Research Article
BibTex RIS Cite

İHA'lardan Elde Edilen Konum Doğruluğunun İncelenmesi

Year 2023, Volume: 5 Issue: 2, 89 - 96, 30.12.2023
https://doi.org/10.51489/tuzal.1385412

Abstract

Sayısal Arazi Modelleri (SAM) birçok mühendislik projesinde temel veri olarak kullanılmaktadır. SAM’ların üretiminde klasik yersel tekniklerin yanı sıra yaygın olarak uzay ve uydu teknikleri ile İnsansız Hava Araçları (İHA'lar) kullanılmaktadır. SAM’ın İHA'lar yardımıyla üretilmesinde insanların ulaşmasının zor olduğu yerlerde kolaylıkla ölçümler yapılabilmekte ve geniş alanların haritaları kısa sürede üretilebilmektedir. Ancak İHA'larda en temel sorunlardan biri homojen yayılmış yer kontrol noktaları (YKN) sayısını seçerek en doğru SAM’ı elde etmektir. Bu çalışmada, SAM üretiminde uçuş yüksekliği ve YKN yoğunluğunun konum doğruluğuna etkisi araştırılmıştır. Bu amaçla test alanında yaklaşık 40 m aralıklarla 56 nokta tesis edilmiş ve 80, 100, 120 m uçuş yüksekliğinden görüntüler alınmıştır. Noktaların koordinatlarının yüksek doğrulukla elde edilmesi için hızlı statik Küresel Navigasyon Uydu Sistemleri (GNSS) yöntemi kullanılmıştır. Daha sonra homojen olarak yayılan 5, 10 ve 15 nokta sırasıyla YKN olarak seçilmiştir. Görüntüler Pix4d Mapper programında 9 farklı kombinasyonla değerlendirilerek SAM’lar üretilmiştir. Modellerden elde edilen koordinatlardan uyuşumsuz ölçüler Bland-Altman yöntemi ile belirlenerek ölçü grubundan çıkartılmıştır. Üretilen modellerin geometrik doğruluğunun belirlenmesi amacıyla modellerden elde edilen test noktalarının koordinatları ve hızlı statik GNSS ölçüm sonuçları istatistiksel yöntemlerle karşılaştırılmış ve elde edilen sonuçlar yorumlanmıştır.

