Abstract
Estimation of accurate forest variable is crucial for forest monitoring and quantifying forest aboveground biomass (AGB). The objective of this study was to estimate forest variables and AGB using the TLS data acquired over the tropical rainforest of Malaysia. Individual trees were detected using the manual detection method in the RiSCAN PRO software. An average tree detection rate of 99.55% was achieved from the 10 sample plots. Forest variables, including DBH and height, were measured from 10 circular sample plots in the field. The accuracy of diameter at breast height (DBH) of trees measured from TLS was validated using field DBH as reference. A root means square error (RMSE) of 1.37 cm (6.60%) was obtained for manually measured TLS DBH. Similarly, TLS-based tree height was validated using airborne laser scanner height as a reference and resulted in RMSE of 1.74 m (9.30%). Finally, AGB was calculated using the variables derived from the TLS data. The result has shown an R2 value of 0.98 and RMSE of 0.077 Mg for AGB calculated from TLS data. The result of this study confirmed that TLS can provide a very good estimation of forest variables and AGB in the tropical dense rainforest.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Abegg, M., Kükenbrink, D., Zell, J., Schaepman, M. E., & Morsdorf, F. (2017). Terrestrial laser scanning for forest inventories-tree diameter distribution and scanner location impact on occlusion. Forests,8(6), 1–29. https://doi.org/10.3390/f8060184.
Åkerblom, M., Raumonen, P., Mäkipää, R., & Kaasalainen, M. (2017). Automatic tree species recognition with quantitative structure models. Remote Sensing of Environment,191, 1–12. https://doi.org/10.1016/j.rse.2016.12.002.
Astrup, R., Ducey, M. J., Granhus, A., Ritter, T., & von Lüpke, N. (2014). Approaches for estimating stand-level volume using terrestrial laser scanning in a single-scan mode. Canadian Journal of Forest Research,44(6), 666–676. https://doi.org/10.1139/cjfr-2013-0535.
Barbosa, J. M., Broadbent, E. N., & Bitencourt, M. D. (2014). Remote sensing of aboveground biomass in tropical secondary forests: A review. International Journal of Forestry Research,2014, 1–14. https://doi.org/10.1155/2014/715796.
Bauwens, S., Bartholomeus, H., Calders, K., & Lejeune, P. (2016). Forest inventory with terrestrial LiDAR: A comparison of static and hand-held mobile laser scanning. Forests. https://doi.org/10.3390/f7060127
Bazezew, M. N., Hussin, Y. A., & Kloosterman, E. H. (2018). Integrating airborne LiDAR and terrestrial laser scanner forest parameters for accurate above-ground biomass/carbon estimation in Ayer Hitam tropical forest, Malaysia. International Journal of Applied Earth Observation and Geoinformation,73(July), 638–652. https://doi.org/10.1016/j.jag.2018.07.026.
Brolly, G., & Király, G. (2009). Algorithms for stem mapping by means of terrestrial laser scanning. Acta Silvatica et Lignaria Hungarica,5, 119–130.
Cabo, C., Ordóñez, C., López-Sánchez, C. A., & Armesto, J. (2018). Automatic dendrometry: Tree detection, tree height and diameter estimation using terrestrial laser scanning. International Journal of Applied Earth Observation and Geoinformation,69(January), 164–174. https://doi.org/10.1016/j.jag.2018.01.011.
Calders, K., Armston, J., Newnham, G., Herold, M., & Goodwin, N. (2014). Implications of sensor configuration and topography on vertical plant profiles derived from terrestrial LiDAR. Agricultural and Forest Meteorology,194, 104–117. https://doi.org/10.1016/j.agrformet.2014.03.022.
Calders, K., Newnham, G., Burt, A., Murphy, S., Raumonen, P., Herold, M., et al. (2015). Nondestructive estimates of above-ground biomass using terrestrial laser scanning. Methods in Ecology and Evolution.,6(2), 198–208. https://doi.org/10.1111/2041-210X.12301.
