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İnsansız Hava Araçları ve Coğrafi Bilgi Sistemleri Uygulamaları

Year 2023, , 20 - 33, 30.06.2023
https://doi.org/10.56130/tucbis.1297245

Abstract

İnsansız hava araçları son yıllarda sadece askeri uygulamalarda değil mühendislik, bilimsel ve endüstriyel alanlarda sıklıkla kullanılmaktadır. Gelişen teknolojiyle birlikte, birçok aktif veya pasif algılayıcılarla donatılan insansız hava araçları sayesinde hassas veriler elde edilebilmektedir. Uydu verilerine göre düşük maliyetli, hızlı ve analitik çözümler sağlayan insansız hava araçları verileri aynı zamanda mekânsal, radyometrik, spektral ve zamansal çözünürlük açısından da avantajlıdır. Bu verilerin kalitesi, bu veriler ile üretilen 2 ve 3 boyutlu haritalar, ortofotolar, indeks haritaları ve nokta bulutu verilerinin kalitesini ve doğruluğunu da aynı oranda etkilemektedir. Coğrafi bilgi sistemlerine altlık olan bu çıktılar sayesinde, hassas ve nitelikli sonuçlar elde edilebilmektedir. Afet yönetimi, şehir planlama çalışmaları, telekomünikasyon faaliyetleri, risk hesaplama uygulamaları gibi birçok önemli çalışmada insansız hava araçları verileri, coğrafi bilgi sistemlerinin altlık verilerini oluşturmaktadır. Bu çalışma kapsamında, insansız hava aracı ve coğrafi bilgi sistemleri uygulamaları üzerinde durulmuş ve literatürde yapılan çalışmalara yer verilmiştir. Son olarak gelecekteki beklentiler sıralanmıştır.

References

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Unmanned Aerial Vehicles and Geographic Information Systems Applications

Year 2023, , 20 - 33, 30.06.2023
https://doi.org/10.56130/tucbis.1297245

Abstract

Unmanned aerial vehicles have been used not only in military applications but also in engineering, scientific and industrial applications in recent years. With the developing technology, sensitive data can be obtained thanks to the unmanned aerial vehicles equipped with many active or passive sensors. Unmanned aerial vehicle data, which provides low-cost, fast and analytical solutions compared to satellite data, is also advantageous in terms of spatial, radiometric, spectral and temporal resolution. The quality of this data also affects the quality and accuracy of the 2D and 3D maps, orthophotos, index maps and point cloud data produced with these data. Thanks to these outputs, which are the basis of geographic information systems, sensitive and convenient results can be obtained. In many important studies such as disaster management, city planning studies, telecommunication activities, risk calculation applications, unmanned aerial vehicle data constitute the base data of geographic information systems. Within the scope of this study, unmanned aerial vehicles and geographic information systems applications are emphasized and studies in the literature are included. Finally, expectations for the future are listed.

