Estimation of Tree Heights from Seasonal Airborne LiDAR Data

계절별 항공라이다 자료에 의한 수고 추정

  • Received : 2010.07.06
  • Accepted : 2010.08.22
  • Published : 2010.08.31

Abstract

This paper estimates the tree height using Airborne LiDAR that is obtained for each season to analyze its influence based on a canopyclosure and data fusion. The tree height was estimated by extracting the First Return (RF) from the tree and the Last Return (LR) from the surface of earth to assume each tree via image segmentation and to obtain the height of each tree. Each data on tree height that is collected from seasonal data and the result of tree height acquired from the data fusion were compared. A tree height measuring device was used to measure on site and its accuracy was compared. Also, its applicability on the result of fused data that is obtained through the Airborne LiDAR is examined. As a result of the experiment, the result of image segmentation for an individual tree was closer to the result of site study for 1 meter interval when compared to the 0.5 meter interval of point cloud. In case of the tree height, the application of fused data enables a closer site measurement result than the application of data for each season.

본 논문은 계절별로 획득된 항공라이다 자료로부터 수고를 추정하여 수관울폐도와 자료융합에 따른 영향을 분석하였다. 수고추정은 수목에서 반사되는 신호(First Return : FR)와 지표에서 반사되는 신호(Last Return : LR)를 추출하고, 영상분할을 통해 수목개체를 가정하여 개체목별 수고를 획득하는 방법을 적용하였다. 계절별 자료를 통해 획득한 각 수고 자료와 융합자료로부터 획득한 수고의 결과를 비교하였으며, 수고측정기를 사용하여 현지 측정을 하여 정확성을 비교하고, 항공라이다를 통해 획득한 자료들을 융합한 결과에 대한 그 활용성을 검토하였다. 실험 결과, 수목개체를 위한 영상분할 결과는 0.5미터 점군간격보다 1미터 간격이 현지조사 결과와 가까웠으며, 수목고의 경우 각 계절별 자료보다 융합자료를 활용한 결과가 현지 측정 결과에 접근하고 있음을 알 수 있었다.

Keywords

References

  1. 장안진, 유기윤, 김용일, 이병길 (2006), 컬러항공사진과 LiDAR 데이터를 이용한 수목 개체 및 수고 측정, 대한원격탐사학회지, 대한원격탐사학회, 제 22권, 제 6호, pp. 543-551. https://doi.org/10.7780/kjrs.2006.22.6.543
  2. Ali, S.S., Dare, P. and Jones, S. D. (2008), Fusion of Remotely Sensed Multispectral Imagery and LiDAR Data for Forest Structure Assessment at the Tree Level, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVII, Part. B7, Beijing.
  3. Baltsavias, E. P. (1999), A comparison between photogrammetry and laser scanning, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 54, pp. 83-94. https://doi.org/10.1016/S0924-2716(99)00014-3
  4. Beucher, S. and Lantuejoul, C. (1979), Use of watersheds in contour detection, in Proceedings, International Workshop on Image Processing, CCETT/IRISA, Rennes, France.
  5. Clark Mattehew L., Clark David B. and Roberts Dar A. (2004), Small-footprint lidar estimation of sub-canopy elevation and tree height in a tropical rain forest landscape, Remote Sensing of Environment, Vol. 91, pp. 68-89. https://doi.org/10.1016/j.rse.2004.02.008
  6. Holmgren Johan and Persson Asa (2003), Identitying species of individual trees using airborne laser scanner, Remote Sensing of Environment, Vol. 90, pp. 415-423.
  7. Holmgren Johan, Nilsson Mats and Olsson Hakan (2004), Estimation of Tree Height and Stem Volume on Plots Using Airborne Laser Scanning, Forest Science, Vol. 49, No. 3, pp. 419-428.
  8. Huising, E. J., Gomes Pereira, L. M. (1998), Errors and accuracy estimates of laser data acquired by various laser scanning for topographic applications, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 53, pp. 245-261. https://doi.org/10.1016/S0924-2716(98)00013-6
  9. Kwak, Doo-Ahn, Lee, Woo-Kyun and Lee, Jun-Hak (2007), Detection of individual trees and estimation of tree height using LiDAR data, Journal of Forest Research, Vol. 12, No. 6, pp. 425-434. https://doi.org/10.1007/s10310-007-0041-9
  10. McCombs, John W., Roberts Scott D. and Evans David L. (2003), Influence of Fusing Lidar and Multispectral Imagery on Remotely Sensed Estimates of Stand Density and Mean Tree Height in a Managed Loblolly Pine Plantation, Forest Science, Vol. 49, No. 3, pp. 457-466.
  11. Naesset, E. (1997), Determination of mean tree height of forest stands using airborne laser scanner data, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 52, pp. 49-56. https://doi.org/10.1016/S0924-2716(97)83000-6
  12. Naesset, E. (2002), Determination of Mean Tree Height of Forest Stands by Digital Photogrammetry, Scandinavian Journal of Forest Research, Vol. 17, pp. 446-459. https://doi.org/10.1080/028275802320435469
  13. Nilsson, M. (1996), Estimation of Tree Heights and Stand Volume Using an Airborne Lidar System, Remote Sensing of Enviroment, Vol. 56, No. 1, pp. 1-7. https://doi.org/10.1016/0034-4257(95)00224-3
  14. Popescu, Sorin C. and Wynne, Rondolph H. (2004), Seeing the trees in the forest: using lidar and multispectral data fusion with local filtering and variable window size for estimating tree height, Photogrammetric Engineering and Remote Sensing, Vol. 70, No. 5, pp. 589-604. https://doi.org/10.14358/PERS.70.5.589
  15. Sithole, G. and Vosselman, G. (2004), Experimental comparison of filter algorithms for bare-earth extraction from air-borne laser scanning point clouds, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 59, pp. 85-101. https://doi.org/10.1016/j.isprsjprs.2004.05.004
  16. St-Onge, Benoit A and Achaichia, Nora (2001), Measuring Forest Canopy Height using a Combination of LiDAR and Aerial Photography Data, Internaltional Archives of Photogrammetry and Remote Sensing, Volume XXXN-3/W4 Annapolis, MD, pp. 22-24.