Cao, T., Xiao, A., Wu, L., & Mao, L. (2017). Automatic fracture detection based on terrestrial laser scanning data: A new method and case study. Computers and Geosciences,106, 209–216. https://doi.org/10.1016/j.cageo.2017.04.003.
Čerňava, J., Tuček, J., Koreň, M., & Mokroš, M. (2017). Estimation of diameter at breast height from mobile laser scanning data collected under a heavy forest canopy. Journal of Forest Science,63(9), 433–441. https://doi.org/10.17221/28/2017-JFS.
Chave, J., Réjou-Méchain, M., Búrquez, A., Chidumayo, E., Colgan, M. S., Delitti, W. B., et al. (2014). Improved allometric models to estimate the aboveground biomass of tropical trees. Global Change Biology,20(10), 3177–3190. https://doi.org/10.1111/gcb.12629.
Côté, J. F., Fournier, R. A., & Egli, R. (2011). An architectural model of trees to estimate forest structural attributes using terrestrial LiDAR. Environmental Modelling and Software,26(6), 761–777. https://doi.org/10.1016/j.envsoft.2010.12.008.
de Conto, T., Olofsson, K., Görgens, E. B., Rodriguez, L. C. E., & Almeida, G. (2017). Performance of stem denoising and stem modelling algorithms on single tree point clouds from terrestrial laser scanning. Computers and Electronics in Agriculture,143(October), 165–176. https://doi.org/10.1016/j.compag.2017.10.019.
Ducey, M. J., & Astrup, R. (2013). Adjusting for nondetection in forest inventories derived from terrestrial laser scanning. Canadian Journal of Remote Sensing,39(5), 410–425. https://doi.org/10.5589/m13-048.
Ferraz, A., Saatchi, S., Mallet, C., & Meyer, V. (2016). Lidar detection of individual tree size in tropical forests. Remote Sensing of Environment,183, 318–333. https://doi.org/10.1016/j.rse.2016.05.028.
Hackenberg, J., Morhart, C., Sheppard, J., Spiecker, H., & Disney, M. (2014). Highly accurate tree models derived from terrestrial laser scan data: A method description. Forests,5(5), 1069–1105. https://doi.org/10.3390/f5051069.
Hackenberg, J., Wassenberg, M., Spiecker, H., & Sun, D. (2015). Non destructive method for biomass prediction combining TLS derived tree volume and wood density. Forests,6(4), 1274–1300. https://doi.org/10.3390/f6041274.
He, Q., Chen, E., An, R., & Li, Y. (2013). Above-ground biomass and biomass components estimation using LiDAR data in a coniferous forest. Forests,4(4), 984–1002. https://doi.org/10.3390/f4040984.
Heinzel, J., & Huber, M. O. (2017). Detecting tree stems from volumetric TLS data in forest environments with rich understory. Remote Sensing. https://doi.org/10.3390/rs9010009.
Hilker, T., van Leeuwen, M., Coops, N. C., Wulder, M. A., Newnham, G. J., Jupp, D. L. B., et al. (2010). Comparing canopy metrics derived from terrestrial and airborne laser scanning in a Douglas-fir dominated forest stand. Trees - Structure and Function,24(5), 819–832. https://doi.org/10.1007/s00468-010-0452-7.
Holopainen, M., Vastaranta, M., & Hyyppä, J. (2014). Outlook for the next generation’s precision forestry in Finland. Forests,5(7), 1682–1694. https://doi.org/10.3390/f5071682.
Hopkinson, C., Chasmer, L., Young-Pow, C., & Treitz, P. (2004). Assessing forest metrics with a ground-based scanning lidar. Canadian Journal of Forest Research,34(3), 573–583. https://doi.org/10.1139/x03-225.
Hyyppä, J., Holopainen, M., & Olsson, H. (2012). Laser scanning in forests. Remote Sensing,4(10), 2919–2922. https://doi.org/10.3390/rs4102919.
