DÜŞÜK MALİYETLİ İNSANSIZ HAVA ARAÇLARI İÇİN UÇUŞ ÖNCESİ BLOK PLANLAMANIN DEĞERLENDİRİLMESİ

Year 2021, Volume: 5 Issue: 1, 114 - 126, 30.04.2021

Sercan Gülci , Hüseyin Yurtseven , Mustafa Akgül

https://doi.org/10.32328/turkjforsci.856994

Cited By: 1

Abstract

Son yıllarda geliştirilen düşük maliyetli insansız hava araçları (İHA) ve yazılımlar, çok yüksek konumsal çözünürlükte ve kullanıcı tarafından belirlenen aralıklarda düşük maliyetli görüntüleme imkanı sunmaktadır. Ormancılık ile ilgili ölçme ve haritalama kapsamında, dünyada olduğu gibi Türkiye'de de düşük maliyetli İHA talepleri önemli ölçüde artmaktadır. Buna bağlı olarak düşük maliyetli İHA ve sensörleri hızla piyasaya sürülmektedir. Sonuç olarak ürün çeşitliliği hızla artmaktadır. Kullanılan teknikler, yöntemler ve ölçüm araçları İHA ile üretilen verilerin hassasiyetini etkileyen önemli faktörlerdir. Ayrıca, İHA ile elde edilen blok alım kalitesi ve hassasiyeti çevresel faktörlerin yanı sıra uçuş hızı, uçuş yüksekliği ve kullanılan görüntü algılayıcıların özelliklerine bağlı olarak değişmektedir. Bu çalışmada, Structure-from-Motion (SfM) tekniği ile kullanılan düşük maliyetli İHA’nın uçuş öncesi değerlendirilme ve blok alımı planlaması üzerinde durulmuştur. Bu nedenle, İHA'lar ile elde edilen blok alımın bilimsel araştırmalarda ve uygulamalarda istenilen hassasiyeti sağlayabilmek için uçuş öncesi planlama kapsamında irdelenmiştir. Piyasada düşük maliyetli olarak satılan bir İHA (Drone) için beş farklı uçuş öncesi plan hesaplanmıştır. İHA’nın uçuş kapasitesi, üzerindeki sensör özellikleri ve uçuş yükseklikleri arasındaki ilişkiler göz önünde bulundurulmuştur. Sonuç olarak, düşük maliyetli İHA ve üzerine monte edilmiş görüntü sensörünün maksimum ve minimum performansı, birkaç teknik bilgi yardımıyla tahmin edilebilmektedir. Böylece İHA ile elde edilecek veri hassasiyetinin tahmini ve uçuş güvenliği konusunda bilgi sağlanabilir. Bu makale, araştırmalarında düşük maliyetli İHA veya mikro İHA gibi yarı otomatik sistemleri fotogrametrik çalışmalarında kullanmak isteyen uzmanlar veya araştırmacılar için ön kontrol planlamalarına rehberlik etmeyi amaçlamaktadır.

Keywords

Uzaktan algılama, düşük maliyetli İHA, İHA fotogrametrisi, uçuş öncesi planlama, ormancılık

ASSESSMENT OF PRE-FLIGHT BLOCK PLANNING FOR LOW-COST UNMANNED AIR VEHICLES

Abstract

Recent development in low-cost Unmanned Aerial Vehicles (UAVs) and software, which offer low-cost imagining at user defined the aerial photogrammetry is widely preferred for mapping and field measurement purposes because of its time and cost-benefit in various applications. Within the scope of forestry-related surveying and mapping, the demand for low-cost drones in Turkey and the world has increased dramatically. Accordingly, low-cost UAVs and its sensors are rapidly being introduced to the market. Consequently, product varieties increase rapidly. The techniques, methods, and measurement tools used are important factors affecting the sensitivity of the data obtained by the UAVs. Besides, the quality and sensitivity of the block acquisition obtained with UAVs varies depending on the environmental factors as well as the flight speed, flight altitude and the characteristics of sensors. In the present study, low-cost UAV used in the Structure-from-Motion (SfM) studies was evaluated and examined pre-flight block planning scenarios. Hence the block acquisition obtained by UAVs has been explored for the scope of pre-flight planning in order to provide the proper sensitivity in scientific research and applications. Five different pre-flight plans were calculated for a low-cost drone in the market, especially considering the UAV (Drone)’s flight capacity and its sensor feature and flight altitudes. The maximum and minimum performance of the low-cost UAV-mounted image sensor can be estimated with the help of a few technical information. Therefore, it is possible to predict and ensure data sensitivity and flight safety obtained by drones. This article aims to provide a pre-control plan for experts or researchers who tend to use semi-automated systems such as low-cost drones or micro drones in field surveys based on photogrammetry.

