Skip to main content

Registration of Multi-scan Forest Terrestrial Laser Scanning Data Integrated with Smartphone

  • Conference paper
  • First Online:
  • 501 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12473))

Abstract

Terrestrial laser scanning (TLS) is an important technique to obtain the side view data under the forest canopy and the registration of TLS data captured from different positions is an important step to obtain a complete forest dataset. As commonly used TLS data registration methods are not suitable for the forest scene, this paper presents a registration method of forest TLS data based on orienting and positioning data of smartphone. The coarse transformation parameters between two scans are calculated based on the initial scanner direction and position of each scan, and then used as the input of the Iterative Closest Point (ICP) algorithm for stem position points to get the fine transformation parameters. The experimental results show that this method can achieve accurate alignment of the stem points captured from different sides in case of no artificial targets and poor intervisibility between different scans.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Côté, J.F., Fournier, R.A., Egli, R.: An architectural model of trees to estimate forest structural attributes using terrestrial LiDAR. Environ. Model Softw. 26(6), 761–777 (2011)

    Article  Google Scholar 

  2. La, H.P., Eo, Y.D., Chang, A., et al.: Extraction of individual tree crown using hyperspectral image and LiDAR data. KSCE J. Civ. Eng. 19(4), 1078–1087 (2015)

    Article  Google Scholar 

  3. Liu, F., Tan, C., Zhang, G., et al.: Estimation of forest parameter and biomass for individual pine trees using airborne LiDAR. Trans. Chin. Soc. Agric. Mach. 44(9), 219–242 (2013)

    Google Scholar 

  4. Chen, M., Wan, Y., Wang, M., et al.: Automatic stem detection in terrestrial laser scanning data with distance-adaptive search radius. IEEE Trans. Geosci. Remote Sens. 56(5), 2968–2979 (2018)

    Article  Google Scholar 

  5. Pirotti, F., Guarnieri, A., Vettore, A.: Ground filtering and vegetation mapping using multi-return terrestrial laser scanning. ISPRS J. Photogram. Remote Sens. 76(2), 56–63 (2013)

    Article  Google Scholar 

  6. Calders, K., Newnham, G., Burt, A., et al.: Nondestructive estimates of above-ground biomass using terrestrial laser scanning. Methods Ecol. Evol. 6(2), 198–208 (2015)

    Article  Google Scholar 

  7. Olofsson, K., Holmgren, J., Olsson, H.: Tree stem and height measurements using terrestrial laser scanning and the RANSAC algorithm. Remote Sens. 6(5), 4323–4344 (2014)

    Google Scholar 

  8. Besl, P.J., Mckay, N.D.: A Method for registration of 3-D shapes. In: Robotics - DL Tentative, pp. 239–256. International Society for Optics and Photonics (1992)

    Google Scholar 

  9. Chen, Y., Medioni, G.: Object modelling by registration of multiple range images. Image Vis. Comput. 10(3), 145–155 (1992)

    Article  Google Scholar 

  10. Li, J., Wang, Z.M., Ma, Y.R.: Automatic and accurate mosaicking of point clouds from multi-station laser scanning. Geomat. Inf. Sci. Wuhan Univ. 39(9), 1114–1120 (2014). (in Chinese)

    Google Scholar 

  11. Rusu, R.B., Blodow, N., Marton, Z.C., et al.: Aligning point cloud views using persistent feature histograms. In: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3384–3391. IEEE (2008)

    Google Scholar 

  12. Yang, B., Dong, Z., Liang, F., et al.: Automatic registration of large-scale urban scene point clouds based on semantic feature points. ISPRS J. Photogram. Remote Sens. 113, 43–58 (2016)

    Article  Google Scholar 

  13. Zhang, W., Chen, Y., Wang, H., et al.: Efficient registration of terrestrial LiDAR scans using a coarse-to-fine strategy for forestry applications. Agric. For. Meteorol. 225, 8–23 (2016)

    Article  Google Scholar 

  14. Kelbe, D., van Aardt, J., Romanczyk, P., et al.: Marker-free registration of forest terrestrial laser scanner data pairs with embedded confidence metrics. IEEE Trans. Geosci. Remote Sens. 54(7), 4314–4330 (2016)

    Article  Google Scholar 

  15. Henning, J.G., Radtke, P.J.: Multiview range-image registration for forested scenes using explicitly-matched tie points estimated from natural surfaces. ISPRS J. Photogram. Remote Sens. 63(1), 68–83 (2008)

    Article  Google Scholar 

  16. Liang, X., Hyyppä, J.: Automatic stem mapping by merging several terrestrial laser scans at the feature and decision levels. Sensors 13(2), 1614–1634 (2013)

    Article  Google Scholar 

  17. Brenner, C., Dold, C., Ripperda, N.: Coarse orientation of terrestrial laser scans in urban environments. ISPRS J. Photogram. Remote Sens. 63(1), 4–18 (2008)

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported in part by National Natural Science Foundation of China under grant no. 41801394, in part by Chongqing Natural Science Foundation under grant no. cstc2019jcyj-msxmX0370 and cstc2018jcyjAX0515 and in part by the Science and Technology Research Program of Chongqing Municipal Education Commission under grant no. KJQN201900729 and KJQN201900728.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Maolin Chen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chen, M., Tang, F., Pan, J. (2020). Registration of Multi-scan Forest Terrestrial Laser Scanning Data Integrated with Smartphone. In: Di Martino, S., Fang, Z., Li, KJ. (eds) Web and Wireless Geographical Information Systems. W2GIS 2020. Lecture Notes in Computer Science(), vol 12473. Springer, Cham. https://doi.org/10.1007/978-3-030-60952-8_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-60952-8_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60951-1

  • Online ISBN: 978-3-030-60952-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics