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Jeodezik Tekniklerle ve İHA'nın Fotogrametrik Kullanımı ile Üretilen Sayısal Yükseklik Modellerinin Karşılaştırılması

Year 2020, Volume: 2 Issue: 2, 58 - 69, 15.12.2020

Abstract

Son yıllarda fotogrametrik amaçlı harita üretiminde İnsansız Hava Araçları (İHA) sıklıkla kullanılmaktadır. Hava fotogrametrisinde kullanılan kameraların aksine, İHA kameraları metrik olmayan kameralardır. Bu nedenle fotogrametride kullanmak için bazı işlemlere ihtiyaç duyarlar. 3 Boyutlu model üretiminde kameranın farklı pozisyonlardan bindirmeli fotoğraf çekimi esasına dayalı Structure from Motion (SfM) algoritmaları, metrik olmayan kameraların kullanılmasına olanak sağlamaktadır. Bu algoritmalar genellikle fotoğraflardaki anahtar noktaları (öznitelik çıkarma yoluyla) tanımlar ve bindirmeli görüntülerde bağlantı noktalarını (öznitelik noktası eşleştirmesi yoluyla) eşleştirir. SfM, yüksek çözünürlüklü fotoğraflar aracılığıyla kenar noktaları köşe noktaları gibi kilit noktaları (keypoint) tanımlayarak eşleşecek anahtar nokta (tie point) üreten bir fotogrametrik tekniktir. Bu çalışmanın amacı, İHA'lar ile çekilmiş fotoğraflardan 3B model üreterek, arazi verilerinden elde edilen 3B modelin karşılaştırılmasıdır. Bu karşılaştırmada SfM algoritma performansı, uçuş yüksekliği, bindirme oranı ve İHA türünün model üzerindeki etkileri incelenmiş ve önemli sonuçlar elde edilmiştir. Ayrıca farklı uçuş yüksekliklerine sahip İHA fotoğraflarından elde edilen modeller ve farklı eğim özelliklerine sahip arazilerde de karşılaştırmalar gerçekleştirildi. Sonuç olarak 80 m uçuş yüksekliği ile 120 m uçuş yüksekliği arasındaki farkın (en büyük fark olarak) 20 cm olduğu (Z değerinde) tespit edilmiştir.

Supporting Institution

Selçuk Üniversitesi Bilimsel Araştırma Projeleri Koordinatörlüğü

Project Number

18401080

References

  • 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.
  • Ahn, S, and Jeffrey A. F. (2003). "Standard errors of mean, variance, and standard deviation estimators." EECS Department, The University of Michigan, 1-2.
  • Amukele, T. K., Sokoll, L. J., Pepper, D., Howard, D. P., & Street, J. (2015). Can unmanned aerial systems (drones) be used for the routine transport of chemistry, hematology, and coagulation laboratory specimens?. PloS one, 10(7), e0134020.
  • Arik, S, Turkmen I, and Oktay T. (2018). "Redesign of morphing UAV for simultaneous improvement of directional stability and maximum lift/drag ratio." Advances in Electrical and Computer Engineering 18.4: 57-63.
  • Berni, J. A., Zarco-Tejada, P. J., Suárez, L., & Fereres, E. (2009). Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Transactions on geoscience and Remote Sensing, 47(3), 722-738.
  • Carr, B. B., Clarke, A. B., Arrowsmith, J. R., Vanderkluysen, L., & Dhanu, B. E. (2019). The emplacement of the active lava flow at Sinabung Volcano, Sumatra, Indonesia, documented by structure-from-motion photogrammetry. Journal of Volcanology and Geothermal Research, 382, 164-172.
  • Clapuyt, F., Vanacker, V., & Van Oost, K. (2016). Reproducibility of UAV-based earth topography reconstructions based on Structure-from-Motion algorithms. Geomorphology, 260, 4-15.
  • Comert, R., Avdan, U., Gorum, T., & Nefeslioglu, H. A. (2019). Mapping of shallow landslides with object-based image analysis from unmanned aerial vehicle data. Engineering Geology, 260, 105264.
  • Colomina, I., & Molina, P. (2014). Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS Journal of photogrammetry and remote sensing, 92, 79-97.
  • Cryderman, C., Mah, S. B., & Shufletoski, A. (2014). Evaluation of UAV photogrammetric accuracy for mapping and earthworks computations. Geomatica, 68(4), 309-317.
  • Draeyer, B., & Strecha, C. (2014). White paper: How accurate are UAV surveying methods. Pix4D White Paper.
  • Gaikwad, L. M., Teli, S. N., Majali, V. S., & Bhushi, U. M. (2016). An application of Six Sigma to reduce supplier quality cost. Journal of The Institution of Engineers (India): Series C, 97(1), 93-107.
  • Govender, N. (2009). "Evaluation of feature detection algorithms for structure from motion.”
  • Makineci, H. B., and Karabörk H. (2016). "Evaluation Digital Elevation Model Generated by Synthetic Aperture Radar Data." International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences 41.
  • Makineci, H. B., Karabörk, H., & Durdu, A. (2020). “The Performance Evaluation of Image Matching Techniques within UAV Images”, Turkish Journal of Geosciences, 1(1), 8-14.
  • Martínez-Carricondo, P., Agüera-Vega, F., Carvajal-Ramírez, F., Mesas-Carrascosa, F. J., García-Ferrer, A., & Pérez-Porras, F. J. (2018). Assessment of UAV-photogrammetric mapping accuracy based on variation of ground control points. International journal of applied earth observation and geoinformation, 72, 1-10.
  • Mesas-Carrascosa, F. J., Notario-García, M. D., de Larriva, J. E. M., de la Orden, M. S., & Porras, A. G. F. (2014). Validation of measurements of land plot area using UAV imagery. International Journal of Applied Earth Observation and Geoinformation, 33, 270-279.
  • Micheletti, N, Jim H. C, and Stuart N. L. (2015). "Structure from motion (SFM) photogrammetry."
  • Sabins, F F. (2007). “Remote sensing: principles and applications.” Waveland Press.
  • Strecha, C. (2014). "The rayCloud–a vision beyond the point cloud." FIG Congress.
  • Uysal, M, Yılmaz, M, Tiryakioğlu, İ, Polat, N. (2018). İnsansız hava araçlarının afet yönetiminde kullanımı. Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler, 6, 219-224.
  • Thiels, C. A., Aho, J. M., Zietlow, S. P., & Jenkins, D. H. (2015). Use of unmanned aerial vehicles for medical product transport. Air medical journal, 34(2), 104-108.
  • 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.

