Determining the Accuracy of Structural Parameters Measured from LiDAR Images in Lowland Oak Forests

Data on forests (e.g., height, diameter at breast height and volume) are increasingly being collected using remote sensing methods, leading to improved forest inventories. At present, a popular method for data collection is the use of unmanned aerial vehicles (UAVs) equipped with LiDAR sensors, which allow for a more detailed assessment of structural parameters in both space and time, facilitating the practical application of more complex forest management systems. Therefore, the main objective of this study was to measure the structural elements of stands (e.g., volume, basal area, tree count, height, diameter at breast height, crown width, and area) from LiDAR images and determine the accuracy of the obtained results. The research was conducted in a 5500 ha area containing some of the most valuable forests in Croatia, namely, lowland oak forests. The results of this study show that there are no statistically significant differences between the diameters and heights measured in the field and those from LiDAR images and, consequently, no difference in the calculated volume. This study also concluded that the use of unmanned aerial vehicles with various sensors can significantly reduce fieldwork while achieving the same accuracy in the results, thus leading to substantial savings in both time and money.