IPCC. (2006). IPCC guidelines for national greenhouse gas inventories. In D. Aalde, N.H.R.H., Gonzalez, P., Gytarsky, M., Krug, T., Kurz, W.A., Ogle, S., Raison, J., Schoene (Ed.), Institute for global environmental strategies (IGES), (Vol. 4, pp. 556–556). Hayama, Japan,: Agriculture, Forestry and Other Land Use.
Kankare, V., Holopainen, M., Vastaranta, M., Liang, X., Yu, X., Kaartinen, H., Kukko, A., & Forest, Á. L. Á. S. Á. (2017). Outlook for the single-tree-level forest inventory in Nordic Countries. In The rise of big spatial data (pp. 183–195). https://doi.org/10.1007/978-3-319-45123-7_14
Kankare, V., Holopainen, M., Vastaranta, M., Puttonen, E., Yu, X., Hyyppä, J., et al. (2013). Individual tree biomass estimation using terrestrial laser scanning. ISPRS Journal of Photogrammetry and Remote Sensing.,75, 64–75. https://doi.org/10.1016/j.isprsjprs.2012.10.003.
Kankare, V., Liang, X., Vastaranta, M., Yu, X., Holopainen, M., & Hyyppä, J. (2015). Diameter distribution estimation with laser scanning based multisource single tree inventory. ISPRS Journal of Photogrammetry and Remote Sensing,108, 161–171. https://doi.org/10.1016/j.isprsjprs.2015.07.007.
Kankare, V., Puttonen, E., Holopainen, M., & Hyyppä, J. (2016). The effect of TLS point cloud sampling on tree detection and diameter measurement accuracy. Remote Sensing Letters,7(5), 495–502. https://doi.org/10.1080/2150704X.2016.1157639.
Kelbe, D., Van Aardt, J., Romanczyk, P., Van Leeuwen, M., & Cawse-Nicholson, K. (2015). Single-scan stem reconstruction using low-resolution terrestrial laser scanner data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,8(7), 3414–3427. https://doi.org/10.1109/JSTARS.2015.2416001.
Koreň, M., Mokroš, M., & Bucha, T. (2017). Accuracy of tree diameter estimation from terrestrial laser scanning by circle-fitting methods. International Journal of Applied Earth Observation and Geoinformation,63(April), 122–128. https://doi.org/10.1016/j.jag.2017.07.015.
Kronseder, K., Ballhorn, U., Böhmc, V., & Siegert, F. (2012). Above ground biomass estimation across forest types at different degradation levels in central kalimantan using lidar data. International Journal of Applied Earth Observation and Geoinformation,18(1), 37–48. https://doi.org/10.1016/j.jag.2012.01.010.
Liang, X., Hyyppä, J., Kaartinen, H., Lehtomäki, M., Pyörälä, J., Pfeifer, N., et al. (2018). International benchmarking of terrestrial laser scanning approaches for forest inventories. ISPRS Journal of Photogrammetry and Remote Sensing.,144, 137–179. https://doi.org/10.1016/j.isprsjprs.2018.06.021.
Liang, X., Hyyppa, J., Kukko, A., Kaartinen, H., Jaakkola, A., & Yu, X. (2014). The use of a mobile laser scanning system for mapping large forest plots. IEEE Geoscience and Remote Sensing Letters,11(9), 1504–1508. https://doi.org/10.1109/LGRS.2013.2297418.
Liang, X., Kankare, V., Hyyppä, J., Wang, Y., Kukko, A., Haggrén, H., et al. (2016). Terrestrial laser scanning in forest inventories. ISPRS Journal of Photogrammetry and Remote Sensing.,1(115), 63–77. https://doi.org/10.1016/j.isprsjprs.2016.01.006.
Liang, X., Litkey, P., Hyyppä, J., Kaartinen, H., Vastaranta, M., & Holopainen, M. (2012). Automatic stem mapping using single-scan terrestrial laser scanning. IEEE Transactions on Geoscience and Remote Sensing,50(2), 661–670. https://doi.org/10.1109/TGRS.2011.2161613.
