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Accurate estimation of vegetation biophysical variables such as the vegetation canopy height (H) is of great importance to the applications of the land surface models. It is difficult to obtain the data of H at the regional scale or larger scale, but the remote sensing provides the most useful and most effective method. The leaf area index (LAI) is closely related to the H, and we analyzed its relationship with the correlation analysis based on the dataset at 86 site-years of field measurements from sites worldwide in this study. The result indicates that there is significant positive exponent correlation between these two parameters and the change of LAI would exert great impacts on H. The higher the LAI is, the higher the H is, and vice versa. Besides, the coefficients of different land cover types are very heterogeneous, and LAI of the needleleaf forest shows strong correlation with H, while that of the cropland shows weak correlation with H. The results may provide certain reference information for the extraction of the data of H at the regional scale with the remote sensing data.