Öz
İnsansız Hava Araçları (İHA) destekli uzaktan algılama verilerinin doğruluk düzeyindeki iyileşmelere paralel olarak ormancılık çalışmalarındaki kullanımı yaygınlaşmıştır. Son yıllarda İHA tabanlı üç boyutlu (3B) nokta bulutu verileri kullanılarak tek ağaç parametreleri hesaplanabilmektedir. Bu çalışmada, Bursa Teknik Üniversitesi (BTÜ) Mimar Sinan Kampüsü’ndeki fıstık çamı (Pinus pinea, L.) alanında, İHA verileri kullanılarak ağaç parametrelerinin (ağaç boyu ve tepe tacı genişliği) belirlenmesi amaçlanmıştır. Örnek sahadan alınan İHA görüntüleri üzerinde 3B nokta bulutu yöntemi kullanılarak ağaç boyu ve tepe tacı genişliği parametreleri elde edilmiştir. İHA tabanlı yöntemin başarısını değerlendirmek için klasik yersel ölçüm cihazları kullanılarak çalışma alanındaki ağaçların boy ve tepe tacı genişliği verileri elde edilmiştir. Çalışmada, yersel ölçümlerle ve İHA verileri ile belirlenen ağaç parametreleri arasındaki ilişkiler istatistiksel analizlerle incelenmiştir. Ayrıca, her iki yöntemle elde edilen ağaç parametreleri Ortalama Kare Hatası (Mean Squared Error-MSE) ve Kök Ortalama Kare Hatası (Root Mean Squared Error-RMSE) yöntemleri ile karşılaştırılarak İHA tabanlı yöntemin etkinliği değerlendirilmiştir. Ağaç boyu için hata değerleri, MSE ve RMSE, sırasıyla 0,057 ve 0,427 olarak belirlenmiştir. Tepe tacı genişliği için ise hata değerleri sırasıyla 0,239 ve 0,653 bulunmuştur. Ağaç boyu ve tepe tacı genişliği parametreleri kendi arasında karşılaştırıldığında ağaç boyunun daha yüksek doğrulukla belirlendiği görülmüştür.
Anahtar Kelimeler
Etik Beyan
Bu çalışma etik kurul izni veya herhangi bir özel izin gerektirmemektedir.
Destekleyen Kurum
Yazar(lar) bu çalışmanın araştırılması, yazarlığı veya yayınlanması için herhangi bir finansal destek almamıştır.
Kaynakça
- Akgul, M., Yurtseven, H., Gulci, S., & Akay, A. E. (2018). Evaluation of UAV-and GNSS-based DEMs for earthwork volume. Arabian Journal of Science and Engineering, 43(4), 1893–1909.
- Ciritcioğlu, M. G., & Buğday, E. (2022). Assessment of unmanned aerial vehicle use opportunities in forest road project (Düzce sample). Bartın Orman Fakültesi Dergisi, 24(2), 247–257.
- Dainelli, R., Toscano, P., Di Gennaro, S. F., & Matese, A. (2021). Recent advances in unmanned aerial vehicle forest remote sensing—A systematic review. Part I: A general framework. Forests, 12, 327.
- DJI. (2024, Nisan 5). Mavic 2 Pro specifications. https://www.dji.com/global/support/product/mavic-2 Ecke, S., Dempewolf, J., Frey, J., Schwaller, A., Endres, E., Klemmt, H.-J., Tiede, D., & Seifert, T. (2022). UAV-based forest health monitoring: A systematic review. Remote Sensing, 14(13), 3205.
- Eker, R., Aydın, A., & Hübl, J. (2018). Unmanned aerial vehicle (UAV)-based monitoring of a landslide: Gallenzerkogel landslide (Ybbs-Lower Austria) case study. Environmental Monitoring and Assessment, 190(1), 28.
- Elmeseiry, N., Alshaer, N., & Ismail, T. (2021). A detailed survey and future directions of unmanned aerial vehicles (UAVs) with potential applications. Aerospace, 8(12), 363.
- Giordan, D., Adams, M. S., Aicardi, I., Alicandro, M., Allasia, P., Baldo, M., De Berardinis, P., Dominici, D., Godone, D., Hobbs, P., Lechner, V., Niedzielski, T., Piras, M., Rotilio, M., Salvini, R., Segor, V., Sotier, B., & Troilo, F. (2020). The use of unmanned aerial vehicles (UAVs) for engineering geology applications. Bulletin of Engineering Geology and the Environment, 79, 3437–3481.
