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Comparative Accuracy Analysis of Lidar Systems

Year 2020, Volume: 2 Issue: 2, 34 - 40, 24.12.2020

Abstract

The use of high-precision and sufficiently collected point clouds for 3D data modeling is very important for geomatics and other branches of engineering (such as mechanical and construction), and architectural applications. For this reason, various filtering and interpolation methods are improved for 3D modeling. However, if the point cloud is collected inaccurate or missing, the 3D data modeling is always an issue. Therefore, before the 3D modeling process, the point positioning accuracy and resolution of the point cloud should be investigated. For this purpose, accuracy assessment can be performed by comparing with data obtained from a measurement system that is considered to be more accurate. This comparison is used for the accuracy assessment of the maps produced by different Lidar (Light Detection and Ranging) point clouds. In this study, the accuracy of the point clouds obtained using Terrestrial Lidar Systems (TLS) and Mobile Lidar Systems (MLS) were determined. The reference measurements were obtained by Total Station (TS) surveys. Yılmaz Akdoruk Student Dormitory located in Ayazaga Campus of Istanbul Technical University was selected as a test-area in order to evaluate the TLS and MLS performance for applications in urban areas. The results showed that the accuracy of the TLS system was better than the MLS system. In addition, while TLS should be preferred in studies requiring high accuracy, such as 3D cultural heritage documentation, MLS may be preferred in applications such as various topographic maps and 3D city models. 

Thanks

“Koyuncu Lidar Harita ve Mühendislik” Company is acknowledged for providing the mobile mapping systems for this study. The point cloud data were processed by using CloudCompare Software and the statistics were obtained by using IBM SPSS Statistics 26 software. The authors appreciate both software. This article is the extended version of the proceeding that was presented at the 1st Intercontinental Geoinformation Days (IGD) on 25-26 November 2020 in Mersin, Turkey.

References

  • Bliss C. (1967). Analysis of fourfold tables. Statistics in biology, 1, 53-91.
  • Chen G, Weng Q, Hay G J & He Y (2018). Geographic object-based image analysis (GEOBIA): emerging trends and future opportunities. GIScience & Remote Sensing, 55 (2), 159-182.
  • Çelik M Ö, Hamal S N G & Yakar İ (2020). Yersel Lazer Tarama (YLT) Yönteminin Kültürel Mirasın Dokümantasyonunda Kullanımı: Alman Çeşmesi Örneği. Türkiye Lidar Dergisi, 2 (1), 15-22.
  • Fowler A & Kadatskiy V (2011). Accuracy and error assessment of terrestrial, mobile and airborne lidar. Paper presented at the Proceedings of American Society of Photogrammetry and Remote Sensing Conference (ASPRP 2011), 1–5 May 2011, Milwaukee, Wisconsin.
  • Haala N, Peter M, Kremer J & Hunter G (2008a). Mobile LiDAR mapping for 3D point cloud collection in urban areas—A performance test. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci, 37, 1119-1127.
  • Haala N, Peter M, Kremer J & Hunter G (2008b). Mobile LiDAR mapping for 3D point cloud collection in urban areas—A performance test. The international archives of the photogrammetry, remote sensing and spatial information sciences, 37 (Part B5).
  • IBM (International Business Machines) 2020 https://www.ibm.com/support/pages/ibm-spss-statistics-26-documentation. Date:16.11.2020.
  • Jing H, Meng X, Slatcher N & Hunter G (2020). Efficient point cloud corrections for mobile monitoring applications using road/rail-side infrastructure. Survey Review, 1-17.
  • Kuçak R, Kılıç F & Kısa A (2016). Analysis of terrestrial laser scanning and photogrammetry data for documentation of historical artifacts. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 155.
  • Kuçak R, Özdemir E & Erol S (2017). The segmentation of point clouds with k-means and ANN (artifical neural network). The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 595.
  • Kuçak R A, Kılıç F & Kısa A (2014). Analysis Of Various Data Collection Methods For Documentation Ofhistorical Artifacts. Paper presented at the 5. Remote Sensing-GIS Conference , İstanbul.
  • Kuçak R, Erol S & İşiler M (2020). The Accuracy Assessment of Terrestrial and Mobile Lidar Systems for 3D Modelling. Proceedings book of the 1st Intercontinental Geoinformation Days (IGD) Symposium, Mersin, Mersin, Turkey.
  • Rieger P, Studnicka N, Pfennigbauer M & Zach G (2010). Boresight alignment method for mobile laser scanning systems. Journal of Applied Geodesy, 4 (1), 13-21.
  • Rodríguez-Gonzálvez P, Jimenez Fernandez-Palacios B, Muñoz-Nieto Á L, Arias-Sanchez P & Gonzalez-Aguilera D (2017). Mobile LiDAR system: New possibilities for the documentation and dissemination of large cultural heritage sites. Remote Sensing, 9 (3), 189.
  • Rusu R B, Marton Z C, Blodow N, Dolha M & Beetz M (2008). Towards 3D point cloud based object maps for household environments. Robotics and Autonomous Systems, 56 (11), 927-941.
  • Scaioni M (2005). Direct georeferencing of TLS in surveying of complex sites. Proceedings of the ISPRS Working Group, 4, 22-24.
  • Toschi I, Rodríguez-Gonzálvez P, Remondino F, Minto S, Orlandini S & Fuller A (2015). Accuracy evaluation of a mobile mapping system with advanced statistical methods. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40 (5), 245.
  • Wang Y, Chen Q, Zhu Q, Liu L, Li C & Zheng D (2019). A survey of mobile laser scanning applications and key techniques over urban areas. Remote Sensing, 11 (13), 1540.
  • Wright D B & Herrington J A (2011). Problematic standard errors and confidence intervals for skewness and kurtosis. Behavior Research Methods, 43 (1), 8-17.

