Address: Naberezhnaya Severnoy Dviny, 17, Arkhangelsk, 163002, Russian Federation, Northern (Arctic) Federal University named after M.V.Lomonosov, office 1425

Phone: +7 (8182) 21-61-18
E-mail: forest@narfu.ru
http://lesnoizhurnal.ru/en/

Lesnoy Zhurnal

Laser Scanning and Aerial Photography with UAV in Studying the Structure of Forest-Tundra Stands in the Khibiny Mountains

Версия для печати

N.F. Nisametdinow, P.A. Moiseev, I.B. Vorobiev

Complete text of the article:

Download article (pdf, 2.6MB )

UDС

528.854:630*5

DOI:

10.37482/0536-1036-2021-4-9-22

Abstract

Studying the structure of stands is a key point in assessing the role of trees in carbon deposition. Information on the spatial structure of ground vegetation at the upper treeline is still insufficiently presented in modern studies. High resolution remote sensing can provide important data to understand the properties and dynamics of vegetation in these conditions. We test the applicability of ground-based mobile laser scanning of the terrain and aerial photography for the rapid and high-precision assessment of the characteristics of tree stands in the forest-tundra ecotone. We obtained canopy height models (CHMs) of the forest and supplemented them with aerial photographs of the research area on the southeastern slope of the Khibiny Mountains. Using CHMs we have delineated boundaries of tree crowns. The height and projection area were determined for each tree. The first characteristic obtained by laser scanning was compared to the heights of the same trees estimated by field measurements. This was done for the purposes of verification. The comparison revealed that laser scanning data allow to set heights closest to field measurements in case the heights are determined by the maximum values of brightness of pixels of CHMs with manual correction of values when outliers are detected (R2 = 0.84). Since manual correction of outliers is time-consuming, we proposed a way to automate the measurements by determining tree heights using the sum of the average value of pixel brightness and the standard deviation multiplied by 2.5 (R2 = = 0.79). We compared the area characteristics of the stands obtained by laser scanning and the unmanned aerial vehicle (UAV) photography. Thus, we obtained detailed information on the spatial location and size of 4424 trees in an area of about 10 ha and compared the results of measuring tree characteristics obtained by different methods. It was also found that with increasing height from 290 to 425 m above sea level on the studied slope, the average height of stands decreases gradually from 4.5–5.0 to 1.1–1.6 m with small fluctuations (0.2–0.4 m), while the density of stands changes from 4620–5860 to 145 m2/ha in a non-linear way.

Authors

Nail F. Nisametdinow, Candidate of Agriculture, Research Scientist; ResearcherID:AAI-3961-2020, ORCID: https://orcid.org/0000-0001-9410-6807
Pavel A. Moiseev, Doctor of Biology; ResearcherIDM-9132-2013, ORCID: https://orcid.org/0000-0003-4808-295X
Ivan B. Vorobiev, Research Scientist; ResearcherID:AAK-3957-2021, ORCID: https://orcid.org/0000-0002-2563-585X
e-mail: niznail@yandex.ru

Affiliation

Institute of Plant and Animal Ecology, Ural Branch, Russian Academy of Sciences, ul. 8 Marta, 202, Yekaterinburg, 620144, Russian Federation

Keywords

laser scanning, aerial photography, digital elevation model, digital surface model, canopy height model, segmentation, upper treeline, Khibiny Mountains

For citation

Nisametdinow N.F., Moiseev P.A., Vorobiev I.B. Laser Scanning and Aerial Photography with UAV in Studying the Structure of Forest-Tundra Stands in the Khibiny Mountains. Lesnoy Zhurnal [Russian Forestry Journal], 2021, no. 4, pp. 9–22. DOI: 10.37482/0536-1036-2021-4-9-22

References

1. Grigor’ev A.A., Devi N.M., Kukarskikh V.V., V’yukhin S.O., Galimova A.A., Moiseev P.A., Fomin V.V. Structure and Dynamics of Tree Stands at the Upper Timberline in the Western Part of the Putorana Plateau. Ekologiya [Russian Journal Ecology], 2019, no. 4, pp. 243–254. DOI: https://doi.org/10.1134/S0367059719040073

2. Moiseev P.A., Galimova A.A., Bubnov M.O., Devi N.M., Fomin V.V. Tree Stands and Their Productivity Dynamics at the Upper Growing Limit in Khibiny on the Background of Modern Climate Changes. Ekologiya [Russian Journal Ecology], 2019, no. 5, pp. 341–355. DOI: https://doi.org/10.1134/s0367059719050081

3. Agisoft PhotoScan User Manual. Professional Edition, Version 0.9.0. Agisoft LLC, 2012. 49 p. Available at: http://downloads.agisoft.ru/pdf/photoscan-pro_0_9_0_en.pdf (accessed 07.02.20).

4. Bonan G.B. Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests. Science, 2008, vol. 320, iss. 5882, pp. 1444–1449. DOI: https://doi.org/10.1126/science.1155121

5. Brieger F., Herzschuh U., Pestryakova L.A., Bookhagen B., Zakharov E.S., Kruse S. Advances in the Derivation of Northeast Siberian Forest Metrics Using High-Resolution UAV-Based Photogrammetric Point Clouds. Remote Sensing, 2019, vol. 11, iss. 12, art. 1447. DOI: https://doi.org/10.3390/rs11121447

6. Cairns D.M. Patterns of Winter Desiccation in Krummholz Forms of Abies lasiocarpa at Treeline Sites in Glacier National Park, Montana, USA. Geografiska Annaler: Series A, Physical Geography, 2001, vol. 83, iss. 3, pp. 157–168. DOI: https://doi.org/10.1111/j.0435-3676.2001.00151.x