Comparison of Digital Elevation Models Produced with Photogrammetric Usage of UAV by Geodetic Techniques

Year 2020, Volume: 2 Issue: 2, 58 - 69, 15.12.2020

Abstract

Unmanned Aerial Vehicles (UAV) use in the production of the map for photogrammetric purposes. Unlike aerial photogrammetry, UAV cameras are non-metric amateur cameras. Therefore, they need some operations to use in photogrammetry. Structure from Motion (SfM) algorithms prefers for processing images because of the usage of the non-metric cameras. These algorithms generally identify key-points (via feature extraction) on the photos and match tie-points (via feature point matching) in overlap images. SfM is a photogrammetric technique that produces keypoint to match by identifying key points, such as edge-to-corner points, through high-resolution RGB photos. The scope of this study was to compare the results obtained by UAVs and the results acquired by ground truth data. In this comparison, SfM algorithm performance, the effects of flight height, overlap rate, and UAV-type on the model investigated, and significant results achieved. Additionally, the models obtained from the UAV photographs with different flight heights and overlaps in the areas with varying characteristics of the slope compared. Consequently, it determined the difference between around 20 cm (Z value), comparing the flight height of 80 m and the flight height of 120 m. Since it is observed that the flight height does not have a significant effect.  

Project Number

18401080

References

  • 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.
  • Ahn, S, and Jeffrey A. F. (2003). "Standard errors of mean, variance, and standard deviation estimators." EECS Department, The University of Michigan, 1-2.
  • Amukele, T. K., Sokoll, L. J., Pepper, D., Howard, D. P., & Street, J. (2015). Can unmanned aerial systems (drones) be used for the routine transport of chemistry, hematology, and coagulation laboratory specimens?. PloS one, 10(7), e0134020.
  • Arik, S, Turkmen I, and Oktay T. (2018). "Redesign of morphing UAV for simultaneous improvement of directional stability and maximum lift/drag ratio." Advances in Electrical and Computer Engineering 18.4: 57-63.
  • Berni, J. A., Zarco-Tejada, P. J., Suárez, L., & Fereres, E. (2009). Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Transactions on geoscience and Remote Sensing, 47(3), 722-738.
  • Carr, B. B., Clarke, A. B., Arrowsmith, J. R., Vanderkluysen, L., & Dhanu, B. E. (2019). The emplacement of the active lava flow at Sinabung Volcano, Sumatra, Indonesia, documented by structure-from-motion photogrammetry. Journal of Volcanology and Geothermal Research, 382, 164-172.
  • Clapuyt, F., Vanacker, V., & Van Oost, K. (2016). Reproducibility of UAV-based earth topography reconstructions based on Structure-from-Motion algorithms. Geomorphology, 260, 4-15.
  • Comert, R., Avdan, U., Gorum, T., & Nefeslioglu, H. A. (2019). Mapping of shallow landslides with object-based image analysis from unmanned aerial vehicle data. Engineering Geology, 260, 105264.
  • Colomina, I., & Molina, P. (2014). Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS Journal of photogrammetry and remote sensing, 92, 79-97.
  • Cryderman, C., Mah, S. B., & Shufletoski, A. (2014). Evaluation of UAV photogrammetric accuracy for mapping and earthworks computations. Geomatica, 68(4), 309-317.
  • Draeyer, B., & Strecha, C. (2014). White paper: How accurate are UAV surveying methods. Pix4D White Paper.
  • Gaikwad, L. M., Teli, S. N., Majali, V. S., & Bhushi, U. M. (2016). An application of Six Sigma to reduce supplier quality cost. Journal of The Institution of Engineers (India): Series C, 97(1), 93-107.
  • Govender, N. (2009). "Evaluation of feature detection algorithms for structure from motion.”
