Evaluation of tree stump measurement methods for estimating diameter at breast height and tree height

The estimation of diameter at breast height (DBH) and tree height from stump dimensions plays a crucial role in assessing the economic and environmental impacts resulting from illegal logging or natural disasters. In this study, we assessed tree stump dimension measurements using a tape measure, nadir color photographs, and the UAV orthophoto. We explored challenges in stump measurement and evaluated the effectiveness of these measurement methods in predicting DBH and tree height from stump dimensions. The study was conducted on 93 stumps of European beech (Fagus sylvatica L.) in a 100-year-old forest with a planned timber harvest. In the first part of the study, we compared the smallest and largest diameter, circumference, and area of the stumps measured by the methods studied. The best correlation was found between the stump measurements on the UAV orthophoto and the nadir color photographs. The tape measurements were statistically significantly different from the measurements on the UAV orthophoto. Most of the outliers in the measurements were found in the pairs of UAV orthophoto and nadir photographs. An incorrect determination of the shape of the tree stump in the UAV orthophoto mainly caused the outliers. The visibility of the tree stumps in the orthophoto was affected by nearby vegetation, logging residues, and light conditions. In the second part of the study, we derived linear regression models for one, two, and three independent variables of DBH and measured tree stump sizes and linear regression models for tree height and measured stump sizes. The performance of the linear regression models for DBH was similar for all stump measurement methods examined. For the linear regression models for tree height, the best accuracy was obtained for models based on measurements on nadir photographs. Increasing the number of independent variables only slightly improved the accuracy of the linear regression models. We also tested whether using the average distance to the three nearest tree stumps measured on a UAV orthophoto could improve the accuracy of linear regression models. Including the average distance to the three nearest stumps did not improve the accuracy of the linear regression models for DBH but did help improve the accuracy of the distance-dependent linear regression models for tree height. The performance of the linear regression models for tree height for two and three independent variables was similar for all stump measurement methods examined. Given the accuracy of DBH and tree height estimates and the error distribution, top-down photography appears to be the most appropriate method for measuring stump size. Stump accessibility, forest regeneration, obstacles, time required for data collection, complexity of data processing, and expected accuracy of stump measurements must all be considered when selecting an appropriate method for stump surveying. The influence of the surveyor's skills on the field measurements and the orthophoto interpretation must also be considered.