Methodology of real-time 3D point cloud mapping with UAV lidar

Kacar, Elif; Candan, Levent

doi:10.26833/ijeg.1178260

Methodology of real-time 3D point cloud mapping with UAV lidar

Levent Candan, (Kocaeli Üniversitesi, Lazer Teknolojileri Araştırma ve Uygulama Merkezi, Kocaeli, Türkiye)

Elif Kacar (Kocaeli Üniversitesi, Fizik Bölümü, Kocaeli, Türkiye)

International Journal of Engineering and Geosciences

5 2

Yıl: 2023 Cilt: 8 Sayı: 3 Sayfa Aralığı: 301 - 309 Metin Dili: İngilizce DOI: 10.26833/ijeg.1178260 İndeks Tarihi: 03-07-2023

Methodology of real-time 3D point cloud mapping with UAV lidar

Öz:

Accurate and timely availability of LiDAR data is vital in some cases. To facilitate monitoring of any environmental changes, LiDAR systems can be designed, and carried by UAV platforms that can take off without major preparation. In this study, the methodology of the real-time LiDAR mapping system was developed in the laboratory. The designed system shortens the target-based flight planning and post-flight data processing. In this system, the data is taken instantly and thus the change in the mapping area can be detected quickly. The simulation system, produce 3D point cloud, and data was stored in a database for later analysis. The 3D visualization of the data obtained from our developed UAV-LiDAR system was carried out with a platform-independent interface designed as web-based. The X3D file format used in the study to produce 3D point data provide an infrastructure for AI and ML-based systems in identifying urban objects in systems containing big data such as LiDAR.

Anahtar Kelime: UAV LiDAR System 3D Point Cloud Remote Sensing X3D 3D Modeling Real-Time Mapping