Lindberg, E., Holmgren, J., Olofsson, K., & Olsson, H. (2012). Estimation of stem attributes using a combination of terrestrial and airborne laser scanning. European Journal of Forest Research,131(6), 1917–1931. https://doi.org/10.1007/s10342-012-0642-5.
Liu, G., Wang, J., Dong, P., Chen, Y., & Liu, Z. (2018). Estimating individual tree height and diameter at breast height (DBH) from terrestrial laser scanning (TLS) data at plot level. Forests,8(2), 1–19. https://doi.org/10.3390/f9070398.
Liu, J., Liang, X., Hyyppä, J., Yu, X., Lehtomäki, M., Pyörälä, J., et al. (2017). Automated matching of multiple terrestrial laser scans for stem mapping without the use of artificial references. International Journal of Applied Earth Observation and Geoinformation.,56, 13–23. https://doi.org/10.1016/j.jag.2016.11.003.
Lovell, J. L., Jupp, D. L. B., Newnham, G. J., & Culvenor, D. S. (2011). Measuring tree stem diameters using intensity profiles from ground-based scanning lidar from a fixed viewpoint. ISPRS Journal of Photogrammetry and Remote Sensing,66(1), 46–55. https://doi.org/10.1016/j.isprsjprs.2010.08.006.
Lu, D., Chen, Q., Wang, G., Liu, L., Li, G., & Moran, E. (2016). A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems. International Journal of Digital Earth. https://doi.org/10.1080/17538947.2014.990526.
Newnham, G. J., Armston, J. D., Calders, K., Disney, M. I., Lovell, J. L., Schaaf, C. B., et al. (2015). Terrestrial laser scanning for plot-scale forest measurement. Current Forestry Reports,1(4), 239–251. https://doi.org/10.1007/s40725-015-0025-5.
Nurul-Shida, S., Faridah-Hanum, I., Wan Razali, W. M., & Kamziah, K. (2014). Community structure of trees in Ayer Hitam Forest Reserve, Puchong, Selangor, Malaysia. Malaysian Forester,77(1), 73–86.
Olofsson, K., Holmgren, J., & Olsson, H. (2014). Tree stem and height measurements using terrestrial laser scanning and the RANSAC algorithm. Remote Sensing,6(5), 4323–4344. https://doi.org/10.3390/rs6054323.
Olschofsky, K., Mues, V., & Köhl, M. (2016). Operational assessment of aboveground tree volume and biomass by terrestrial laser scanning. Computers and Electronics in Agriculture,127, 699–707. https://doi.org/10.1016/j.compag.2016.07.030.
Oveland, I., Hauglin, M., Giannetti, F., Kjørsvik, N. S., & Gobakken, T. (2018). Comparing three different ground based laser scanning methods for tree stem detection. Remote Sensing,10(4), 1–17. https://doi.org/10.3390/rs10040538.
Ramirez, F. A., Armitage, R. P., & Danson, F. M. (2013). Testing the application of terrestrial laser scanning to measure forest canopy gap fraction. Remote Sensing,5(6), 3037–3056. https://doi.org/10.3390/rs5063037.
Reddy, R. S., Jha, C. S., & Rajan, K. S. (2018). Automatic estimation of tree stem attributes using terrestrial laser scanning in central Indian dry deciduous forests. Current Science,114(1), 201–206. https://doi.org/10.18520/cs/v114/i01/201-206.
RIEGL. (2017). RIEGL VZ-400 Specifications. Retrieved from. https://www.riegl.com/uploads/tx_pxpriegldownloads/10_DataSheet_VZ-400_2017-06-14.pdf
Simonse, M., Aschoff, T., Spiecker, H., & Thies, M. (2003). Automatic Determination of Forest Inventory Parameters Using Terrestrial Laserscanning. Institute for Forest Growth, 1–7.
Srinivasan, S., Popescu, S. C., Eriksson, M., Sheridan, R. D., & Ku, N. W. (2015). Terrestrial laser scanning as an effective tool to retrieve tree level height, crown width, and stem diameter. Remote Sensing,7(2), 1877–1896. https://doi.org/10.3390/rs70201877.