References

  • Agüera-Vega F., Carvajal-Ramírez F., Martínez-Carricondo P.J., (2016), Accuracy of digital surface models and orthophotos derived from unmanned aerial vehicle photogrammetry, J. Surv. Eng., 143, 1-10.
  • 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, 1893-1909.
  • Bland J.M., Altman D.G., (1986) Statistical methods for assessing agreement between two methods of clinical measurement (PDF), Lancet, 327, 307–310.
  • Bland J.M., Altman D.G., (1999), Measuring agreement in method comparison studies, Statistical Methods in Medical Research, 8, 135–160.
  • Canis B., (2015), Unmanned aircraft systems (UAS): Commercial outlook for a new industry, CRS Report: Congressional Res. Service, September 9.
  • Dalamagkidis K., (2015), Classification of UAVs. In: Handbook of Unmanned Aerial Vehicles, Valavanis K.P., Vachtsevanos G.J. (Eds.), Springer, Dordrecht, 83-91.
  • Ewertowski M.W., Tomczyk A.M., Evans D.J.A., Roberts D.H., Ewertowski W., (2019), Operational Framework for Rapid, Very-high Resolution Mapping of Glacial Geomorphology Using Low-cost Unmanned Aerial Vehicles and Structure-from-Motion Approach, Remote Sensing, 11, 1-18.
  • Makineci, H. B., (2023), Comparative accuracy analysis of DEMs generated from descending and ascending orbit TerraSAR-X data, Bulletin of Geophysics and Oceanography Vol. 64, n. 3, pp. 259-278., DOI 10.4430/bgo00427.
  • Makineci, H. B. (2022). İstanbul İli Merkez İlçelerindeki NO2 ve CO Emisyonlarının Uzaktan Algılama ve Yersel İstasyon Verileri Kullanılarak İncelenmesi . Türkiye Uzaktan Algılama Dergisi , 4 (2) , 62-74 . DOI: 10.51489/tuzal.1160333
  • 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 orthomosaics by UAV to support site-specific crop management, Remote Sens., 7, 12793–12814.
  • Hoffman-Wellenhof B., Lichtenegger H., Wasle E., (2008), GNSS - Global Navigation Satellite Systems, Springer, Austria.
  • Hugenholtz C.H., Whitehead K., Brown O.W., Barchyn T.E., Moorman B.J., LeClair A., Riddell K., Hamilton T., (2013), Geomorphological mapping with a small unmanned aircraft system (sUAS): Feature detection and accuracy assessment of a photogrammetrically-derived digital terrain model. Geomorphology, 194, 16-24.
  • Jin S., Cardellach E., Xie F., (2014), GNSS Remote Sensing, Springer, New York.
  • Koeva M., Muneza M., Gevaer, C., Gerke M., Nex F., (2018), Using UAVs for map creation and updating. A case study in Rwanda, Survey Review, 50, 312-325.
  • Lague D., Brodu N., Leroux J., (2013), Accurate 3D comparison of complex topography with terrestrial laser scanner: application to the Rangitikei canyon (N-Z), ISPRS J. Photogramm. Remote Sens, 82, 10–26.
  • Liu X.Y., (2008), Airborne LiDAR for DEM generation: some critical issues. Progress in Physical Geography, 32, 31-49.
  • Lucieer A., De Jong S.M., Turner D., (2014), Mapping landslide displacements using Structure from Motion (SfM) and image correlation of multi-temporal UAV photography, Prog. Phys. Geogr., 38, 97–116.
  • Uysal M., Toprak A.S., Polat N., (2015), DEM generation with UAV Photogrammetry and accuracy analysis in Sahitler hill, Measurement, 73, 539–543.
  • 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.
  • Nex F., Remondino F., (2014), UAV for 3D mapping applications: a review, Applied Geomatics, 6, 1-15.
  • Ottichilo W., Khamala E., (2002), Map updating using high resolution satelite imagery – A case of the kingdom of Swaziland, International Archives of Photogrammetry and Remote Sensing, 34, 89–92.
  • Otto A., Agatz N., Campbell J., Golden B., Pesch E., (2018), Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey. Networks, 72, 411-458.
  • Rawat K. S., Lawrence E. E., (2014), A mini-UAV VTOL Platform for Surveying Applications, International Journal of Robotics and Automation (IJRA), 3, 259-267.
  • Ruzgiene B., Berteska T., Gecyte S., Jakubauskiene E., Aksamitaukas V.C., (2015), The surface modelling based on UAV Photogrammetry and qualitative estimation, Measurement, 73, 619–627.
  • Samad A. M., Kamarulzaman N., Hamdani M. A., Mastor T. A., Hashim K. A., (2013), The Potential of Unmanned Aerial Vehicle (UAV) for Civilian and Mapping Application, 2013 IEEE 3rd International Conference on System Engineering and Technology, Shah Alam, Malaysia, 19 - 20 Aug. 2013.
  • Smith M.W., Carrivick J.L., Quincey D.J., (2016), Structure from motion photogrammetry in physical geography, Progress in Physical Geography, 40, 247-275.
  • Stöckl D., Rodríguez Cabaleiro D., Van Uytfanghe K., Thienpont L.M., (2004), Interpreting method comparison studies by use of the Bland-Altman plot: reflecting the importance of sample size by incorporating confidence limits and predefined error limits in the graphic, Clinical Chemistry, 50, 2216-2218.
  • Suziedelyte Visockiene J., Puziene R., Stanionis A., Tumeliene E., (2016), Unmanned Aerial Vehicles for Photogrammetry: Analysis of Orthophoto Images over the Territory of Lithuania, International Journal of Aerospace Engineering, 2016, 1-9.
  • Tonkin T.N., Midgley N.G., Graham D.J., Labadz J.C., (2014), The potential of small unmanned aircraft systems and structure-from-motion for topographic surveys: A test of emerging integrated approaches at Cwm Idwal, North Wales, Geomorphology, 226, 35-43.
  • Westoby M.J., Brasington J., Glasser N. F., Hambrey M. J., Reynolds J.M., (2012), Structure-from-Motion photogrammetry: A low-cost, effective tool for geoscience applications, Geomorphology, 179, 300-314.
  • Yildirim O., Susam T., Yaprak S., Delen A., Inyurt S., (2016), The Availability of UAV Systems for Agricultural Purposes, Journal of Agricultural Faculty of Gaziosmanpasa University, 33, 111-120.

