Measuring the diameter and length of brutian pine tree from aerial photographs obtained by unmanned aerial vehicle
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Abstract (EN)
Aerial photographs taken with sensor systems on Unmanned Aerial Vehicles (UAVs) can be processed by using photogrammetric software to produce data such as point cloud and orthomosaic. Therefore, it is possible to perform some measurements related to forest ecosystems on the remotely sensed data. In terms of the sustainability of effective use of forest resources, the over-bark stem volumes of trees cut down or felled in a forest area should be predicted in a practical way. In this study, it is aimed to estimate the over-bark stem volumes by measuring the diameter and height of cut brutian pine trees (Pinus brutia Ten.) on orthomosaic and point cloud data produced from UAV photographs. The study was carried out in two different brutian pine stands located within the borders of Çandır Forestry Chief of Sütçüler Forestry Directorate in Isparta Regional Directorate of Forestry. The diameter at breast height (d1.3) and height of total 175 felled red pine trees were measured on the point cloud and orthomosaic data produced from UAV photographs of the study area. Volume predictions were made by various methods using these data measured and the results were compared with the field measurements. According to the findings, for diameter measurement the lowest correlation value 0.78, the highest 0.92, for height measurement the lowest correlation value 0.96 and the highest 0.99 and for volume predictions the lowest 0.70 and the highest 0.93 correlation values were found between UAV and field data. As a result, it has been revealed that the remote sensing data obtained from the UAVs, which are preferred as a practical remote sensing platform, can be used to measure the diameter and height of red pine trees lying on the ground and tree volumes can be successfully predicted by UAV photogrammetry.
Author
Hakan Durgun
How to Cite
Hakan Durgun (Master Thesis). Measuring the diameter and length of brutian pine tree from aerial photographs obtained by unmanned aerial vehicle, 2023, Isparta University of Applied Sciences.
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