Prediction of diameter distribution with MSN and SUR

This study used a non-parametric most similar neighbour (MSN) approach and a parametric seemingly unrelated regression (SUR) approach to model and to predict diameter distributions in conifer forests. Based on calculated differences between predicted and observed number of stems on a validation dataset, we found that SUR gave unbiased results and that MSN slightly underestimated total number of stems. However, both methods overpredicted the number of stems per hectare between 4 and 12 cm. If the predicted diameter distributions were converted into basal area per hectare, both methods gave unbiased results. We concluded that the even though both methods overall yielded accurate results, the MSN approach was more reliable in terms of predicting the number of large trees


Leave a Reply

Your email address will not be published. Required fields are marked *