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Leaf area and leaf biomass have an important influence on the exchange of energy, light interception, carbon cycling, plant growth, and forest productivity. This study showed development and comparison of models for predicting leaf area and leaf biomass of Lagerstroemia speciosa on the basis of diameter at breast height and tree height as predictors. Data on tree parameters were collected randomly from 312 healthy, well-formed tree species that were considered specifically for full tree crowns. Twenty-four different forms of linear and power models were compared in this study to select the best model. Two models (M10 and M22) for the estimation of leaf area and leaf biomass were selected based on , adjusted , root mean squared error, corrected akaike information criterion, Bayesian information criterion and Furnival’s index, and the three assumptions of linear regression. The models were validated with a test data set having the same range of DBH and tree height of the sampled data set on the basis of linear regression Morisita’s similarity index. So, the robustness of the models suggests their further application for leaf area and biomass estimation of L. speciosa in West Vanugach reserve forest of Bangladesh.

Modeling Develops to Estimate Leaf Area and Leaf Biomass of Lagerstroemia speciosa in West Vanugach Reserve Forest of Bangladesh