References

  • Alptekin A, Çelik M Ö, Doğan Y & Yakar M (2019). Mapping of a Rockfall Site with an Unmanned Aerial Vehicle. Mersin Photogrammetry Journal, 1 (1), 12-16.
  • Alptekin A, Çelik M Ö, Kuşak L, Ünel F B & Yakar M (2019). Anafi Parrot’un Heyelan Bölgesi Haritalandırılmasında Kullanımı. Türkiye İnsansız Hava Araçları Dergisi, 1(1), 33-37.
  • Alptekin A & Yakar M (2020a). Determination of Pond Volume with Using an Unmanned Aerial Vehicle. Mersin Photogrammetry Journal, 2 (2), 59-63.
  • Alptekin A & Yakar, M (2020b). Heyelan bölgesinin İHA kullanarak modellenmesi. Türkiye İnsansız Hava Araçları Dergisi, 2(1), 17-21.
  • Alptekin A & Yakar M (2021). 3D Model of Üçayak Ruins Obtained from Point Clouds. Mersin Photogrammetry Journal, 3 (2), 37-40. https://doi.org/10.53093/mephoj.939079
  • Alptekin A & Yakar M (2022). Modelling A Landslide Site Using UAV Photogrammetry in Değirmençay Village, Mersin. Intercontinental Geoinformation Days, 4, 196-198.
  • Başarsoft (2023). Coğrafi Bilgi SCBS Nedir? [Erişim Tarihi: 06.05.2023], https://www.basarsoft.com.tr/cografi-bilgi-sistemleri-cbs-nedir/
  • Bento M D F (2008). Unmanned Aerial Vehicles: An Overview. InsideGNSS, 54-61.
  • Bretschneider T R & Shetti K (2015). UAV-Based Gas Pipeline Leak Detection. In Proc. of ARCS.
  • Ca (2023). Current Emergency Incidents, [Erişim Tarihi: 10.05.2023], https://www.fire.ca.gov/incidents/.
  • Carey J A, Pinter N, Pickering A J, Prentice C S & Delong S B (2019). Analysis of Landslide Kinematics Using Multi-temporal Unmanned Aerial Vehicle Imagery, La Honda, California. Environmental & Engineering Geoscience, 25(4), 301-317. https://doi.org/10.2113/EEG-2228
  • Cilek A, Berberoglu S, Donmez C & Cilek M. U. (2020). Journal of Digital Landscape Architecture, 5-2020, 275-284.
  • Cömert R, Şenkal E & Avdan U (2012). İnsansız Hava Araçlarının Kullanım Alanları ve Gelecekteki Beklentiler. IV. Uzaktan Algılama ve CBS Sempozyumu (UZAL-CBS 2012), Zonguldak, Türkiye.
  • Dabski M, Zmarz A, Pabjanek P, Korczak-Abshire M, Karsznia I & Chwedorzewska K J (2017). UAV-based detection and spatial analyses of periglacial landforms on Demay Point (King George Island, South Shetland Islands, Antarctica). Geomorphology, 290, 29-38.
  • De Smet T S, Nikulin A, Romanzo N, Graber N, Dietrich C & Puliaiev A (2021). Successful Application of Drone-Based Aeromagnetic Surveys to Locate Legacy Oil and Gas Wells in Cattaraugus County, New York. Journal of Applied Geophysics, 186, 104250. https://doi.org/10.1016/j.jappgeo.2020.10425
  • Dewanto B G, Novitasari D, Tan Y C, Puruhito D D, Fikriyadi Z A & Aliyah F (2020). Application of Web 3D GIS to Display Urban Model and Solar Energy Analysis using The Unmanned Aerial Vehicle (UAV) Data (Case Study: National Cheng Kung University Buildings). In IOP Conference Series: Earth and Environmental Science, 20(1), 12-17.
  • Donmez C, Villi O, Berberoglu S & Cilek A (2021). Computer Vision-Based Citrus Tree Detection in a Cultivated Environment Using UAV Imagery. Computers and Electronics in Agriculture, 187, 106273. https://doi.org/10.1016/j.compag.2021.106273
  • Duarte L, Silva P & Teodoro A C (2018). Development of a QGIS Plugin to Obtain Parameters and Elements of Plantation Trees and Vineyards with Aerial Photographs. ISPRS International Journal of Geo-Information, 7(3), 109. https://doi.org/10.3390/ijgi7030109
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  • Fareed N & Rehman K (2020). Integration of Remote Sensing and GIS to Extract Plantation Rows from a Drone-Based Image Point Cloud Digital Surface Model. ISPRS International Journal of Geo-Information, 9(3), 151. https://doi.org/10.3390/ijgi9030151
  • Fukano Y, Guo W, Aoki N, Ootsuka S, Noshita K, Uchida K, Kato Y, Sasaki K, Kamikawa S & Kubota H (2021). GIS-based Analysis for UAV-Supported Field Experiments Reveals Soybean Traits Associated with Rotational Benefit. Frontiers in Plant Science, 12, 637694. https://doi.org/10.3389/fpls.2021.637694