Lidar Sistemlerinin Karşılaştırmalı Doğruluk Analizi

Year 2020, Volume: 2 Issue: 2, 34 - 40, 24.12.2020

Abstract

3B veri modellemesi için yüksek hassasiyetli ve yeterli miktardaki nokta bulutlarının kullanılması, Geomatik ve diğer mühendislik dalları (makine ve inşaat gibi) ve mimari uygulamalar için çok önemlidir. Bu nedenle, 3B modelleme için çeşitli filtreleme ve enterpolasyon yöntemleri geliştirilmiştir. Bunun yanında, nokta bulutunun yanlış veya eksik elde edilmesi, 3B veri modelleme için her zaman bir sorundur. Bu amaçla, 3 boyutlu modelleme işlemine geçilmeden önce nokta bulutunun çözünürlüğü ve nokta konumlandırma doğruluğu araştırılmalıdır. Bu amaçla, doğruluk değerlendirmesi, daha doğru olduğu düşünülen bir ölçüm sisteminden elde edilen veriler ile karşılaştırılma yapılarak gerçekleştirilebilir. Bu şekilde bir karşılaştırma, farklı Lidar (Light Detection and Ranging) nokta bulutlarından üretilen ölçülerin doğruluk değerlendirmesinde kullanılır. Bu çalışmada, Yersel Lidar Sistemleri (YLS) ve Mobil Lidar Sistemleri (MLS) kullanılarak elde edilen nokta bulutlarının doğruluğu belirlenmiştir. Referans ölçümler Total Station (TS) ile elde edilmiştir. İstanbul Teknik Üniversitesi Ayazağa Yerleşkesinde bulunan Yılmaz Akdoruk Öğrenci Yurdu, kentsel alanlardaki 3D model uygulamalarında YLS ve MLS performansını değerlendirmek amacıyla test alanı olarak seçilmiştir. Sonuçlar, TLS sisteminin doğruluğunun MLS sisteminden daha iyi olduğunu göstermiştir. Buna bağlı olarak 3 boyutlu kültürel miras dokümantasyonu gibi yüksek doğruluk gerektiren çalışmalarda YLS tercih edilirken, çeşitli topoğrafik haritalar ve 3 boyutlu şehir modelleri gibi uygulamalarda MLS tercih edilebilir.

