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Estimating stem volume and biomass of Pinus koraiensis using LiDAR data

  • JPR Symposium
  • Carbon cycle process in East Asia
  • Published:
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Abstract

The objective of this study was to estimate the stem volume and biomass of individual trees using the crown geometric volume (CGV), which was extracted from small-footprint light detection and ranging (LiDAR) data. Attempts were made to analyze the stem volume and biomass of Korean Pine stands (Pinus koraiensis Sieb. et Zucc.) for three classes of tree density: low (240 N/ha), medium (370 N/ha), and high (1,340 N/ha). To delineate individual trees, extended maxima transformation and watershed segmentation of image processing methods were applied, as in one of our previous studies. As the next step, the crown base height (CBH) of individual trees has to be determined; information for this was found in the LiDAR point cloud data using k-means clustering. The LiDAR-derived CGV and stem volume can be estimated on the basis of the proportional relationship between the CGV and stem volume. As a result, low tree-density plots had the best performance for LiDAR-derived CBH, CGV, and stem volume (R 2 = 0.67, 0.57, and 0.68, respectively) and accuracy was lowest for high tree-density plots (R 2 = 0.48, 0.36, and 0.44, respectively). In the case of medium tree-density plots accuracy was R 2 = 0.51, 0.52, and 0.62, respectively. The LiDAR-derived stem biomass can be predicted from the stem volume using the wood basic density of coniferous trees (0.48 g/cm3), and the LiDAR-derived above-ground biomass can then be estimated from the stem volume using the biomass conversion and expansion factors (BCEF, 1.29) proposed by the Korea Forest Research Institute (KFRI).

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References

  • ArcGIS (2001) Help document in program. Environmental Systems Research Institute (ESRI), United States of America

  • Bortolot ZJ, Wynne RH (2005) Estimating forest biomass using small footprint LiDAR data: an individual tree-based approach that incorporates training data. Photogramm Remote Sens 59:342–360

    Article  Google Scholar 

  • Boudreau J, Nelson RF, Margolis HA, Beaudoin A, Guindon L, Kimes DS (2008) Regional aboveground forest biomass using airborne and spaceborne LiDAR in Québec. Remote Sens Environ 112:3876–3890

    Article  Google Scholar 

  • Brandtberg T, Warner TA, Landenberger RE, McGraw JB (2003) Detection and analysis of individual leaf-off tree crowns in small footprint, high sampling density LiDAR data from eastern deciduous forest in North America. Remote Sens Environ 85:290–303

    Article  Google Scholar 

  • Chen Q, Baldocchi D, Gong P, Kelly M (2006) Delineating individual trees in a Savanna Woodland using small footprint LiDAR data. Photogramm Eng Remote Sens 72:923–932

    Google Scholar 

  • Chen Q, Gong P, Baldocchi D, Tian YQ (2007) Estimating basal area and stem volume for individual trees from LiDAR data. Photogramm Eng Remote Sens 73:1355–1365

    Google Scholar 

  • Coder KD (2000) Crown shape factor & volumes. Tree biomechanics series of University of Georgia 11:1–5

    Google Scholar 

  • Drake JB, Dubayah RO, Clark DB, Knox RG, Blair JB, Hofton MA, Chazdon RL, Weishampel JF, Prince S (2002) Estimation of tropical forest structural characteristics using large-footprint LiDAR. Remote Sens Environ 79:305–319

    Article  Google Scholar 

  • Drake JB, Knox RG, Dubayah RO, Clark DB, Condit R, Blair JB, Hofton M (2003) Above-ground biomass estimation in closed canopy Neotropical forests using LiDAR remote sensing: factors affecting the generality of relationships. Glob Ecol Biogeogr 12:147–159

    Article  Google Scholar 

  • Enquist BJ (2002) Universal scaling in tree and vascular plant allometry: toward a general quantitative theory linking plant form and function from cells to ecosystem. Tree Physiol 22:1045–1064

    PubMed  Google Scholar 

  • Holmgren J, Nilsson M, Olsson H (2003) Estimation of tree height and stem volume on plots using airborne laser scanning. For Sci 49:419–428

    Google Scholar 

  • Hyyppä J, Inkinen M (1999) Detecting and estimating attributes for single trees using laser scanner. Photogramm J Finl 16:27–42