  • Gantimurova S, Parshin A & Erofeev V (2021). GIS-Based Landslide Susceptibility Mapping of the Circum-Baikal Railway in Russia Using UAV Data. Remote Sensing, 13(18), 3629. https://doi.org/10.3390/rs13183629
  • Gislounge (2021). Autonomous UAVs and Geospatial Data, [Erişim Tarihi: 11.05.2023], https://www.gislounge.com/autonomous-uavs-and-geospatial-data/
  • Kanun E, Alptekin A & Yakar M (2021). Cultural Heritage Modelling Using UAV Photogrammetric Methods: A Case Study of Kanlıdivane Archeological Site. Advanced UAV, 1(1), 24-33.
  • Kanun E, Alptekin A, Karataş L & Yakar M (2022). The Use of UAV Photogrammetry in Modeling Ancient Structures: A case Study of “Kanytellis”. Advanced UAV, 2(2), 41-50.
  • Karakose, E. (2017). Performance Evaluation of Electrical Transmission Line Detection and Tracking Algorithms Based on Image Processing Using UAV," International Artificial Intelligence and Data Processing Symposium (IDAP), Malatya, Turkey.
  • Kınalı M & Çalışkan E (2022). Use of Unmanned Aerial Vehicles in Forest Road Projects. Bartın Orman Fakültesi Dergisi, 24(3), 1-1. https://doi.org/10.24011/barofd.1073229
  • Koçyiğit, F. U., Durduran, S. S. & Alkan, T. (2022). Creatıng Geographical Information System (Gıs) Database with Unmanned Aerial Vehicles (Uav) In Archaelogical Areas; The Case of Anemurium Ancient City. Journal of Engineering Sciences and Design, 10(3), 831-843. https://doi.org/10.21923/jesd.999829
  • Kusak L, Unel F, Alptekin A, Celik M & Yakar M (2021). Apriori Association Rule and K-Means Clustering Algorithms for Interpretation of Pre-Event Landslide Areas and Landslide Inventory Mapping. Open Geosciences, 13(1), 1226-1244.
  • Kyriou A, Nikolakopoulos K, Koukouvelas I & Lampropoulou P (2021). Repeated UAV Campaigns, GNSS Measurements, GIS, and Petrographic Analyses for Landslide Mapping and Monitoring. Minerals, 11(3), 300. https://doi.org/10.3390/min11030300
  • Liao K C & Lu J H (2021). Using UAV to Detect Solar Module Fault Conditions of a Solar Power Farm with IR and Visual Image Analysis. Applied Sciences, 11(4), 1835. https://doi.org/10.3390/app11041835
  • Lifeingis (2023). UAVs in the GIS industry: Applications, Trends and Future Outlook, [Erişim Tarihi: 10.05.2023], https://www.lifeingis.com/uavs-in-gis-industry/
  • Mangiameli M, Muscato G, Mussumeci G & Milazzo C (2013). A GIS Application for UAV Flight Planning. IFAC Proceedings, 46(30), 147-151.
  • Morgenthal G & Hallermann N (2014). Quality Assessment of Unmanned Aerial Vehicle (UAV) Based Visual Inspection of Structures. Advances in Structural Engineering, 17(3), 289-302. https://doi.org/10.1260/1369-4332.17.3.289
  • Noo, N ., Abdullah A A A, Abdullah A, Ibrahim I & Sabeek S (2019). 3D City Modeling Using Multirotor Drone for City Heritage Conservation. Planning Malaysia, 17. https://doi.org/10.21837/pm.v17i9.610
  • Odo A, McKenna S, Flynn D & Vorstius J (2020). Towards the Automatic Visual Monitoring of Electricity Pylons from Aerial Images. 15th International Conference on Computer Vision Theory and Applications, 566-573.
  • Ok A O & Ozdarici-Ok A (2017). Detection of Citrus Tree from UAV DSMS. ISPRS Annals o the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume IV-1/W1, 2017 ISPRS Hannover Workshop: HRIGI 17 – CMRT 17 – ISA 17. – EuroCOW 17, 6–9 June 2017, Hannover, Germany
  • Özcan O (2017). İnsansız Hava Aracı (İHA) ile Farklı Yüksekliklerden Üretilen Sayısal Yüzey Modellerinin (SYM) Doğruluk Analizi. Mühendislik ve Yer Bilimleri Dergisi, 2(1), 1-7.
  • PSU (2023). Emerging Theme: GIS and UAVs, [Erişim Tarihi: 10.05.2023] https://www.e-education.psu.edu/geog858/node/557/.
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There are 58 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Review Article
Authors

Osman Villi 0000-0002-8174-409X

Murat Yakar 0000-0002-2664-6251

Early Pub Date June 23, 2023
Publication Date June 30, 2023
Published in Issue Year 2023

Cite

APA Villi, O., & Yakar, M. (2023). İnsansız Hava Araçları ve Coğrafi Bilgi Sistemleri Uygulamaları. Türkiye Coğrafi Bilgi Sistemleri Dergisi, 5(1), 20-33. https://doi.org/10.56130/tucbis.1297245

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