References

  • Bliss C. (1967). Analysis of fourfold tables. Statistics in biology, 1, 53-91.
  • Chen G, Weng Q, Hay G J & He Y (2018). Geographic object-based image analysis (GEOBIA): emerging trends and future opportunities. GIScience & Remote Sensing, 55 (2), 159-182.
  • Çelik M Ö, Hamal S N G & Yakar İ (2020). Yersel Lazer Tarama (YLT) Yönteminin Kültürel Mirasın Dokümantasyonunda Kullanımı: Alman Çeşmesi Örneği. Türkiye Lidar Dergisi, 2 (1), 15-22.
  • Fowler A & Kadatskiy V (2011). Accuracy and error assessment of terrestrial, mobile and airborne lidar. Paper presented at the Proceedings of American Society of Photogrammetry and Remote Sensing Conference (ASPRP 2011), 1–5 May 2011, Milwaukee, Wisconsin.
  • Haala N, Peter M, Kremer J & Hunter G (2008a). Mobile LiDAR mapping for 3D point cloud collection in urban areas—A performance test. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci, 37, 1119-1127.
  • Haala N, Peter M, Kremer J & Hunter G (2008b). Mobile LiDAR mapping for 3D point cloud collection in urban areas—A performance test. The international archives of the photogrammetry, remote sensing and spatial information sciences, 37 (Part B5).
  • IBM (International Business Machines) 2020 https://www.ibm.com/support/pages/ibm-spss-statistics-26-documentation. Date:16.11.2020.
  • Jing H, Meng X, Slatcher N & Hunter G (2020). Efficient point cloud corrections for mobile monitoring applications using road/rail-side infrastructure. Survey Review, 1-17.
  • Kuçak R, Kılıç F & Kısa A (2016). Analysis of terrestrial laser scanning and photogrammetry data for documentation of historical artifacts. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 155.
  • Kuçak R, Özdemir E & Erol S (2017). The segmentation of point clouds with k-means and ANN (artifical neural network). The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 595.
  • Kuçak R A, Kılıç F & Kısa A (2014). Analysis Of Various Data Collection Methods For Documentation Ofhistorical Artifacts. Paper presented at the 5. Remote Sensing-GIS Conference , İstanbul.
  • Kuçak R, Erol S & İşiler M (2020). The Accuracy Assessment of Terrestrial and Mobile Lidar Systems for 3D Modelling. Proceedings book of the 1st Intercontinental Geoinformation Days (IGD) Symposium, Mersin, Mersin, Turkey.
  • Rieger P, Studnicka N, Pfennigbauer M & Zach G (2010). Boresight alignment method for mobile laser scanning systems. Journal of Applied Geodesy, 4 (1), 13-21.
  • Rodríguez-Gonzálvez P, Jimenez Fernandez-Palacios B, Muñoz-Nieto Á L, Arias-Sanchez P & Gonzalez-Aguilera D (2017). Mobile LiDAR system: New possibilities for the documentation and dissemination of large cultural heritage sites. Remote Sensing, 9 (3), 189.
  • Rusu R B, Marton Z C, Blodow N, Dolha M & Beetz M (2008). Towards 3D point cloud based object maps for household environments. Robotics and Autonomous Systems, 56 (11), 927-941.
  • Scaioni M (2005). Direct georeferencing of TLS in surveying of complex sites. Proceedings of the ISPRS Working Group, 4, 22-24.
  • Toschi I, Rodríguez-Gonzálvez P, Remondino F, Minto S, Orlandini S & Fuller A (2015). Accuracy evaluation of a mobile mapping system with advanced statistical methods. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40 (5), 245.
  • Wang Y, Chen Q, Zhu Q, Liu L, Li C & Zheng D (2019). A survey of mobile laser scanning applications and key techniques over urban areas. Remote Sensing, 11 (13), 1540.
  • Wright D B & Herrington J A (2011). Problematic standard errors and confidence intervals for skewness and kurtosis. Behavior Research Methods, 43 (1), 8-17.
There are 19 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Ramazan Alper Kuçak 0000-0002-1128-1552

Serdar Erol 0000-0002-7100-8267

Mehmet İşiler 0000-0003-0543-0029

Publication Date December 24, 2020
Submission Date November 17, 2020
Published in Issue Year 2020 Volume: 2 Issue: 2

Cite

APA Kuçak, R. A., Erol, S., & İşiler, M. (2020). Comparative Accuracy Analysis of Lidar Systems. Türkiye Lidar Dergisi, 2(2), 34-40.

Türkiye LiDAR Dergisi