Abstract: To compare the effects of two atmospheric correction models on the relationships between vegetation indices (VIs) and forest leaf area index (LAI), the atmospheric correction reflectance images on the basis of DN image were obtained by using 6S and Gilabert models. The simple ratio (SR), normalizes difference vegetation index (NDVI), modified normalizes difference vegetation index (MNDVI), atmospheric resistant vegetation index (ARVI) and reduced simple ratio (RSR) of the broadleaved forests and mixed broad-leaved and coniferous forests in Baohe basin were estimated, and the relationships between the VIs and the ground-based measurements of LAI were calculated. The results showed that compared with DN image, the two models significantly increased the correlation coefficients between LAI and VIs except SR and NDVI. Different atmospheric correction models had significant effects on the estimation of forest leaf area. It was suggested that more attention should be paid to choose appropriate atmospheric correction models and VIs when remote sensing data were applied to quantitative analyzing and information collecting in field.

Key words: Elevated CO₂ concentration, Physiological and biochemical response, Pine broadleaf forest, Changbai Mountain