Keywords

Remote sensing, low-cost UAV, UAV photogrammetry, pre-flight planning, forestry

References

• Akgül, M., Yurtseven, H., Demir, M., Akay, A.E., Gülci, S., & Öztürk, T., (2016) Usage opportunities of generating digital elevation model with unmanned aerial vehicles on forestry. Journal of the Faculty of Forestry Istanbul University, 66(1), 104-118.
• Akgul, M., Yurtseven, H., Gulci, S., & Akay, A.E., (2018) Evaluation of UAV-and GNSS-based DEMs for earthwork volume. Arabian Journal for Science and Engineering, 43(4), 1893-1909.
• Akturk, E., & Altunel, A. O., 2019. Accuracy assessment of a low-cost UAV derived digital elevation model (DEM) in a highly broken and vegetated terrain. Measurement, 136, 382-386.
• Banu, T. P., Borlea, G. F., & Banu, C., (2016) The use of drones in forestry. Journal of Environmental Science and Engineering B, 5(11), 557-562.
• Buğday, E., (2018) Capabilities of using UAVs in forest road construction activities. European Journal of Forest Engineering, 4(2), 56-62.
• Coşkun, M.Z., (2012) Today and future of mobile mapping via low cost UAV (Unmanned Aerial Vehicles). Electronic Journal of Map Technologies, 4(2), 11-18. [Turkish]
• Dandois, J. P., Olano, M., & Ellis, E. C. (2015) Optimal altitude, overlap, and weather conditions for computer vision UAV estimates of forest structure. Remote Sensing, 7(10), 13895-13920.
• Dji (2016) Specifications of DJI Inspire One Pro. http://www.dji.com/product/inspire-1-pro-and-raw (Ziyaret tarihi: 10.04.2016)
• Dji (2016a) Specifications of Zenmuse x5. http://www.dji.com/product/zenmuse-x5s/info#specs (Ziyaret tarihi: 10.04.2016)
• Dudek, M., Tomczyk, P., Wygonik, P., Korkosz, M., Bogusz, P., & Lis, B., (2013) Hybrid fuel cell-battery system as a main power unit for small Unmanned Aerial Vehicles (UAV). International Journal of Electrochemical Science, 8(6), 8442-63.
• Eisenbeiss, H., (2009) UAV photogrammetry. Dissertation ETH No. 18515, Institute of Geodesy and Photogrammetry, ETH Zurich, Switzerland, Mitteilungen 105.
• 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.
• Eker. R., & Aydın, A., (2020) The use of Unmanned Aerial Vehicle (UAV) for tracking stock movements in forest enterprise depots. European Journal of Forest Engineering, 6(2), 68-77.
• Erdin, K., (1992) Fotogrametri. Istanbul Üniversitesi Matbası, İstanbul.
• Grenzdörffer, G. J., Engel, A., & Teichert, B., (2008) The photogrammetric potential of low-cost UAVs in forestry and agriculture. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 31(B3), 1207-1214.
• 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.
• Gülci, S., & Akay, A.E., (2016) Using thermal infrared imagery produced by unmanned air vehicles to evaluate locations of ecological road structures. Journal of the Faculty of Forestry Istanbul University 66 (2): 698-709. doi:10.17099/jffiu.76461 [Turkish]
• Hardin, P.J., & Jensen, R.R., (2011) Small-scale unmanned aerial vehicles in environmental remote sensing: challenges and opportunities. GIScience and Remote Sensing, 48(1), 99-111.
• Leckie, D. G., & Gillis, M., (1995) Forest inventory in Canada with emphasis on map production. Forestry Chronicle, 71: 74–88.
