Researchers developed a model to predict the height of Pinus massoniana trees in a forest in Fujian province. They used tree diameter and forest stand factors to create the model, which was tested for accuracy. By adding variables like tree height and stand basal area, they improved the model's accuracy. The final model showed reduced bias and error, and a higher coefficient of determination, making it better at predicting tree height based on diameter.