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık

1. Toth, C., & Jóźków, G. (2016). Remote sensing platforms and sensors: A survey. ISPRS Journal of Photogrammetry and Remote Sensing, 115, 22-36. https://doi.org/10.1016/j.isprsjprs.2015.10.004
2. Lechner, A. M., Foody, G. M., & Boyd, D. S. (2020). Applications in remote sensing to forest ecology and management. One Earth, 2(5), 405-412. https://doi.org/10.1016/J.ONEEAR.2020.05.001
3. Levin, N., Kyba, C. C., Zhang, Q., de Miguel, A. S., Román, M. O., Li, X., ... & Elvidge, C. D. (2020). Remote sensing of night lights: A review and an outlook for the future. Remote Sensing of Environment, 237, 111443. https://doi.org/10.1016/J.RSE.2019.111443
4. Diaz, B. S., Mata-Zayas, E. E., Gama-Campillo, L. M., Rincon-Ramirez, J. A., Vidal-Garcia, F., Rullan-Silva, C. D., & Sanchez-Gutierrez, F. (2022). LiDAR modeling to determine the height of shade canopy tree in cocoa agrosystems as available habitat for wildlife. International Journal of Engineering and Geosciences, 7(3), 283-293. https://doi.org/10.26833/ijeg.978990
5. Sishodia, R. P., Ray, R. L., & Singh, S. K. (2020). Applications of remote sensing in precision agriculture: A review. Remote Sensing, 12(19), 3136. https://doi.org/10.3390/RS12193136
6. Ørka, H. O., Jutras-Perreault, M. C., Næsset, E., & Gobakken, T. (2022). A framework for a forest ecological base map–An example from Norway. Ecological Indicators, 136, 108636. https://doi.org/10.1016/j.ecolind.2022.108636
7. Calera, A., Campos, I., Osann, A., D’Urso, G., & Menenti, M. (2017). Remote sensing for crop water management: From ET modelling to services for the end users. Sensors, 17(5), 1104. https://doi.org/10.3390/S17051104
8. Jiang, D., & Wang, K. (2019). The role of satellite-based remote sensing in improving simulated streamflow: A review. Water, 11(8), 1615. https://doi.org/10.3390/W11081615
9. Keleş, M. D., & Aydın, C. C. (2020). Mobil Lidar Verisi ile Kent Ölçeğinde Cadde Bazlı Envanter Çalışması ve Coğrafi Sistemleri Entegrasyonu-Ankara Örneği. Geomatik, 5(3), 193-200. https://doi.org/10.29128/geomatik.643569
10. Awad, M. M. (2017). Toward robust segmentation results based on fusion methods for very high resolution optical image and lidar data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(5), 2067-2076. https://doi.org/10.1109/JSTARS.2017.2653061
11. Yao, H., Qin, R., & Chen, X. (2019). Unmanned aerial vehicle for remote sensing applications—A review. Remote Sensing, 11(12), 1443. https://doi.org/10.3390/rs11121443
12. Yang, B., & Chen, C. (2015). Automatic registration of UAV-borne sequent images and LiDAR data. ISPRS Journal of Photogrammetry and Remote Sensing, 101, 262-274. https://doi.org/10.1016/j.isprsjprs.2014.12.025
13. Li, J., Yang, B., Chen, C., & Habib, A. (2019). NRLI-UAV: Non-rigid registration of sequential raw laser scans and images for low-cost UAV LiDAR point cloud quality improvement. ISPRS Journal of Photogrammetry and Remote Sensing, 158, 123-145. https://doi.org/10.1016/j.isprsjprs.2019.10.009
14. Jiang, S., Jiang, W., Huang, W., & Yang, L. (2017). UAV- based oblique photogrammetry for outdoor data acquisition and offsite visual inspection of transmission line. Remote Sensing, 9(3), 278. https://doi.org/10.3390/rs9030278
15. Fuad, N. A., Ismail, Z., Majid, Z., Darwin, N., Ariff, M. F. M., Idris, K. M., & Yusoff, A. R. (2018, June). Accuracy evaluation of digital terrain model based on different flying altitudes and conditional of terrain using UAV LiDAR technology. In IOP conference series: earth and environmental science (Vol. 169, No. 1, p. 012100). IOP Publishing. https://doi.org/10.1088/1755- 1315/169/1/012100
16. Sofonia, J. J., Phinn, S., Roelfsema, C., Kendoul, F., & Rist, Y. (2019). Modelling the effects of fundamental UAV flight parameters on LiDAR point clouds to facilitate objectives-based planning. ISPRS journal of photogrammetry and remote sensing, 149, 105-118. https://doi.org/10.1016/j.isprsjprs.2019.01.020
17. Jiang, S., Jiang, C., & Jiang, W. (2020). Efficient structure from motion for large-scale UAV images: A review and a comparison of SfM tools. ISPRS Journal of Photogrammetry and Remote Sensing, 167, 230- 251. https://doi.org/10.1016/j.isprsjprs.2020.04.016
18. Awrangjeb, M. (2015). Effective generation and update of a building map database through automatic building change detection from LiDAR point cloud data. Remote Sensing, 7(10), 14119-14150. https://doi.org/10.3390/RS71014119
19. He, M., Zhu, Q., Du, Z., Hu, H., Ding, Y., & Chen, M. (2016). A 3D shape descriptor based on contour clusters for damaged roof detection using airborne LiDAR point clouds. Remote Sensing, 8(3), 189. https://doi.org/10.3390/rs8030189
20. Meng, X., Currit, N., & Zhao, K. (2010). Ground filtering algorithms for airborne LiDAR data: A review of critical issues. Remote Sensing, 2(3), 833-860. https://doi.org/10.3390/rs2030833
21. Tulldahl, H. M., Bissmarck, F., Larsson, H., Grönwall, C., & Tolt, G. (2015, October). Accuracy evaluation of 3D lidar data from small UAV. In Electro-Optical Remote Sensing, Photonic Technologies, and Applications IX (Vol. 9649, p. 964903). SPIE. https://doi.org/10.1117/12.2194508
22. Thiel, C., & Schmullius, C. (2017). Comparison of UAV photograph-based and airborne lidar-based point clouds over forest from a forestry application perspective. International Journal of Remote Sensing, 38(8-10), 2411-2426. https://doi.org/10.1080/01431161.2016.1225181
23. Zhou, S., & Wu, Z. (2013). Social Media Retrieval and Mining. IOP Conference Series: Earth and Environmental Science (Vol. 387). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-41629-3
24. Sun, Y., & Polys, N. (2020, November). The Scalability of X3D4 PointProperties: Benchmarks on WWW Performance. In The 25th International Conference on 3D Web Technology (pp. 1-8). https://doi.org/10.1145/3424616.3424707
25. Yoo, B., & Brutzman, D. (2009, June). X3D earth terrain-tile production chain for georeferenced simulation. In Proceedings of the 14th international conference on 3D Web technology (pp. 159-166). https://doi.org/10.1145/1559764.1559791
26. Han, S., Brutzman, D., Lee, J., Yoo, K. H., Marchetti, V., Mouton, C., ... & Jia, J. (Eds.). (2020). The 25th International Conference on 3D Web Technology. ACM.
27. Kim, J. S., Polys, N., & Sforza, P. (2015, June). Preparing and evaluating geospatial data models using X3D encodings for web 3D geovisualization services. In Proceedings of the 20th International Conference on 3D Web Technology (pp. 55-63). https://doi.org/10.1145/2775292.2775304