• Mesas-Carrascosa, F. J., Torres-Sánchez, J., Clavero-Rumbao, I., García-Ferrer, A., Peña, J. M., Borra-Serrano, I., & López-Granados, F., (2015) Assessing optimal flight parameters for generating accurate multispectral orthomosaicks by UAV to support site-specific crop management. Remote Sensing, 7(10), 12793-12814.
• Oğuz, H., & Gülci S., (2019) The use of unmanned aerial vehicles Kahramanmaras-Turkey. (Proceedings) III. International Mediterranean Forest and Environment Symposium, November 30, Kahramanmaras, Turkey. 139-144 pp.
• Papakonstantinou, A., Topouzelis, K., & Pavlogeorgatos, G., (2016) Coastline zones identification and 3D coastal mapping using UAV Spatial Data. ISPRS International Journal of Geo-Information, 5(6), 75.
• Pepe, M., Fregonese, L., & Scaioni, M., (2018) Planning airborne photogrammetry and remote-sensing missions with modern platforms and sensors. European Journal of Remote Sensing, 51(1), 412-436.
• Pérez, M., Agüera, F., & Carvajal, F., (2013) Low cost surveying using an unmanned aerial vehicle. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1/W2, 2013 UAV-g2013, 4 – 6 September, Rostock, Germany.
• PSU (2015) https://www.e-education.psu.edu/geog892/node/658 (Ziyaret tarihi: 19 Nisan 2015)
• SHGM (2020) (Sivil Havacılık Genel Müdürlüğü) http://web.shgm.gov.tr/documents/sivilhavacilik/files/ mevzuat/sektorel/talimatlar/2020/SHT-IHA_Rev-04.pdf (Ziyaret tarihi: 07 Nisan 2021)
• Tang, L., and Shao, G. (2015) “Drone Remote Sensing for Forestry Research and Practices: Review Article.” Journal of Forestry Research 26 (4): 791-7.
• Torresan, C., Berton, A., Carotenuto, F., Di Gennaro, S. F., Gioli, B., Matese, A., ... & Wallace, L., (2017) Forestry applications of UAVs in Europe: A review. International Journal of Remote Sensing, 38(8-10), 2427-2447.
• Van Blyenburgh, P., (1999) UAVs: an overview. Air & Space Europe, 1(5/6), 43-47.
• Vautherin, J., Rutishauser, S., Schneider-Zapp, K., Choi, H. F., Chovancova, V., Glass, A., & Strecha, C., (2016) Photogrammetric accuracy and modeling of rolling shutter cameras. ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences, 3(3).
• Wallace, L., Lucieer, A., Malenovskè, Z., Turner, D. & Vopěnka, P., (2016) Assessment of forest structure using two UAV techniques: a comparison of airborne laser scanning and structure from motion (SfM) point clouds. Forests, 7, 1-16.
• Watts, A.C., Ambrosia, V.C., & Hinkley, E.A., (2012) Unmanned aircraft systems in remote sensing and scientific research: classification and considerations of use. Remote Sensing, 4, 1671-1692.
• Wing, M.G., Burnett, S., Johnson, S., Akay, A.E., & Sessions, J., (2014) A Low-cost unmanned aerial system for remote sensing of forested landscapes. International Journal of Remote Sensing Applications, 4(3), 113-120.
• Yundong, W.U., Qiang, Z., & Shaoqin, L., (2008) A contrast among experiments in three low-altitude unmanned aerial vehicles photography: Security, quality & efficiency. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37(B1), 1223–1227.
• Yurtseven, H., (2019). Comparison of GNSS-, TLS-and different altitude UAV-generated datasets on the basis of spatial differences. ISPRS International Journal of Geo-Information, 8(4), 175.
• 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.
• Zeybek, M., & Şanlıoğlu, İ., (2020) Investigation of landslide detection using radial basis functions: a case study of the Taşkent landslide, Turkey. Environmental Monitoring and Assessment, 192(4), 1-19.