    Google Scholar 

  • Hyyppä J, Kelle O, Lehikoinen M, Inkinen M (2001) A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners. IEEE Trans Geosci Remote Sens 39:969–975

    Article  Google Scholar 

  • Kim JM, Park KS, Baek ES, Song YK, Ahn CY, Lee KH, Lee MH, Lee SY, Lee SH, Jeong YK, Jeong JH, Joo RW, Choi K, Choi MS, Song JH, Kim JW, Kim JY, Park MS, Song TY, Kim JH, Yang SI, Jang WH, Jang CS (2000) Forest & forestry technique. Korea Forest Service, Daejeon, South Korea

  • Kubo M, Nishikawa S, Yamamoto E, Muramoto K (2007) Identification of individual tree crowns from satellite image and image-to-map rectification. In: Geoscience and remote sensing symposium, 2007. IGARSS IEEE 2007 international, July 23–28 2007, pp 1905–1908

  • Kwak DA, Lee WK, Lee JH, Biging GS, Gong P (2007) Detection of individual trees and estimation of tree height using LiDAR data. J For Res 12:425–434

    Article  Google Scholar 

  • Leckie D, Gougeon F, Hill D, Quinn R, Armstrong L, Shreenan R (2003) Combined high-density LiDAR and multispectral imagery for individual tree crown analysis. Can J Remote Sens 29:633–649

    Google Scholar 

  • Lee JK, Hwang CS, Jung SH (2003) Analysis of accuracy for the control points using the GPS continuous stations. Korean Soc Civil Eng J 23:401–409

    Google Scholar 

  • Lefsky MA, Cohen WB, Acker SA, Parker GG, Spies TA, Harding D (1999a) LiDAR remote sensing of the canopy structure and biophysical properties of Douglas-fir western hemlock forests. Remote Sens Environ 70:339–361

    Article  Google Scholar 

  • Lefsky MA, Harding D, Cohen WB, Parker GG, Shugart HH (1999b) Surface LiDAR remote sensing of basal area and biomass in deciduous forests of Eastern Maryland, USA. Remote Sens Environ 67:83–98

    Article  Google Scholar 

  • Lefsky MA, Cohen WB, Spies TA (2001) An evaluation of alternative remote sensing products for forest inventory, monitoring, and mapping of Douglas-fir forests in western Oregon. Can J For Res 31:78–87

    Article  Google Scholar 

  • Lefsky MA, Cohen WB, Harding DJ, Parker GG, Acker SA, Gower ST (2002) LiDAR remote sensing of aboveground biomass in three biomes. Glob Ecol Biogeogr 11:393–399

    Article  Google Scholar 

  • Lim C (2007) Estimation of urban tree crown volume based on object-oriented approach and LiDAR data. Master’s Thesis, International Institute for Geo-Information Science and Earth observation, Enschede, Netherlands, p 23

  • Lim KS, Treitz PM (2004) Estimation of above ground forest biomass from airborne discrete return laser scanner data using canopy-based quantile estimators. Scand J For Res 19:558–570

    Article  Google Scholar 

  • Lim K, Treitz P, Baldwin K, Morrison I, Green J (2003) LiDAR remote sensing of biophysical properties of tolerant northern hardwood forests. Can J Remote Sens 29:658–678

    Google Scholar 

  • Malhi Y, Meir P, Brown S (2002) Forests, carbon and global climate. Philos Trans R Soc London A 360(1797):1567–1591

    Article  Google Scholar 

  • MATLAB (2006) Help document in program. Mathwork, United States of America

    Google Scholar 

  • Means JE, Acker SA, Harding DJ, Blair JB, Lefsky MA, Cohen WB, Harmon ME, McKee WA (1999) Use of large footprint scanning airborne LiDAR to estimate forest stand characteristics in the Western Cascades of Oregon. Remote Sens Environ 67:298–308

    Article  Google Scholar 

  • Morsdorf F, Kötz B, Meier E, Itten KI, Allgöwer B (2005) The potential of discrete return, small footprint airborne laser scanning data for vegetation density estimation. In: Proceedings of ISPRS WG III/3, III/4, V/3 Workshop Laser scanning 2005, September 12–14, 2005, Enschede, The Netherlands

  • Naesset E (1997) Estimating timber volume of forest stands using airborne laser scanner data. Remote Sens Environ 61:246–253