7. Chen Q., Baldocchi D., Gong P., Kelly M. Isolating Individual Trees in a Savanna Woodland Using Small Footprint Lidar Data. Photogrammetric Engineering & Remote Sensing, 2006, vol. 72, no. 8, pp. 923–932. DOI: https://doi.org/10.14358/PERS.72.8.923

8. Durrant-Whyte H., Bailey T. Simultaneous Localization and Mapping: Part I. IEEE Robotics & Automation Magazine, 2006, vol. 13, iss. 2, pp. 99–110. DOI: https://doi.org/10.1109/MRA.2006.1638022

9. Hagedorn F., Shiyatov S.G., Mazepa V.S., Devi N.M., Grigor’ev A.A., Bartysh A.A., Fomin V.V., Kapralov D.S., Terent’ev M., Bugman H., Rigling A., Moiseev P.A. Treeline Advances along the Urals Mountain Range – Driven by Improved Winter Conditions? Global Change Biology, 2014, vol. 20, iss. 11, pp. 3530–3543. DOI: https://doi.org/10.1111/gcb.12613

10. Harsch M.A., Hulme P.E., McGlone M.S., Duncan R.P. Are Treelines Advancing? A Global Meta-Analysis of Treeline Response to Climate Warming. Ecology Letters, 2009, vol. 12, iss. 10, pp. 1040–1049. DOI: https://doi.org/10.1111/j.1461-0248.2009.01355.x

11. Kammer A., Hagedorn F., Shevchenko I., Leifeld J., Guggenberger G., Goryacheva T.,Rigling A., Moiseev P. Treeline Shifts in the Ural Mountains Affect Soil Organic Matter Dynamics. Global Change Biology, 2009, vol. 15, iss. 6, pp. 1570–1583. DOI: https://doi.org/10.1111/j.1365-2486.2009.01856.x

12. Kulha N., Pasanen L., Aakala T. How to Calibrate Historical Aerial Photographs: A Change Analysis of Naturally Dynamic Boreal Forest Landscapes. Forests, 2018, vol. 9, iss. 10, art. 631. DOI: https://doi.org/10.3390/f9100631

13. Kullman L. Climate Change and Primary Birch Forest (Betula pubescens ssp. czerepanovii) Succession in the Treeline Ecotone of the Swedish Scandes. International Journal of Research in Geography, 2016, vol. 2, iss. 2, pp. 36–47. DOI: https://doi.org/10.20431/2454-8685.0202004

14. Liang X., Kukko A., Hyyppä J., Lehtomäki M., Pyörälä J., Yu X., Kaartinen H., Jaakkola A., Wang Y. In-situ Measurements from Mobile Platforms: An Emerging Approach to Address the Old Challenges Associated with Forest Inventories. ISPRS Journal of Photogrammetry and Remote Sensing, 2018, vol. 143, pp. 97–107. DOI: https://doi.org/10.1016/j.isprsjprs.2018.04.019

15. Lisein J., Pierrot-Deseilligny M., Bonnet S., Lejeune P. A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery. Forests, 2013, vol. 4, iss. 4, pp. 922–944. DOI: https://doi.org/10.3390/ f4040922

16. Maguire A.J., Eitel J.U.H., Vierling L.A., Johnson D.M., Griffin K.L., Boelman N.T., Jensen J.E., Greaves H.E., Meddens A.J.H. Terrestrial Lidar Scanning Reveals Fine-Scale Linkages between Microstructure and Photosynthetic Functioning of Small-Stature Spruce Trees at the Forest-Tundra Ecotone. Agricultural and Forest Meteorology, 2019, vol. 269-270, pp. 157–168. DOI: https://doi.org/10.1016/j.agrformet.2019.02.019

17. Ranson K.J., Montesano P.M., Nelson R. Object-Based Mapping of the Circumpolar Taiga-Tundra Ecotone with MODIS Tree Cover. Remote Sensing of Environment, 2011, vol. 115, iss. 12, pp. 3670–3680. DOI: https://doi.org/10.1016/j.rse.2011.09.006

18. Shettigara V.K., Sumerling G.M. Height determination of extended objects using shadows in SPOT images. Photogrammetric Engineering and Remote Sensing, 1998, vol. 64, iss. 1, pp. 35–44.

19. Solly E.F., Djukic I., Moiseev P.A., Andreyashkina N.I., Devi N.M., Göransson H., Mazepa V.S., Shiyatov S.G., Trubina M.R., Schweingruber F.H., Wilmking M., Hagedorn F. Treeline Advances and Associated Shifts in the Ground Vegetation Alter Fine Root Dynamics and Mycelia Production in the South and Polar Urals. Oecologia, 2017, vol. 183, iss. 2, pp. 571–586. DOI: https://doi.org/10.1007/s00442-016-3785-0

20. Westoby M.J., Brasington J., Glasser N.F., Hambrey M.J., Reynolds J.M. ‘Structure-from-Motion’ Photogrammetry: A Low-Cost, Effective Tool for Geoscience Applications. Geomorphology, 2012, vol. 179, pp. 300–314. DOI: https://doi.org/10.1016/j.geomorph.2012.08.021


Laser Scanning and Aerial Photography with UAV in Studying the Structure of Forest-Tundra Stands in the Khibiny Mountains

 

Make a Submission


ADP_cert_2025.png

Lesnoy Zhurnal (Russian Forestry Journal) was awarded the "Seal of Recognition for Active Data Provider of the Year 2025"

INDEXED IN: 

scopus.jpg

DOAJ_logo-colour.png

logotype.png

Логотип.png