Investigation of Position Accuracy in UAVs

Year 2023, Volume: 5 Issue: 2, 89 - 96, 30.12.2023
https://doi.org/10.51489/tuzal.1385412

Abstract

Digital Terrain Models (DTMs) are used as primary data in many engineering projects. In addition to classical terrestrial techniques, space and satellite techniques and Unmanned Aerial Vehicles (UAVs) are commonly used in the production of the DTMs. In the production of the DTM with the help of the UAVs, measurements can be made easily where people can access hardly, and large areas can be mapped quickly. However, one of the most fundamental problems in the UAVs is to obtain the most accurate DTM by choosing the homogeneously spread ground control points (GCPs) number. In this study, the effect of flight altitude and the density of GCPs on position accuracy were investigated in production of the DTM. For this purpose, 56 points were established at approximately 40 m intervals and images from 80, 100, 120 m flight altitude were taken in the test area. The rapid static Global Navigation Satellite Systems (GNSS) method was used to obtain the coordinates of the points with high accuracy. Then, the homogeneously spread 5, 10, and 15 points were chosen as GCPs, respectively. The images were evaluated in Pix4d Mapper software with 9 different combinations and DTMs were produced. Outliers of the coordinates obtained from the models were detected by Bland-Altman Plot. To determine the geometric accuracy of the produced models, the coordinates of the test points obtained from the models and the results of rapid static GNSS measurements were compared with the statistical methods and the obtained results were interpreted.

