Vol. 4 No. 1 (2024)
Articles

Comprehensive Study on Enhanced Accuracy Analysis of LIDAR Data : The Example of Skopje

BERKAN SARITAŞ
Eskisehir techinical University

Published 2024-03-31

Keywords

  • Remote sensing,
  • CSF Filter,
  • DTM,
  • LIDAR,
  • Accuracy analysis

How to Cite

SARITAŞ, B., & KAPLAN, G. (2024). Comprehensive Study on Enhanced Accuracy Analysis of LIDAR Data : The Example of Skopje. Advanced LiDAR, 4(1), 09–18. Retrieved from https://publish.mersin.edu.tr/index.php/lidar/article/view/1361

Abstract

By harnessing LIDAR technology, a prominent remote sensing method widely employed today, we explore its efficacy as a rapid and dependable tool for data collection. We focus on generating a numerical terrain model by leveraging the CSF Filter algorithm within the accessible CloudCompare software to filter an urban LIDAR point cloud. This study involves meticulous manual intervention to eliminate noise points, followed by examining the creation of a numerical terrain model by varying cover values (0.1, 0.5, 1, 2, and 5) in the CSF Filter algorithm. Our investigation delves into calculating the volume disparity between a reference model meticulously crafted within a computer environment, integrating manual interventions, and models derived through the CSF Filter algorithm. This approach aims to identify the cover value that best approximates reality in filtering operations. The decryption of volume disparities between the computer-generated reference model and the CSF Filter algorithm sheds light on the most accurate filtering outcome. The results indicates that opting for a cover value of 5 yields the most significant divergence from the reference model, presenting a less accurate model. Conversely, selecting a cover value of 0.5 as input data offers the closest approximation to the truth. However, it remains evident that manual interventions are indispensable for refining filtering operations even in the most precise model derived from these investigations.