Stovall, A. E. L., Vorster, A. G., Anderson, R. S., Evangelista, P. H., & Shugart, H. H. (2017). Non-destructive aboveground biomass estimation of coniferous trees using terrestrial LiDAR. Remote Sensing of Environment,200(July), 31–42. https://doi.org/10.1016/j.rse.2017.08.013.
Thies, M., & Spiecker, H. (2004). Evaluation and future prospects of terrestrial laser-scanning for standardized forest inventories. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences,36, 192–197.
Toriman, M. E., Er, A. C., Lee, Q. Y., Mastura, S. S., Jali, F. M., Mokhtar, M., et al. (2013). Paddy production and climate change variation in Selangor, Malaysia. Asian Social Science,9(14), 55. https://doi.org/10.5539/ass.v9n14p55.
Vastaranta, M., Wulder, M. A., White, J. C., Pekkarinen, A., Tuominen, S., Ginzler, C., et al. (2013). Airborne laser scanning and digital stereo imagery measures of forest structure: Comparative results and implications to forest mapping and inventory update. Canadian Journal of Remote Sensing,39(5), 382–395. https://doi.org/10.5589/m13-046.
Wang, Y., Lehtomäki, M., Liang, X., Pyörälä, J., Kukko, A., Jaakkola, A., et al. (2019). Is field-measured tree height as reliable as believed – A comparison study of tree height estimates from field measurement, airborne laser scanning and terrestrial laser scanning in a boreal forest. ISPRS Journal of Photogrammetry and Remote Sensing,147(November), 132–145. https://doi.org/10.1016/j.isprsjprs.2018.11.008.
Watt, P. J., & Donoghue, D. N. M. (2005). Measuring forest structure with terrestrial laser scanning. International Journal of Remote Sensing,26(7), 1437–1446. https://doi.org/10.1080/01431160512331337961.
White, J. C., Coops, N. C., Wulder, M. A., Vastaranta, M., Hilker, T., & Tompalski, P. (2016). Remote sensing technologies for enhancing forest inventories: A review. Canadian Journal of Remote Sensing,42(5), 619–641. https://doi.org/10.1080/07038992.2016.1207484.
Wilkes, P., Lau, A., Disney, M., Calders, K., Burt, A., de Tanago, J. G., et al. (2017). Data acquisition considerations for terrestrial laser scanning of forest plots. Remote Sensing of Environment,196, 140–153. https://doi.org/10.1016/j.rse.2017.04.030.
Xi, Z., Hopkinson, C., & Chasmer, L. (2016). Automating plot-level stem analysis from terrestrial laser scanning. Forests,7(11), 1–20. https://doi.org/10.3390/f7110252.
Yang, B., Dai, W., Dong, Z., & Liu, Y. (2016). Automatic forest mapping at individual tree levels from terrestrial laser scanning point clouds with a hierarchical minimum cut method. Remote Sensing, 8(5). https://doi.org/10.3390/rs8050372
Zhang, W., Wan, P., Wang, T., Cai, S., Chen, Y., Jin, X., et al. (2019). A novel approach for the detection of standing tree stems from plot-level terrestrial laser scanning data. Remote Sensing,11(2), 1–19. https://doi.org/10.3390/rs11020211.
Acknowledgements
The research was conducted in Ayer Hitam tropical rainforest, Malaysia, in collaboration with the University of Putra Malaysia. This research was funded by NUFFIC, the Netherlands Fellowship Programmes (NFP). We are grateful for those who were actively involved and helped us in the field data collection. We are also thankful for the anonymous reviewers who gave us constructive comments and suggestions that helped us to improve the manuscript.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Beyene, S.M. Estimation of Forest Variable and Aboveground Biomass using Terrestrial Laser Scanning in the Tropical Rainforest. J Indian Soc Remote Sens 48, 853–863 (2020). https://doi.org/10.1007/s12524-020-01119-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12524-020-01119-2