- Görnaz, G. (2025). İHA verileri kullanılarak meşcere parametrelerinin belirlenmesi [Yüksek lisans tezi], Bursa Teknik Üniversitesi Lisansüstü Eğitim Enstitüsü, Bursa.
- Gülci, S., Akay, A. E., Gülci, N., & Taş, İ. (2021). An assessment of conventional and drone-based measurements for tree attributes in timber volume estimation: A case study on stone pine plantation. Ecological Informatics, 63, 101303.
- Gülci, S. (2019). The determination of some stand parameters using SfM-based spatial 3D point cloud in forestry studies: an analysis of data production in pure coniferous young forest stands. Environmental Monitoring and Assessment, 191, 495. https://doi.org/10.1007/s10661-019-7628-4
- Gülci, S., Akay, A. E., Aricak, B., & Sariyildiz, T. (2022). Recent advances in UAV-based structure-from-motion photogrammetry for aboveground biomass and carbon storage estimations in forestry. In M. N. Suratman (Ed.), Concepts and applications of remote sensing in forestry (pp. 395–409). Springer Singapore.
- Hasegawa, H., Sujaswara, A. A., Kanemoto, T., & Tsubota, K. (2023). Possibilities of using UAV for estimating earthwork volumes during process of repairing a small-scale forest road, case study from Kyoto Prefecture, Japan. Forests, 14(4), 677.
- Kınalı, M., & Çalışkan, E. (2022). Use of unmanned aerial vehicles in forest road projects. Bartın Orman Fakültesi Dergisi, 24(3), 530–541.
- Lisein, J., Pierrot-Deseilligny, M., Bonnet, S., & Lejeune, P. (2013). A photogrammetric workflow for the creation of a forest canopy height model from small unmanned aerial system imagery. Forests, 4, 922–944.
- Mohsan, S. A. H., Khan, M. A., Noor, F., Ullah, I., & Alsharif, M. H. (2022). Towards the unmanned aerial vehicles (UAVs): a comprehensive review. Drones, 6(6), 147.
- Nasiri, V., Darvishsefat, A. A., Arefi, H., Pierrot-Deseilligny, M., Namiranian, M., & Le Bris, A. (2021). Unmanned aerial vehicles (UAV)-based canopy height modeling under leaf-on and leaf-off conditions for determining tree height and crown diameter (case study: hyrcanian mixed forest). Canadian Journal of Forest Research, 51(7), 962–971.
- Pajares, G. (2015). Overview and current status of remote sensing applications based on unmanned aerial vehicles (UAVs). Photogrammetric Engineering & Remote Sensing, 81(4), 281–329.
- Pix4D. (2024, Nisan 5). Pix4D capture – drone mapping software. https://pix4d.com
- Siafali, E., & Tsioras, P. A. (2024). An innovative approach to surface deformation estimation in forest road and trail networks using unmanned aerial vehicle real-time kinematic-derived data for monitoring and maintenance. Forests, 15(1), 212.
- Smith, M. W., Carrivick, J. L., & Quincey, D. J. (2015). Structure from motion photogrammetry in physical geography. Progress in Physical Geography, 40, 247–275.
- Tomaštík, J., Mokroš, M., Surový, P., Grznárová, A., & Merganič, J. (2019). UAV RTK/PPK method—an optimal solution for mapping inaccessible forested areas? Remote Sensing, 11, 721. https://doi.org/10.3390/rs11060721
- Türk, Y., & Canyurt, H. (2024). Capabilities of using UAVs to determine forest road excavation volumes in mountainous areas. Šumarski List, 148(3–4), 137–150.
