background reflectance through the incorporation of the reflectance of shortwave infrared wavelength into SR. LAI derived from models based on SR and RSR was well correlated (${\bf R}^{\bf 2}\!\! =\!\! {\bf 0.7219}$, N=180932). The mean of LAI estimated using the SR-based model was 0.37 larger than that estimated using the RSR-based model for the entire study area. LAI estimated using the former model was smaller than that estimated by the latter model when LAI estimated by the latter was larger than 5.6, indicating that RSR saturates slower than SR under the condition of high LAI. However, RSR is more sensitive to the influence of topography and shadows of clouds than SR.