Turkish Journal of Forestry (Dec 2022)
Estimating stem volume and measuring diameter and height of brutian pine trees from aerial photographs taken by unmanned aerial vehicle
Abstract
Remote sensing data and techniques are widely used in modern forestry studies. Today, aerial photographs taken with remote sensors on Unmanned Aerial Vehicles (UAV) can be processed by using softcopy photogrammetry to produce data such as point cloud and orthomosaic. Therefore, it is possible to make some remote measurements in forest ecosystems. It may be necessary to predict stem volumes of trees cut down in a forest area or felled for any reason in a practical way. In this study, it is aimed to predict the over-bark stem volumes by measuring the diameter and height of cut brutian pine trees (Pinus brutia Ten.) in orthomosaic and point cloud data produced from UAV photographs. The study was carried out in 2 different brutian pine stands located within the borders of Çandır Forestry Chief of Sütçüler Forestry Directorate in Isparta Regional Directorate of Forestry. In these areas, the diameter at breast height (d1.3) and total height of 175 cut brutian pine trees were measured on the point cloud and orthomosaics, tree volume predictions were made from these values obtained by various methods and the results were compared with the references data based on field measurements. In the study, the diameter and height measurement results calculated depending on the ground sampling distance of the aerial photographs were also compared. According to the findings, the lowest correlation value of 0.78 and the highest 0.92 for diameter measurements, the lowest 0.96 and highest 0.99 correlation values in height measurements, the lowest 0.70 and the highest 0.93 correlation values in stem volume predictions were obtained between UAV photogrammetry and reference data. As a result, it has been understood that UAVs, which are preferred as a practical remote sensing tool today, can be used to measure the diameter and height of pine trees lying on the ground and stem volumes can be successfully predicted by UAV photogrammetry.
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