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Leaf orientation measurement in a mixed hemiboreal broadleaf forest stand using terrestrial laser scanner

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Abstract

Orientation of leaves in a mature hemiboreal mixed broadleaf stand (the Järvselja RAMI birch stand) was measured using the high-density point cloud of terrestrial laser scanner hits. Leaf normal distribution in the upper part of crowns of tall aspen and birch trees is almost spherical, and slightly planophile in the lower part of crowns. Leaves of alder trees are rather planophile in the upper part of crowns, and strongly planophile in the lower part of crowns. Lime and maple trees form the lower layer of trees in the stand. Their crowns are mainly in shade, and therefore, their leaf orientation is strongly planophile throughout the whole crown. Parameters of beta distribution and elliptical distribution are provided for the approximation of empirical distributions. The acquired information about leaf orientation can improve performance assessment of radiative transfer models.

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References

  • Cignoni P, Callieri M, Corsini M, Dellepiane M, Ganovelli F, Ranzuglia G (2008) MeshLab: an open-source mesh processing tool. In: Scarano V, Chiara RD, Erra U (eds) Eurographics Italian chapter conference, The Eurographics Association. https://doi.org/10.2312/LocalChapterEvents/ItalChap/ItalianChapConf2008/129-136

  • Danson F, Hetherington D, Morsdorf F, Koetz B, Allgöwer B (2007) Forest canopy gap fraction from terrestrial laser scanning. IEEE Geosci Remote Sens Lett 4(1):157–160

    Article  Google Scholar 

  • Disney M (2018) Terrestrial LiDAR: a three-dimensional revolution in how we look at trees. New Phytol. https://doi.org/10.1111/nph.15517

    Article  PubMed  Google Scholar 

  • Goel N, Strebel D (1984) Simple beta distribution representation of leaf orietation in vegetation canopies. Agron J 76(5):800–802

    Article  Google Scholar 

  • Hancock S, Essery R, Reid T, Carle J, Baxter R, Rutter N, Huntley B (2014) Characterising forest gap fraction with terrestrial lidar and photography: an examination of relative limitations. Agric For Meteorol 189–190:105–114

    Article  Google Scholar 

  • Hosoi F, Omasa K (2015) Estimating leaf inclination angle distribution of broad-leaved trees in each part of the canopies by a high-resolution portable scanning lidar. J Agric Meteorol 71:136–141. https://doi.org/10.2480/agrmet.D-14-00049

    Article  Google Scholar 

  • ** S, Tamura M, Susaki J (2016) A new approach to retrieve leaf normal distribution using terrestrial laser scanners. J For Res 27(3):631–638. https://doi.org/10.1007/s11676-015-0204-z

    Article  CAS  Google Scholar 

  • Kuusk A (1995) A fast, invertible canopy reflectance model. Remote Sens Environ 51(3):342–350

    Article  Google Scholar 

  • Kuusk A, Lang M, Kuusk J (2013) Database of optical and structural data for the validation of forest radiative transfer models. In: Kokhanovsky A (ed) Light scattering reviews, vol 7. Springer, Berlin, pp 109–148

    Chapter  Google Scholar 

  • Kuusk A, Pisek J, Lang M, Märdla S (2018) Estimation of gap fraction and foliage clum** in forest canopies. Remote Sens 10(7):1153. https://doi.org/10.3390/rs10071153

    Article  Google Scholar 

  • LG (2011) Leica scanstation C10. The all-in-one laser scanner for any application. Leica Geosystems AG, Heerbrugg, Switzerland

    Google Scholar 

  • Lovell J, Jupp D, Culvenor D, Coops N (2003) Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests. Can J Remote Sens 29(5):607–622

    Article  Google Scholar 

  • McNeil B, Pisek J, Lepisk H, Flamenco E (2016) Measuring leaf angle distribution in broadleaf canopies using UAVs. Agric For Meteorol 218–219:204–208

    Article  Google Scholar 

  • Nilson T (1968) On the optimal geometrical arrangement of foliage in the plant cover. In: The radiation regime in vegetation canopy. Institute of Physics and Astronomy, Estonian Academy of Sciences, Tartu, pp 112–146 (Russian)

  • Nilson T (1971) A theoretical analysis of the frequency of gaps in plant stands. Agric Meteorol 8:25–38

    Article  Google Scholar 

  • PCL (2018) Point cloud library, electronic document. http://pointclouds.org

  • PCL, Normals (2018) Estimating surface normals in a pointcloud, electronic document. http://pointclouds.org/documentation/tutorials/normal_estimation.php

  • Pisek J, Ryu Y, Alikas K (2011) Estimating leaf inclination and G-function from leveled digital camera photography in broadleaf canopies. Trees 25:919–924

