Araştırma Makalesi
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Fark SYM ve 3B nokta bulutu karşılaştırma yöntemlerinin doğruluklarının incelenmesi: Açık maden ocağı örneği

Yıl 2024, Cilt: 11 Sayı: 1, 41 - 50, 03.05.2024
https://doi.org/10.9733/JGG.2024R0004.E

Öz

İnsansız hava araçlarının (İHA) yaygınlaşmasıyla birlikte düşük maliyetli basit sistemlerle küçük alanlar üzerinde yüksek doğruluklu fotogrametrik haritalama çalışmaları yapılabilmektedir. Farklı zamanlarda elde edilen görüntüler karşılaştırılarak 3 Boyutlu (3B) değişim tespit çalışmaları da kolaylıkla gerçekleştirilebilmektedir. Fotogrametrik değerlendirme yazılımları ile elde edilen nokta bulutundan sayısal yüzey modelleri (SYM) elde edilir, farkları alınır ve zamansal değişimler modellenebilir. Bu yöntem pratikte Fark SYM yöntemi olarak bilinir ve düşük hesaplama maliyetine sahiptir. Son zamanlarda, büyük veri işleyebilen güçlü bilgisayarların gelişmesi ve bunlara erişimin düşük maliyetlerle mümkün olması neticesinde 3B değişim tespit çalışmaları ham nokta bulutundan SYM elde edilmeksizin doğrudan noktaların kendisiyle yapılabilmektedir. Metodolojik olarak, Fark SYM ve nokta bulutu tabanlı analiz stratejilerinin farklı değerlendirme aşamaları ve çıktıları vardır. Fark SYM ile sadece düşey yöndeki değişimler ortaya çıkarılabilirken, ham nokta bulutu karşılaştırma yöntemleri 3B değişim vektörünü hesaplayabilmektedir. Bu çalışmada, pratikte sıklıkla kullanılan Fark SYM yöntemi ile 3B nokta bulutu karşılaştırma yöntemlerinden biri olan M3C2 karşılaştırılmıştır. Yöntemlerin doğruluğu, yoğun kazı çalışmalarının yapıldığı aktif bir açık ocak maden sahasında test edilmiştir. Ortalama yer örnekleme aralığı 5.8-6.9 cm olan İHA görüntülerinden elde edilen M3C2 uzunluk ve DoD farklarıyla 11 cm'den düşük standart sapma değerleri bulunmuştur. Farkların sadece %1 civarındaki kesimi uyuşumsuz olarak ortaya çıkmıştır.

Kaynakça

  • Besl, P. J., & McKay, N. D. (1992). A method for registration of 3-D shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(2), 239-256.
  • Cao, D., Zhang, B., Zhang, X., Yin, L., & Man, X. (2023). Optimization methods on dynamic monitoring of mineral reserves for open pit mine based on UAV oblique photogrammetry. Measurement, 207, 112364.
  • Cook, K. L. (2017). An evaluation of the effectiveness of low-cost UAVs and structure from motion for geomorphic change detection. Geomorphology, 278, 195-208.
  • de Gélis, I., Lefèvre, S., & Corpetti, T. (2021). Change detection in urban point clouds: An experimental comparison with simulated 3d datasets. Remote Sensing, 13(13), 2629.
  • James, M. R., Robson, S., & Smith, M. W. (2017). 3‐D uncertainty‐based topographic change detection with structure‐from‐motion photogrammetry: precision maps for ground control and directly georeferenced surveys. Earth Surface Processes and Landforms, 42(12), 1769-1788.
  • Kharroubi, A., Poux, F., Ballouch, Z., Hajji, R., & Billen, R. (2022). Three dimensional change detection using point clouds: A review. Geomatics, 2(4), 457-485.
  • Lague, D., Brodu, N., & Leroux, J. (2013). Accurate 3D comparison of complex topography with terrestrial laser scanner: Application to the Rangitikei canyon (NZ). ISPRS journal of photogrammetry and remote sensing, 82, 10-26.
  • Li, P., Li, D., Hu, J., Fassnacht, F. E., Latifi, H., Yao, W., Gao, J., Chan, F.K.S., Dang, T., & Tang, F. (2024). Improving the application of UAV-LiDAR for erosion monitoring through accounting for uncertainty in DEM of difference. Catena, 234, 107534.
  • Liu, X., Zhu, W., Lian, X., & Xu, X. (2023). Monitoring mining surface subsidence with multi-temporal three-dimensional unmanned aerial vehicle point cloud. Remote Sensing, 15(2), 374.
  • Nex, F., Armenakis, C., Cramer, M., Cucci, D. A., Gerke, M., Honkavaara, E., Kukko, A., Persello, C., & Skaloud, J. (2022). UAV in the advent of the twenties: Where we stand and what is next. ISPRS journal of photogrammetry and remote sensing, 184, 215-242.
  • Nourbakhshbeidokhti, S., Kinoshita, A. M., Chin, A., & Florsheim, J. L. (2019). A workflow to estimate topographic and volumetric changes and errors in channel sedimentation after disturbance. Remote Sensing, 11(5), 586.
  • Okyay, U., Telling, J., Glennie, C. L., & Dietrich, W. E. (2019). Airborne lidar change detection: An overview of Earth sciences applications. Earth-Science Reviews, 198, 102929.
  • Ren, H., Zhao, Y., Xiao, W., & Hu, Z. (2019). A review of UAV monitoring in mining areas: Current status and future perspectives. International Journal of Coal Science & Technology, 6, 320-333.
  • Théau, J. (2022). Change detection. Kresse, W., & Danko, D. (ed) Springer Handbook of Geographic Information, Springer International Publishing.
  • Williams, R. (2012). DEMs of difference. Geomorphological Techniques, 2(3.2).
  • Wilson, J. P. (2012). Digital terrain modeling. Geomorphology, 137(1), 107-121.
  • URL-1: CloudCompare (version 2.12.4) [GPL software], http://www.cloudcompare.org/ (Accessed: 25 December 2023).

Examining the accuracy of DEM of difference and 3D point cloud comparison methods: Open pit mine case study

Yıl 2024, Cilt: 11 Sayı: 1, 41 - 50, 03.05.2024
https://doi.org/10.9733/JGG.2024R0004.E

Öz

With the widespread use of unmanned aerial vehicles (UAV), high-accuracy photogrammetric mapping studies can be carried out over small areas with cost-effective simple systems. By comparing images obtained at different epochs, 3 Dimensional (3D) change detection studies can be easily performed. Digital surface models (DSM) are obtained from the point cloud (PC) with the processing software, their differences are taken, and temporal changes can thus be modeled. This method is known as DEM (DSM) of Difference (DoD) in practice and has low computational cost. Recently, with the availability and accessibility of powerful computers capable of processing increasing amounts of data, 3D change detection studies can be performed directly with raw PCs without converting them to DSM. Methodologically, DoD and PC-based analysis strategies have different evaluation stages and outputs. With DoD, only changes in the vertical direction can be revealed, while PC comparison methods can produce the 3D change vector. In this study, the well-established DoD method and Multiscale Model-to-Model Cloud Comparison (M3C2), one of the 3D PC comparison methods, were compared. The accuracy of the methods was tested at an active open pit mine site where intensive excavation works have been undertaken. Standard deviation values were found below 11 cm with M3C2 distance and DoD differences obtained from UAV images having average ground sampling distances (GSD) of 5.8-6.9 cm. Only about 1% of the differences were categorized as outliers.

Teşekkür

We would like to express our sincere gratitude to FİDES Mühendislik for providing access to the UAV images used in this research.

Kaynakça

  • Besl, P. J., & McKay, N. D. (1992). A method for registration of 3-D shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(2), 239-256.
  • Cao, D., Zhang, B., Zhang, X., Yin, L., & Man, X. (2023). Optimization methods on dynamic monitoring of mineral reserves for open pit mine based on UAV oblique photogrammetry. Measurement, 207, 112364.
  • Cook, K. L. (2017). An evaluation of the effectiveness of low-cost UAVs and structure from motion for geomorphic change detection. Geomorphology, 278, 195-208.
  • de Gélis, I., Lefèvre, S., & Corpetti, T. (2021). Change detection in urban point clouds: An experimental comparison with simulated 3d datasets. Remote Sensing, 13(13), 2629.
  • James, M. R., Robson, S., & Smith, M. W. (2017). 3‐D uncertainty‐based topographic change detection with structure‐from‐motion photogrammetry: precision maps for ground control and directly georeferenced surveys. Earth Surface Processes and Landforms, 42(12), 1769-1788.
  • Kharroubi, A., Poux, F., Ballouch, Z., Hajji, R., & Billen, R. (2022). Three dimensional change detection using point clouds: A review. Geomatics, 2(4), 457-485.
  • Lague, D., Brodu, N., & Leroux, J. (2013). Accurate 3D comparison of complex topography with terrestrial laser scanner: Application to the Rangitikei canyon (NZ). ISPRS journal of photogrammetry and remote sensing, 82, 10-26.
  • Li, P., Li, D., Hu, J., Fassnacht, F. E., Latifi, H., Yao, W., Gao, J., Chan, F.K.S., Dang, T., & Tang, F. (2024). Improving the application of UAV-LiDAR for erosion monitoring through accounting for uncertainty in DEM of difference. Catena, 234, 107534.
  • Liu, X., Zhu, W., Lian, X., & Xu, X. (2023). Monitoring mining surface subsidence with multi-temporal three-dimensional unmanned aerial vehicle point cloud. Remote Sensing, 15(2), 374.
  • Nex, F., Armenakis, C., Cramer, M., Cucci, D. A., Gerke, M., Honkavaara, E., Kukko, A., Persello, C., & Skaloud, J. (2022). UAV in the advent of the twenties: Where we stand and what is next. ISPRS journal of photogrammetry and remote sensing, 184, 215-242.
  • Nourbakhshbeidokhti, S., Kinoshita, A. M., Chin, A., & Florsheim, J. L. (2019). A workflow to estimate topographic and volumetric changes and errors in channel sedimentation after disturbance. Remote Sensing, 11(5), 586.
  • Okyay, U., Telling, J., Glennie, C. L., & Dietrich, W. E. (2019). Airborne lidar change detection: An overview of Earth sciences applications. Earth-Science Reviews, 198, 102929.
  • Ren, H., Zhao, Y., Xiao, W., & Hu, Z. (2019). A review of UAV monitoring in mining areas: Current status and future perspectives. International Journal of Coal Science & Technology, 6, 320-333.
  • Théau, J. (2022). Change detection. Kresse, W., & Danko, D. (ed) Springer Handbook of Geographic Information, Springer International Publishing.
  • Williams, R. (2012). DEMs of difference. Geomorphological Techniques, 2(3.2).
  • Wilson, J. P. (2012). Digital terrain modeling. Geomorphology, 137(1), 107-121.
  • URL-1: CloudCompare (version 2.12.4) [GPL software], http://www.cloudcompare.org/ (Accessed: 25 December 2023).
Toplam 17 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Fotogrametri
Bölüm Araştırma Makalesi
Yazarlar