References

  1. Adjiski, V., Kaplan, G. & Mijalkovski, S. (2023). Assessment of the solar energy potential of rooftops using LIDAR datasets and GIS based approach. International Journal of Engineering and Geosciences, 8(2), 188-199.
  2. Akgül, M., Yurtseven, H., Demir, M., Akay, A. E., Gülci, S., & Öztürk, T. (2016). İnsansız hava araçları ile yüksek hassasiyette sayısal yükseklik modeli üretimi ve ormancılıkta kullanım olanakları. İstanbul Üniversitesi Orman Fakültesi Dergisi, 66(1). https://doi.org/10.17099/jffiu.23976
  3. Başambar, Ş., Karimi, Z. K., Öztürk, F., Acet, Ş. B., & Pekkan, Ö. I. (2021). Uzaktan Algılama Tekniklerinden Yararlanarak Tarımsal Faaliyetlerin İzlenmesi. GSI Journals Serie C: Advancements in Information Sciences and Technologies , 4(2), 58–79.
  4. Civelekoğlu, B. (2015). Hava Lidar Verilerinin Sınıflandırılması Ve Orman Ağaçlarına Ait Öznitelik Değerlendirilmesi İstanbul Belgrad Ormanı Örneği [Yüksek Lisans Tezi]. Yıldız Teknik Üniversitesi.
  5. Çakmak, Z. B., Akpinar, B., & Selbesoğlu, M. O. (2022). Taşınabilir Lazer Tarama Sistemleri ile Farklı Alanlarda Doğruluk Analizi. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, 22(5), 1075–1086. https://doi.org/10.35414/AKUFEMUBID.1139569
  6. Çelik, H., Baş, N., & Coşkun, H. G. (2014). Taşkın Modelleme ve Risk Analizinde LiDAR Verisiyle Sayısal Yükseklik Modeli Üretimi. Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 4(1), 117. https://doi.org/10.17714/GUFBED.2014.04.009
  7. Çömert, R., Avdan, U., Tün, M., & Ersoy, M. (2012). Mimari Belgelemede Yersel Lazer Tarama Yönteminin Uygulanması (Seyitgazi Askerlik Şubesi Örneği). Harita Teknolojileri Elektronik Dergisi, 4(1), 1–18. www.teknolojikarastirmalar.com
  8. Döş, M. E., & Uysal, M. (2019). Uzaktan algılama verilerinin derin öğrenme algoritmaları ile sınıflandırılması. Türkiye Uzaktan Algılama Dergisi, 1(1), 28–34. https://dergipark.org.tr/tr/pub/tuzal/issue/50531/648988
  9. Ekercin, S., & Üstün, B. (2004). Uzaktan algılamada yeni bir teknoloji: Lidar. HKM Jeodezi Jeoinformasyon Arazi Yönetimi Dergisi, 0(91), 34–38. http://search/yayin/detay/59216
  10. Fabris, M., Achilli, V., Artese, G., Boatto, G., Bragagnolo, D., Concheri, G., Meneghello, R., Menin, A., & Trecroci, A. (2009). High Resolution Data From Laser Scanning and Digıtal Photogrammetry Terrestrial Methodologies Test Site: An Architectural Surface. ISPRS, 38(3/W8), 43–48.
  11. Fidan, D., & Fidan, Ş. (2021). Yersel lazer tarama teknolojileriyle oluşturulan 3B modellerin akıllı kent uygulamalarında kullanımı: Mersin Süslü Çeşme örneği. Türkiye LIDAR Dergisi, 3(2), 48–57. https://doi.org/10.51946/melid.1021819
  12. Habib, A., & Rens, J. V. (2017). Quality Assurance and Quality Control of Lidar Systems and Derived Data. Advanced Lidar Workshop, University of Northern Iowa, 10, 269–294. https://doi.org/10.1201/9781420051438.CH9
  13. Kaplan, G., Comert, R., Kaplan, O., Matci, D. K., & Avdan, U. (2022). Using Machine Learning to Extract Building Inventory Information Based on LIDAR Data. ISPRS International Journal of Geo-Information, 11(10). https://doi.org/10.3390/IJGI11100517
  14. Karasaka, L., & Keleş, H. (2020). CSF (Cloth simulation filtering) Algoritmasının Zemin Noktalarını Filtrelemedeki Performans Analizi. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 267–275. https://doi.org/10.35414/akufemubid.660828
  15. Kostrikov, S. (2019). Urban remote sensing with lidar for the Smart City Concept implementation. Visnyk of V. N. Karazin Kharkiv National University, Series ‘Geology. Geography. Ecology’, 50. https://doi.org/10.26565/2410-7360-2019-50-08
  16. Liu, X. (2008). Airborne LIDAR for DEM generation: some critical issues. Http://Dx.Doi.Org/10.1177/0309133308089496, 32(1), 31–49. https://doi.org/10.1177/0309133308089496
  17. Lu, Y., Wang, X., Zhou, K., & Yang, J. (2011). MATLAB Tools for LIDAR Data Conversion, Visualization, and Processing. In X. He, J. Xu, & V. G. Ferreira (Eds.), International Symposium on LIDAR and Radar Mapping 2011: Technologies and Applications. https://doi.org/10.1117/12.912529
  18. Makineci, H. B. (2016). İnsansız Hava Araçları Lidar Etkileşimi. Geomatik, 1(1), 19–23. https://doi.org/10.29128/geomatik.294076
  19. Podobnikar, T., & Vrečko, A. (2012). Digital Elevation Model from the Best Results of Different Filtering of a LiDAR Point Cloud. Transactions in GIS, 16(5), 603–617. https://doi.org/10.1111/J.1467-9671.2012.01335.X
  20. Sarıtaş, B. & Kaplan, G. (2023). Enhancing Ground Point Extraction in Airborne LiDAR Point Cloud Data Using the CSF Filter Algorithm. Advanced LiDAR, 3(2), 53-61.
  21. Sevinç Tigin, Ö. (2023). Investigation of Technological Developments in Remote Sensing And Geographical Information Systems With Patent Statistics. GSI Journals Serie C: Advancements in Information Sciences and Technologies, 6(2), 20–30.
  22. Soycan, M., Tunalioǧlu, N., Öcalan, T., Soycan, A., & Gümüş, K. (2011b). Three Dimensional Modeling of a Forested Area Using an Airborne Light Detection and Ranging Method. Arabian Journal for Science and Engineering, 36(4), 581–595. https://doi.org/10.1007/S13369-011-0054-8/METRICS
  23. Uça Avcı, Z. D., Uça Güneş, E. P., & Çabuk, A. (2015). An Evaluation of ‘Remote Sensing’ and ‘Geographic Information Systems’ Training in Distance Education. Harita Teknolojileri Elektronik Dergisi, 7(3), 53–68. https://doi.org/10.15659/hartek.15.11.90
  24. Uray, F. (2016). Hava LIDAR Nokta Bulutu Verileri Fİltreleme Algoritmalarının Geliştirilmesi ve Performanslarının Karşılaştırılması [Yüksek Lisans Tezi]. Necmettin Erbakan Üniversitesi.
  25. Uray, F. (2022). Derin öğrenme tekniklerini kullanarak hava LIDAR nokta bulutlarının sınıflandırılması [Doktora Tezi]. Necmettin Erbakan Üniversitesi.https://doi.org/10.1515/geo-2019-0038
  26. URL-1: en.wikipedia.org (2023). (Date of Access:14.08.2023) https://en.wikipedia.org/wiki/CloudCompare
  27. URL-2: cloudcompare.org (2023). (Date of Access:14.08.2023) https://www.cloudcompare.org/doc/wiki/index.php/Introduction
  28. URL-3: autodesk.com (2023). (Date of Access:14.08.2023) https://www.autodesk.com/products/recap/overview?term=1-YEAR&tab=subscription&plc=RECAP
  29. URL-4: autodesk.com (2023). (Date of Access:14.08.2023) https://www.autodesk.com.tr/products/civil-3d/overview
  30. URL-5: penta.com.tr (2023). (Date of Access:14.08.2023) https://www.penta.com.tr/markalar/autodesk/urunler/autocad-civil-3d/autocad-civil-3d-nedir-/en/
  31. URL-6: penta.com.tr (2023). (Date of Access:14.08.2023) https://www.penta.com.tr/markalar/autodesk/urunler/autocad-civil-3d/ayrintili-bilgi/en/
  32. URL-7: earth.google.com (2023). (Date of Access:18.07.2023) https://earth.google.com/web/search/Partizanski+Odredi+87,+Boulevard+Partizanski+Odredi,+%c3%9csk%c3%bcp,+Kuzey+Makedonya/@42.00585824,21.3618348,265.50010264a,2966.21743366d,35y,178.08009325h,0t,0r/data=CigiJgokCXBCgJB73ERAEb4DjSnX2kRAGaAp-XmozDVAIdb_99uWwzVAOgMKATA
  33. Wehr, A., & Lohr, U. (1999). Airborne laser scanning - An introduction and overview. ISPRS Journal of Photogrammetry and Remote Sensing, 54(2–3), 68–82. https://doi.org/10.1016/S0924-2716(99)00011-8
  34. Yurtsever, A. (2023). Taşınır ve taşınmaz kültür varlıklarının yeni nesil LiDAR sensörlü tablet bilgisayar ile belgelenmesi. Geomatik, 8(2), 200–207. https://doi.org/10.29128/geomatik.1209701