- Vacca, G., & Vecchi, E. (2024). UAV photogrammetric surveys for tree height estimation. Drones, 8(3), 106. White, J. C., Coops, N. C., Wulder, M. A., Vastaranta, M., Hilker, T., & Tompalski, P. (2016). Remote sensing technologies for enhancing forest inventories: a review. Canadian Journal of Remote Sensing, 42(5), 619–641. https://doi.org/10.1080/07038992.2016.1207484
- Yurtseven, H., Akgul, M., Coban, S., & Gulci, S. (2019). Determination and accuracy analysis of individual tree crown parameters using UAV-based imagery and OBIA techniques. Measurement, 145, 651–664. https://doi.org/10.1016/j.measurement.2019.05.092
- Zhang, J., Hu, J., Lian, J., Fan, Z., Ouyang, X., & Ye, W. (2016). Seeing the forest from drones: testing the potential of lightweight drones as a tool for long-term forest monitoring. Biological Conservation, 198, 60–69. https://doi.org/10.1016/j.biocon.2016.03.027
Öz
Parallel to the improvements in the accuracy level of Unmanned Aerial Vehicle (UAV) supported remote sensing data, their use in forestry studies has become widespread. In recent years, stand parameters can be calculated using UAV-based three-dimensional (3D) point cloud data. In this study, it was aimed to determine tree parameters (tree height and crown width) using UAV data in the stone pine (Pinus pinea, L.) stand within the Bursa Technical University (BTU) Mimar Sinan Campus. Tree height and crown width parameters were obtained using the 3D point cloud method on UAV images taken from the study area. In order to evaluate the success of the UAV-based method, tree height and crown width data were obtained in the study area using classical ground measurement devices. In the study, the relationships between stand parameters determined by ground measurements and UAV data were examined by statistical analysis. In addition, the stand parameters obtained with both methods were compared with the Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) methods to evaluate the effectiveness of the UAV-based method. The error values for tree height, MSE and RMSE, were determined as 0.057 and 0.427, respectively. The error values for crown width were found as 0.239 and 0.653, respectively. When the tree height and crown width parameters were compared with each other, it was seen that tree height was determined with higher accuracy.
Anahtar Kelimeler
Kaynakça
- Akgul, M., Yurtseven, H., Gulci, S., & Akay, A. E. (2018). Evaluation of UAV-and GNSS-based DEMs for earthwork volume. Arabian Journal of Science and Engineering, 43(4), 1893–1909.
- Ciritcioğlu, M. G., & Buğday, E. (2022). Assessment of unmanned aerial vehicle use opportunities in forest road project (Düzce sample). Bartın Orman Fakültesi Dergisi, 24(2), 247–257.
- Dainelli, R., Toscano, P., Di Gennaro, S. F., & Matese, A. (2021). Recent advances in unmanned aerial vehicle forest remote sensing—A systematic review. Part I: A general framework. Forests, 12, 327.
- DJI. (2024, Nisan 5). Mavic 2 Pro specifications. https://www.dji.com/global/support/product/mavic-2 Ecke, S., Dempewolf, J., Frey, J., Schwaller, A., Endres, E., Klemmt, H.-J., Tiede, D., & Seifert, T. (2022). UAV-based forest health monitoring: A systematic review. Remote Sensing, 14(13), 3205.
- Eker, R., Aydın, A., & Hübl, J. (2018). Unmanned aerial vehicle (UAV)-based monitoring of a landslide: Gallenzerkogel landslide (Ybbs-Lower Austria) case study. Environmental Monitoring and Assessment, 190(1), 28.
- Elmeseiry, N., Alshaer, N., & Ismail, T. (2021). A detailed survey and future directions of unmanned aerial vehicles (UAVs) with potential applications. Aerospace, 8(12), 363.
- Giordan, D., Adams, M. S., Aicardi, I., Alicandro, M., Allasia, P., Baldo, M., De Berardinis, P., Dominici, D., Godone, D., Hobbs, P., Lechner, V., Niedzielski, T., Piras, M., Rotilio, M., Salvini, R., Segor, V., Sotier, B., & Troilo, F. (2020). The use of unmanned aerial vehicles (UAVs) for engineering geology applications. Bulletin of Engineering Geology and the Environment, 79, 3437–3481.
- Görnaz, G. (2025). İHA verileri kullanılarak meşcere parametrelerinin belirlenmesi [Yüksek lisans tezi], Bursa Teknik Üniversitesi Lisansüstü Eğitim Enstitüsü, Bursa.
- Gülci, S., Akay, A. E., Gülci, N., & Taş, İ. (2021). An assessment of conventional and drone-based measurements for tree attributes in timber volume estimation: A case study on stone pine plantation. Ecological Informatics, 63, 101303.