Nilüfer Özdaş 0009-0007-3929-6813

Mehmet Güven Koçak 0000-0002-7992-5860

Serkan Karakış 0000-0002-5765-7666

Erken Görünüm Tarihi 3 Nisan 2024
Yayımlanma Tarihi 3 Mayıs 2024
Gönderilme Tarihi 15 Ocak 2024
Kabul Tarihi 28 Şubat 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 11 Sayı: 1

Kaynak Göster

APA Özdaş, N., Koçak, M. G., & Karakış, S. (2024). Examining the accuracy of DEM of difference and 3D point cloud comparison methods: Open pit mine case study. Jeodezi Ve Jeoinformasyon Dergisi, 11(1), 41-50. https://doi.org/10.9733/JGG.2024R0004.E
AMA Özdaş N, Koçak MG, Karakış S. Examining the accuracy of DEM of difference and 3D point cloud comparison methods: Open pit mine case study. hkmojjd. Mayıs 2024;11(1):41-50. doi:10.9733/JGG.2024R0004.E
Chicago Özdaş, Nilüfer, Mehmet Güven Koçak, ve Serkan Karakış. “Examining the Accuracy of DEM of Difference and 3D Point Cloud Comparison Methods: Open Pit Mine Case Study”. Jeodezi Ve Jeoinformasyon Dergisi 11, sy. 1 (Mayıs 2024): 41-50. https://doi.org/10.9733/JGG.2024R0004.E.
EndNote Özdaş N, Koçak MG, Karakış S (01 Mayıs 2024) Examining the accuracy of DEM of difference and 3D point cloud comparison methods: Open pit mine case study. Jeodezi ve Jeoinformasyon Dergisi 11 1 41–50.
IEEE N. Özdaş, M. G. Koçak, ve S. Karakış, “Examining the accuracy of DEM of difference and 3D point cloud comparison methods: Open pit mine case study”, hkmojjd, c. 11, sy. 1, ss. 41–50, 2024, doi: 10.9733/JGG.2024R0004.E.
ISNAD Özdaş, Nilüfer vd. “Examining the Accuracy of DEM of Difference and 3D Point Cloud Comparison Methods: Open Pit Mine Case Study”. Jeodezi ve Jeoinformasyon Dergisi 11/1 (Mayıs 2024), 41-50. https://doi.org/10.9733/JGG.2024R0004.E.
JAMA Özdaş N, Koçak MG, Karakış S. Examining the accuracy of DEM of difference and 3D point cloud comparison methods: Open pit mine case study. hkmojjd. 2024;11:41–50.
MLA Özdaş, Nilüfer vd. “Examining the Accuracy of DEM of Difference and 3D Point Cloud Comparison Methods: Open Pit Mine Case Study”. Jeodezi Ve Jeoinformasyon Dergisi, c. 11, sy. 1, 2024, ss. 41-50, doi:10.9733/JGG.2024R0004.E.
Vancouver Özdaş N, Koçak MG, Karakış S. Examining the accuracy of DEM of difference and 3D point cloud comparison methods: Open pit mine case study. hkmojjd. 2024;11(1):41-50.