References

  • Agüera-Vega F., Carvajal-Ramírez F., Martínez-Carricondo P.J., (2016), Accuracy of digital surface models and orthophotos derived from unmanned aerial vehicle photogrammetry, J. Surv. Eng., 143, 1-10.
  • 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, 1893-1909.
  • Bland J.M., Altman D.G., (1986) Statistical methods for assessing agreement between two methods of clinical measurement (PDF), Lancet, 327, 307–310.
  • Bland J.M., Altman D.G., (1999), Measuring agreement in method comparison studies, Statistical Methods in Medical Research, 8, 135–160.
  • Canis B., (2015), Unmanned aircraft systems (UAS): Commercial outlook for a new industry, CRS Report: Congressional Res. Service, September 9.
  • Dalamagkidis K., (2015), Classification of UAVs. In: Handbook of Unmanned Aerial Vehicles, Valavanis K.P., Vachtsevanos G.J. (Eds.), Springer, Dordrecht, 83-91.
  • Ewertowski M.W., Tomczyk A.M., Evans D.J.A., Roberts D.H., Ewertowski W., (2019), Operational Framework for Rapid, Very-high Resolution Mapping of Glacial Geomorphology Using Low-cost Unmanned Aerial Vehicles and Structure-from-Motion Approach, Remote Sensing, 11, 1-18.
  • Makineci, H. B., (2023), Comparative accuracy analysis of DEMs generated from descending and ascending orbit TerraSAR-X data, Bulletin of Geophysics and Oceanography Vol. 64, n. 3, pp. 259-278., DOI 10.4430/bgo00427.
  • Makineci, H. B. (2022). İstanbul İli Merkez İlçelerindeki NO2 ve CO Emisyonlarının Uzaktan Algılama ve Yersel İstasyon Verileri Kullanılarak İncelenmesi . Türkiye Uzaktan Algılama Dergisi , 4 (2) , 62-74 . DOI: 10.51489/tuzal.1160333
  • 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 orthomosaics by UAV to support site-specific crop management, Remote Sens., 7, 12793–12814.
  • Hoffman-Wellenhof B., Lichtenegger H., Wasle E., (2008), GNSS - Global Navigation Satellite Systems, Springer, Austria.
  • Hugenholtz C.H., Whitehead K., Brown O.W., Barchyn T.E., Moorman B.J., LeClair A., Riddell K., Hamilton T., (2013), Geomorphological mapping with a small unmanned aircraft system (sUAS): Feature detection and accuracy assessment of a photogrammetrically-derived digital terrain model. Geomorphology, 194, 16-24.
  • Jin S., Cardellach E., Xie F., (2014), GNSS Remote Sensing, Springer, New York.
  • Koeva M., Muneza M., Gevaer, C., Gerke M., Nex F., (2018), Using UAVs for map creation and updating. A case study in Rwanda, Survey Review, 50, 312-325.
  • Lague D., Brodu N., Leroux J., (2013), Accurate 3D comparison of complex topography with terrestrial laser scanner: application to the Rangitikei canyon (N-Z), ISPRS J. Photogramm. Remote Sens, 82, 10–26.
  • Liu X.Y., (2008), Airborne LiDAR for DEM generation: some critical issues. Progress in Physical Geography, 32, 31-49.
  • Lucieer A., De Jong S.M., Turner D., (2014), Mapping landslide displacements using Structure from Motion (SfM) and image correlation of multi-temporal UAV photography, Prog. Phys. Geogr., 38, 97–116.
  • Uysal M., Toprak A.S., Polat N., (2015), DEM generation with UAV Photogrammetry and accuracy analysis in Sahitler hill, Measurement, 73, 539–543.
  • 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.
  • Nex F., Remondino F., (2014), UAV for 3D mapping applications: a review, Applied Geomatics, 6, 1-15.
  • Ottichilo W., Khamala E., (2002), Map updating using high resolution satelite imagery – A case of the kingdom of Swaziland, International Archives of Photogrammetry and Remote Sensing, 34, 89–92.
  • Otto A., Agatz N., Campbell J., Golden B., Pesch E., (2018), Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey. Networks, 72, 411-458.
  • Rawat K. S., Lawrence E. E., (2014), A mini-UAV VTOL Platform for Surveying Applications, International Journal of Robotics and Automation (IJRA), 3, 259-267.
  • Ruzgiene B., Berteska T., Gecyte S., Jakubauskiene E., Aksamitaukas V.C., (2015), The surface modelling based on UAV Photogrammetry and qualitative estimation, Measurement, 73, 619–627.
  • Samad A. M., Kamarulzaman N., Hamdani M. A., Mastor T. A., Hashim K. A., (2013), The Potential of Unmanned Aerial Vehicle (UAV) for Civilian and Mapping Application, 2013 IEEE 3rd International Conference on System Engineering and Technology, Shah Alam, Malaysia, 19 - 20 Aug. 2013.
  • Smith M.W., Carrivick J.L., Quincey D.J., (2016), Structure from motion photogrammetry in physical geography, Progress in Physical Geography, 40, 247-275.
  • Stöckl D., Rodríguez Cabaleiro D., Van Uytfanghe K., Thienpont L.M., (2004), Interpreting method comparison studies by use of the Bland-Altman plot: reflecting the importance of sample size by incorporating confidence limits and predefined error limits in the graphic, Clinical Chemistry, 50, 2216-2218.
  • Suziedelyte Visockiene J., Puziene R., Stanionis A., Tumeliene E., (2016), Unmanned Aerial Vehicles for Photogrammetry: Analysis of Orthophoto Images over the Territory of Lithuania, International Journal of Aerospace Engineering, 2016, 1-9.
  • Tonkin T.N., Midgley N.G., Graham D.J., Labadz J.C., (2014), The potential of small unmanned aircraft systems and structure-from-motion for topographic surveys: A test of emerging integrated approaches at Cwm Idwal, North Wales, Geomorphology, 226, 35-43.
  • Westoby M.J., Brasington J., Glasser N. F., Hambrey M. J., Reynolds J.M., (2012), Structure-from-Motion photogrammetry: A low-cost, effective tool for geoscience applications, Geomorphology, 179, 300-314.
  • Yildirim O., Susam T., Yaprak S., Delen A., Inyurt S., (2016), The Availability of UAV Systems for Agricultural Purposes, Journal of Agricultural Faculty of Gaziosmanpasa University, 33, 111-120.
There are 31 citations in total.