  • Makineci, H. B., and Karabörk H. (2016). "Evaluation Digital Elevation Model Generated by Synthetic Aperture Radar Data." International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences 41.
  • Makineci, H. B., Karabörk, H., & Durdu, A. (2020). “The Performance Evaluation of Image Matching Techniques within UAV Images”, Turkish Journal of Geosciences, 1(1), 8-14.
  • Martínez-Carricondo, P., Agüera-Vega, F., Carvajal-Ramírez, F., Mesas-Carrascosa, F. J., García-Ferrer, A., & Pérez-Porras, F. J. (2018). Assessment of UAV-photogrammetric mapping accuracy based on variation of ground control points. International journal of applied earth observation and geoinformation, 72, 1-10.
  • Mesas-Carrascosa, F. J., Notario-García, M. D., de Larriva, J. E. M., de la Orden, M. S., & Porras, A. G. F. (2014). Validation of measurements of land plot area using UAV imagery. International Journal of Applied Earth Observation and Geoinformation, 33, 270-279.
  • Micheletti, N, Jim H. C, and Stuart N. L. (2015). "Structure from motion (SFM) photogrammetry."
  • Sabins, F F. (2007). “Remote sensing: principles and applications.” Waveland Press.
  • Strecha, C. (2014). "The rayCloud–a vision beyond the point cloud." FIG Congress.
  • Uysal, M, Yılmaz, M, Tiryakioğlu, İ, Polat, N. (2018). İnsansız hava araçlarının afet yönetiminde kullanımı. Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler, 6, 219-224.
  • Thiels, C. A., Aho, J. M., Zietlow, S. P., & Jenkins, D. H. (2015). Use of unmanned aerial vehicles for medical product transport. Air medical journal, 34(2), 104-108.
  • 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.
There are 23 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Hasan Bilgehan Makineci 0000-0003-3627-5826

Hakan Karabörk 0000-0001-7387-7004

Akif Durdu 0000-0002-5611-2322

Project Number 18401080
Publication Date December 15, 2020
Acceptance Date October 17, 2020
Published in Issue Year 2020 Volume: 2 Issue: 2

Cite

APA Makineci, H. B., Karabörk, H., & Durdu, A. (2020). Comparison of Digital Elevation Models Produced with Photogrammetric Usage of UAV by Geodetic Techniques. Türkiye Uzaktan Algılama Dergisi, 2(2), 58-69.
AMA Makineci HB, Karabörk H, Durdu A. Comparison of Digital Elevation Models Produced with Photogrammetric Usage of UAV by Geodetic Techniques. TUZAL. December 2020;2(2):58-69.
Chicago Makineci, Hasan Bilgehan, Hakan Karabörk, and Akif Durdu. “Comparison of Digital Elevation Models Produced With Photogrammetric Usage of UAV by Geodetic Techniques”. Türkiye Uzaktan Algılama Dergisi 2, no. 2 (December 2020): 58-69.
EndNote Makineci HB, Karabörk H, Durdu A (December 1, 2020) Comparison of Digital Elevation Models Produced with Photogrammetric Usage of UAV by Geodetic Techniques. Türkiye Uzaktan Algılama Dergisi 2 2 58–69.
IEEE H. B. Makineci, H. Karabörk, and A. Durdu, “Comparison of Digital Elevation Models Produced with Photogrammetric Usage of UAV by Geodetic Techniques”, TUZAL, vol. 2, no. 2, pp. 58–69, 2020.
ISNAD Makineci, Hasan Bilgehan et al. “Comparison of Digital Elevation Models Produced With Photogrammetric Usage of UAV by Geodetic Techniques”. Türkiye Uzaktan Algılama Dergisi 2/2 (December 2020), 58-69.
JAMA Makineci HB, Karabörk H, Durdu A. Comparison of Digital Elevation Models Produced with Photogrammetric Usage of UAV by Geodetic Techniques. TUZAL. 2020;2:58–69.
MLA Makineci, Hasan Bilgehan et al. “Comparison of Digital Elevation Models Produced With Photogrammetric Usage of UAV by Geodetic Techniques”. Türkiye Uzaktan Algılama Dergisi, vol. 2, no. 2, 2020, pp. 58-69.
Vancouver Makineci HB, Karabörk H, Durdu A. Comparison of Digital Elevation Models Produced with Photogrammetric Usage of UAV by Geodetic Techniques. TUZAL. 2020;2(2):58-69.

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