    Article  Google Scholar 

  • Nelson R, Krabill W, Tonelli J (1988) Estimating forest biomass and volume using airborne laser data. Remote Sens Environ 24:247–267

    Article  Google Scholar 

  • Persson Å, Holmgren J, Söderman U (2002) Detecting and measuring individual trees using an airborne laser scanner. Photogramm Eng Remote Sens 68:925–932

    Google Scholar 

  • Popescu SC (2007) Estimating biomass of individual pine trees using airborne lidar. Biomass Bioenergy 31:646–655

    Article  Google Scholar 

  • Popescu SC, Wynne RH (2004) Seeing the trees in the forest: using LiDAR and multispectral data fusion with local filtering and variable window size for estimating tree height. Photogramm Eng Remote Sens 70:589–604

    Google Scholar 

  • Popescu SC, Wynne RH, Nelson RH (2003) Measuring individual tree crown diameter with LiDAR and assessing its influence on estimating forest volume and biomass. Can J Remote Sens 29:564–577

    Google Scholar 

  • Popescu SC, Wynne RH, Scrivani JA (2004) Fusion of small footprint LiDAR and multispectral data to estimate plot-level volume and biomass in deciduous and pine forests in Virginia, USA. For Sci 50:551–565

    Google Scholar 

  • Riaño D, Chuvieco E, Condés S (2004) Generation of crown bulk density for Pinus sylvestris L. form lidar. Remote Sens Environ 92:345–352

    Article  Google Scholar 

  • Shimada M, Muhtar Q, Tadono T, Wakabayashi H (2001) Tree height estimation using an airborne L-band polarimetricinterferometric SAR. In: Geoscience and remote sensing symposium, 2001. IGARSS IEEE 2001 international 3:1430–1432

  • Soille P (2003) Morphological image analysis: principles and applications, 2nd edn. Springer, Berlin

    Google Scholar 

  • Son YM, Lee KH, Park YK, Kim RH, Kwon SD (2008) Management plan for absorption and emission of green house gas in part of forest. Korea Forest Research Institute, Seoul

    Google Scholar 

  • Tange T, Kojima K, Yagi H, Suzuki M (1994) Influence of stand density on the increment of leaf biomass in the young Cryptomeria japonica stand before canopy closing. Bull Tokyo Univ For 92:37–44

    Google Scholar 

  • Van Aardt JAN (2004) An object-oriented approach to forest volume- and above-ground biomass-by-type modeling using small-footprint lidar data for segmentation, estimation, and classification. Ph.D. dissertation, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, p 23

  • Wehr A, Lohr U (1999) Airborne laser scanning-an introduction and overview. ISPRS J Photogramm Remote Sens 54:68–82

    Article  Google Scholar 

  • West GB, Brown JH, Enquist BJ (1999) A general model for the structure and allometry of plant vascular system. Nature 400:664–667

    Article  CAS  Google Scholar 

  • Yu C (2007) Variation of wood basic density, pulp yield and other wood properties for four Eucalyptus clones in Stora Enso Guangxi (China) plantation. Master’s Thesis, Luleå University of Technology, Sweden, p 16

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Acknowledgment

This study was carried out with the support of “Forest Science and Technology Projects (Project No. S120909L010130)” provided by Korea Forest Service.

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Authors and Affiliations

  1. Division of Environmental Science and Ecological Engineering, Korea University, Seoul, 136-701, South Korea

    Doo-Ahn Kwak, Woo-Kyun Lee, Yowhan Son & So-Ra Kim

  2. Division of Forest Resources Information, Korea Forest Research Institute, Seoul, 136-012, South Korea

    Hyun-Kook Cho & Seung-Ho Lee

  3. Center of Excellence in Earth Observing, Schmid College of Science, Chapman University, Orange, CA, 92866, USA

    Menas Kafatos

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  1. Doo-Ahn Kwak
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Correspondence to Woo-Kyun Lee.

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Kwak, DA., Lee, WK., Cho, HK. et al. Estimating stem volume and biomass of Pinus koraiensis using LiDAR data. J Plant Res 123, 421–432 (2010). https://doi.org/10.1007/s10265-010-0310-0

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  • DOI: https://doi.org/10.1007/s10265-010-0310-0

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