Details

Primary Language English
Subjects Photogrammetry and Remote Sensing
Journal Section Research Articles
Authors

Ömer Yıldırım 0000-0002-3537-6732

Cevat İnal 0000-0001-8980-2074

Sercan Bülbül 0000-0001-6066-611X

Burhaneddin Bilgen 0000-0002-1955-7568

Early Pub Date December 28, 2023
Publication Date December 30, 2023
Submission Date November 2, 2023
Acceptance Date December 5, 2023
Published in Issue Year 2023 Volume: 5 Issue: 2

Cite

APA Yıldırım, Ö., İnal, C., Bülbül, S., Bilgen, B. (2023). Investigation of Position Accuracy in UAVs. Türkiye Uzaktan Algılama Dergisi, 5(2), 89-96. https://doi.org/10.51489/tuzal.1385412
AMA Yıldırım Ö, İnal C, Bülbül S, Bilgen B. Investigation of Position Accuracy in UAVs. TUZAL. December 2023;5(2):89-96. doi:10.51489/tuzal.1385412
Chicago Yıldırım, Ömer, Cevat İnal, Sercan Bülbül, and Burhaneddin Bilgen. “Investigation of Position Accuracy in UAVs”. Türkiye Uzaktan Algılama Dergisi 5, no. 2 (December 2023): 89-96. https://doi.org/10.51489/tuzal.1385412.
EndNote Yıldırım Ö, İnal C, Bülbül S, Bilgen B (December 1, 2023) Investigation of Position Accuracy in UAVs. Türkiye Uzaktan Algılama Dergisi 5 2 89–96.
IEEE Ö. Yıldırım, C. İnal, S. Bülbül, and B. Bilgen, “Investigation of Position Accuracy in UAVs”, TUZAL, vol. 5, no. 2, pp. 89–96, 2023, doi: 10.51489/tuzal.1385412.
ISNAD Yıldırım, Ömer et al. “Investigation of Position Accuracy in UAVs”. Türkiye Uzaktan Algılama Dergisi 5/2 (December 2023), 89-96. https://doi.org/10.51489/tuzal.1385412.
JAMA Yıldırım Ö, İnal C, Bülbül S, Bilgen B. Investigation of Position Accuracy in UAVs. TUZAL. 2023;5:89–96.
MLA Yıldırım, Ömer et al. “Investigation of Position Accuracy in UAVs”. Türkiye Uzaktan Algılama Dergisi, vol. 5, no. 2, 2023, pp. 89-96, doi:10.51489/tuzal.1385412.
Vancouver Yıldırım Ö, İnal C, Bülbül S, Bilgen B. Investigation of Position Accuracy in UAVs. TUZAL. 2023;5(2):89-96.