APA	Candan L, Kacar E (2023). Methodology of real-time 3D point cloud mapping with UAV lidar. , 301 - 309. 10.26833/ijeg.1178260
Chicago	Candan Levent,Kacar Elif Methodology of real-time 3D point cloud mapping with UAV lidar. (2023): 301 - 309. 10.26833/ijeg.1178260
MLA	Candan Levent,Kacar Elif Methodology of real-time 3D point cloud mapping with UAV lidar. , 2023, ss.301 - 309. 10.26833/ijeg.1178260
AMA	Candan L,Kacar E Methodology of real-time 3D point cloud mapping with UAV lidar. . 2023; 301 - 309. 10.26833/ijeg.1178260
Vancouver	Candan L,Kacar E Methodology of real-time 3D point cloud mapping with UAV lidar. . 2023; 301 - 309. 10.26833/ijeg.1178260
IEEE	Candan L,Kacar E "Methodology of real-time 3D point cloud mapping with UAV lidar." , ss.301 - 309, 2023. 10.26833/ijeg.1178260
ISNAD	Candan, Levent - Kacar, Elif. "Methodology of real-time 3D point cloud mapping with UAV lidar". (2023), 301-309. https://doi.org/10.26833/ijeg.1178260

APA	Candan L, Kacar E (2023). Methodology of real-time 3D point cloud mapping with UAV lidar. International Journal of Engineering and Geosciences, 8(3), 301 - 309. 10.26833/ijeg.1178260
Chicago	Candan Levent,Kacar Elif Methodology of real-time 3D point cloud mapping with UAV lidar. International Journal of Engineering and Geosciences 8, no.3 (2023): 301 - 309. 10.26833/ijeg.1178260
MLA	Candan Levent,Kacar Elif Methodology of real-time 3D point cloud mapping with UAV lidar. International Journal of Engineering and Geosciences, vol.8, no.3, 2023, ss.301 - 309. 10.26833/ijeg.1178260
AMA	Candan L,Kacar E Methodology of real-time 3D point cloud mapping with UAV lidar. International Journal of Engineering and Geosciences. 2023; 8(3): 301 - 309. 10.26833/ijeg.1178260
Vancouver	Candan L,Kacar E Methodology of real-time 3D point cloud mapping with UAV lidar. International Journal of Engineering and Geosciences. 2023; 8(3): 301 - 309. 10.26833/ijeg.1178260
IEEE	Candan L,Kacar E "Methodology of real-time 3D point cloud mapping with UAV lidar." International Journal of Engineering and Geosciences, 8, ss.301 - 309, 2023. 10.26833/ijeg.1178260
ISNAD	Candan, Levent - Kacar, Elif. "Methodology of real-time 3D point cloud mapping with UAV lidar". International Journal of Engineering and Geosciences 8/3 (2023), 301-309. https://doi.org/10.26833/ijeg.1178260