- Gülci, S. (2019). The determination of some stand parameters using SfM-based spatial 3D point cloud in forestry studies: an analysis of data production in pure coniferous young forest stands. Environmental Monitoring and Assessment, 191, 495. https://doi.org/10.1007/s10661-019-7628-4
- Gülci, S., Akay, A. E., Aricak, B., & Sariyildiz, T. (2022). Recent advances in UAV-based structure-from-motion photogrammetry for aboveground biomass and carbon storage estimations in forestry. In M. N. Suratman (Ed.), Concepts and applications of remote sensing in forestry (pp. 395–409). Springer Singapore.
- Hasegawa, H., Sujaswara, A. A., Kanemoto, T., & Tsubota, K. (2023). Possibilities of using UAV for estimating earthwork volumes during process of repairing a small-scale forest road, case study from Kyoto Prefecture, Japan. Forests, 14(4), 677.
- Kınalı, M., & Çalışkan, E. (2022). Use of unmanned aerial vehicles in forest road projects. Bartın Orman Fakültesi Dergisi, 24(3), 530–541.
- Lisein, J., Pierrot-Deseilligny, M., Bonnet, S., & Lejeune, P. (2013). A photogrammetric workflow for the creation of a forest canopy height model from small unmanned aerial system imagery. Forests, 4, 922–944.
- Mohsan, S. A. H., Khan, M. A., Noor, F., Ullah, I., & Alsharif, M. H. (2022). Towards the unmanned aerial vehicles (UAVs): a comprehensive review. Drones, 6(6), 147.
- Nasiri, V., Darvishsefat, A. A., Arefi, H., Pierrot-Deseilligny, M., Namiranian, M., & Le Bris, A. (2021). Unmanned aerial vehicles (UAV)-based canopy height modeling under leaf-on and leaf-off conditions for determining tree height and crown diameter (case study: hyrcanian mixed forest). Canadian Journal of Forest Research, 51(7), 962–971.
- Pajares, G. (2015). Overview and current status of remote sensing applications based on unmanned aerial vehicles (UAVs). Photogrammetric Engineering & Remote Sensing, 81(4), 281–329.
- Pix4D. (2024, Nisan 5). Pix4D capture – drone mapping software. https://pix4d.com
- Siafali, E., & Tsioras, P. A. (2024). An innovative approach to surface deformation estimation in forest road and trail networks using unmanned aerial vehicle real-time kinematic-derived data for monitoring and maintenance. Forests, 15(1), 212.
- Smith, M. W., Carrivick, J. L., & Quincey, D. J. (2015). Structure from motion photogrammetry in physical geography. Progress in Physical Geography, 40, 247–275.
- Tomaštík, J., Mokroš, M., Surový, P., Grznárová, A., & Merganič, J. (2019). UAV RTK/PPK method—an optimal solution for mapping inaccessible forested areas? Remote Sensing, 11, 721. https://doi.org/10.3390/rs11060721
- Türk, Y., & Canyurt, H. (2024). Capabilities of using UAVs to determine forest road excavation volumes in mountainous areas. Šumarski List, 148(3–4), 137–150.
- Vacca, G., & Vecchi, E. (2024). UAV photogrammetric surveys for tree height estimation. Drones, 8(3), 106. White, J. C., Coops, N. C., Wulder, M. A., Vastaranta, M., Hilker, T., & Tompalski, P. (2016). Remote sensing technologies for enhancing forest inventories: a review. Canadian Journal of Remote Sensing, 42(5), 619–641. https://doi.org/10.1080/07038992.2016.1207484
- Yurtseven, H., Akgul, M., Coban, S., & Gulci, S. (2019). Determination and accuracy analysis of individual tree crown parameters using UAV-based imagery and OBIA techniques. Measurement, 145, 651–664. https://doi.org/10.1016/j.measurement.2019.05.092
- Zhang, J., Hu, J., Lian, J., Fan, Z., Ouyang, X., & Ye, W. (2016). Seeing the forest from drones: testing the potential of lightweight drones as a tool for long-term forest monitoring. Biological Conservation, 198, 60–69. https://doi.org/10.1016/j.biocon.2016.03.027
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Konular | Ormancılık (Diğer) |
| Bölüm | Araştırma Makaleleri |
| Yazarlar | |
| Erken Görünüm Tarihi | 12 Haziran 2025 |
| Yayımlanma Tarihi | 26 Haziran 2025 |
| Gönderilme Tarihi | 23 Mart 2025 |
| Kabul Tarihi | 25 Mayıs 2025 |
| Yayımlandığı Sayı | Yıl 2025 Cilt: 6 Sayı: 1 |
