In view of the fact that most of the existing tree height estimation models are based on a single parameter and tree height, the R2 goodness of fit of the model is not high and the accuracy is relatively rough. In this paper, a multi-parameter combined tree height estimation method based on multiple linear model is proposed. In this method, the height of Metasequoia glyptostroboides is estimated by multiple linear model with different parameter combinations, which improves the accuracy of tree height estimation and solves the problem of low goodness of fit of tree height estimated by single parameter model. In addition，in this paper a multi-time series Metasequoia street tree dataset is introduced and tested it through this method. The experimental results show that the goodness of fit between tree height and actual tree height obtained by the combination of diameter at breast height and subbranch height in multi-parameter combination is 0.984. Compared to the single parameter models, the goodness of fit increases by 0.3 to 0.4. Based on the parameters of individual tree structures, the accuracy of tree height estimation improves by approximately 30% to 40%, and the estimated growth trend aligns with that of mature Metasequoia forests.