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

Data on forests (height, diameter at breast height, volume, etc.) are increasingly being collected using remote sensing methods, which improve forest inventories. The latest popular method of data collection is through unmanned aerial vehicles (UAVs) equipped with LiDAR sensors, which allow for a more detailed assessment of structural parameters in 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 the stand (volume, basal area, tree count, height, diameter at breast height, crown width and area, etc.) from LiDAR images and determine the accuracy of the results obtained. The research was conducted in the area of the most valuable forests in Croatia – the lowland oak forests, covering an area of 5500 ha. The results of the study showed that there is no statistically significant difference between the diameters and heights measured in the field and those from LiDAR images, and consequently, no difference in the calculated volume. The 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.