    Article  Google Scholar 

  • Pisek J, Sonnentag O, Richardson A, Mõttus M (2013) Is the spherical leaf inclination angle distribution a valid assumption for temperate and boreal broadleaf tree species. Agric For Meteorol 169:186–194

    Article  Google Scholar 

  • Raabe K, Pisek J, Sonnentag O, Annuk K (2015) Variations of leaf inclination angle distribution with height over the growing season and light exposure for eight broadleaf tree species. Agric For Meteorol 214–215:2–11

    Article  Google Scholar 

  • RAMI-IV (2009) RAdiation transfer model intercomparison (RAMI). Järvselja Birch Stand (Summer). http://rami-benchmark.jrc.ec.europa.eu/HTML/RAMI-IV/RAMI-IV.php

  • Ramirez F, Armitage R, Danson F (2013) Testing the application of terrestrial laser scanning to measure forest canopy gap fraction. Remote Sens 5:3037–3056. https://doi.org/10.3390/rs5063037

    Article  Google Scholar 

  • Raumonen P, Casella E, Calders K, Murphy S, Åkerblom M, Kaasalainen M (2015) Massive-scale tree modelling from TLS data. In: ISPRS annals of photogrammetry, remote sensing and spatial information sciences, II-3/W4, pp 189–196

  • Richard A, Lang G (1990) An instrument for measuring canopy structure. Remote Sens Rev 5(1):61–71

    Article  Google Scholar 

  • Ross J (1981) The radiation regime and architecture of plant stands. Dr. W. Junk Publishers, The Hague

    Book  Google Scholar 

  • Ryu Y, Nilson T, Kobayashi H, Sonnentag O, Law B, Baldocchi D (2010) On the correct estimation of effective leaf area index: does it reveal information on clum** effects? Agric For Meteorol 150(3):463–472

    Article  Google Scholar 

  • Seidel D, Fleck S, Leuschner C (2012) Analyzing forest canopies with ground-based laser scanning: a comparison with hemispherical photography. Agric For Meteorol 154:1–8

    Article  Google Scholar 

  • Vicari M (2018a) TLSeparation. https://doi.org/10.5281/zenodo.1147706

    Article  Google Scholar 

  • Vicari M (2018b) TLSeparation. Electronic document. https://tlseparation.github.io/documentation/

  • Vicari M, Pisek J, Disney M (2019) New estimates of leaf angle distribution from terrestrial LiDAR: comparison with measured and modelled estimates from nine broadleaf tree species. Agric For Meteorol 264:322–333. https://doi.org/10.1016/j.agrformet.2018.10.021

    Article  Google Scholar 

  • Widlowski JL, Mio C, Disney M, Adams J, Andredakis I, Atzberger C, Brennan J, Busetto L, Chelle M, Ceccherini G, Colombo R, Côté JF, Eenmäe A, Essery R, Gastellu-Etchegorry JP, Gobron N, Grau E, Haverd V, Homolová L, Huang H, Hunt L, Kobayashi H, Koetz B, Kuusk A, Kuusk J, Lang M, Lewis P, Lovell J, Malenovský Z, Meroni M, Morsdorf F, Mõttus M, Ni-Meister W, Pinty B, Rautiainen M, Schlerf M, Somers B, Stuckens J, Verstraete M, Yang W, Zhao F, Zenone T (2015) The fourth phase of the radiative transfer model intercomparison (RAMI) exercise: actual canopy scenarios and conformity testing. Remote Sens Environ 169:418–437. https://doi.org/10.1016/j.rse.2015.08.016

    Article  Google Scholar 

  • Zheng G, Moskal L (2012) Leaf orientation retrieval from terrestrial laser scanning (TLS) data. IEEE Trans Geosci Remote Sens 50(10):3970–3979. https://doi.org/10.1109/TGRS.2012.2188533

    Article  Google Scholar 

  • Zygmunt M (2013) The testing of PCL: an open-source library for point cloud processing. Geomat Landmanag Landsc 3:105–115. https://doi.org/10.15576/GLL/2013.3.105

    Article  Google Scholar 

Download references

Acknowledgements

This study was made possible by funding support from the Estonian Research Council, as project SF0180009Bs11, under Grants PUT232, PUT1355, and Mobilitas Pluss MOBERC-11. I am very grateful to colleagues Drs Silja Märdla, Mait Lang, and Jan Pisek for collecting data and discussing the manuscript. I would like to thank the Government of Estonian for continuously kee** up our hopes about raising research funding to 1% of GDP.

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Correspondence to Andres Kuusk.

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Kuusk, A. Leaf orientation measurement in a mixed hemiboreal broadleaf forest stand using terrestrial laser scanner. Trees 34, 371–380 (2020). https://doi.org/10.1007/s00468-019-01922-6

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