Retrieval of forest canopy heights by using large-footprint waveform data assisted by the LiDAR model over hillsides

  • role: First author第一作者
  • Affiliation:

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

  • Email:wangyao@radi.ac.cn
  • Introduction:汪垚(1993— ),男,硕士研究生,研究方向为森林遥感。E-mail:wangyao@radi.ac.cn
Yao WANG12,  
  • role: Corresponding author通信作者
  • Affiliation:

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

  • Email:niwj@radi.ac.cn
  • Introduction:倪文俭(1982— ),男,研究员,研究方向为森林遥感机理模型发展及基于多源遥感数据的森林植被碳储量及其动态变化监测。E-mail:niwj@radi.ac.cn
Wenjian NI1*,  
  • Affiliation:

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

Zhiyu ZHANG1,  
  • Affiliation:

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

Jianli LIU12,  
  • Affiliation:

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    School of Information Science and Technology, Beijing Normal University, Beijing 100875, China

Haoyang YU13,  
  • Affiliation:

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

Dafeng ZHANG12

ملخص

Full waveform data of large-footprint LiDAR are widely used to retrieve global or regional forest canopy heights. However, most studies have focused on forests on relatively flat terrains where the slope is smaller than 20°. Estimating the canopy height of hillside forest stands over mountainous areas with large relief remains a challenge. A model-assisted method is proposed to estimate canopy heights of hillside forest stands by using LiDAR waveforms and overcome the effect of terrains. The adaptability of the method in 0° to 40° is evaluated. We propose a new method and redefine the height index. First, the LiDAR waveform of bare ground is simulated according to given terrain slopes. Second, the LiDAR waveforms of a forest stand and bare ground are aligned according to their signal ending points. Finally, the heights of quarter energy points (i.e., H50 and H75) of the LiDAR waveform of forests are defined relative to the signal ending points, and the heights of quarter energy points (i.e., Hg50 and Hg75) of the LiDAR waveform of bare ground are defined relative to the signal ending points. The relative height indices (i.e., RH50 and RH75) of the forest LiDAR waveform are defined as the difference in the corresponding index of the simulated waveform of forest and bare ground, namely, RH50=H50 − Hg50 and RH75=H75 − Hg75. The newly defined RH50 and RH75 are used to estimate forest canopy heights. The model-assisted method is validated within 0° to 40° terrain slopes and compared with Gaussian decomposition and edge-extent methods. (1) Within the 0° to 20° terrain slopes, the accuracies of estimating forest canopy heights using Gaussian decomposition, edge-extent, and proposed model-assisted methods areR2=0.70, 0.78, and 0.98 and root-mean-square error (RMSE)=2.90 m, 2.48 m, and 0.60 m, respectively. The performance of the proposed method is slightly better than that of the two other methods. (2) Within the 22° to 40° terrain slopes, the accuracies of estimating forest canopy heights using Gaussian decomposition, edge-extent, and proposed model-assisted methods are R2=0.14, 0.28, and 0.97 and RMSE=4.93 m, 4.53 m, and 0.81 m, respectively. The proposed model-assisted method is superior to the two other methods. (3) The estimation accuracy of the model-assisted method within the 0° to 40° terrain slopes is R2=0.97 and RMSE=0.80 m. This model can overcome the effect of the terrain and maintain high accuracy. The method will be further validated using spaceborne LiDAR data in future research. The proposed method can correct the effect of slope over hillsides, and the relative height indices extracted by this method are insensitive to terrain slopes. The proposed method shows a potential for use in the accurate estimation of forest canopy heights over hillsides.

مفهوم

lidar;terrain;waveform broadened;GLAS;forest canopy height

References

  1. 1.
    Allouis T, Durrieu S and Couteron P. 2012. A new method for incorporating hillslope effects to improve canopy-height estimates from large-footprint lidar waveforms. IEEE Geoscience and Remote Sensing Letters, 9(4): 730–734
  2. 2.
    Cao L, Coops N C, Hermosilla T, Innes J, Dai J S and She G H. 2014. Using small-footprint discrete and full-waveform airborne LiDAR metrics to estimate total biomass and biomass components in subtropical forests. Remote Sensing, 6(8): 7110–7135
  3. 3.
    Carabajal C C and Harding D J. 2005. ICESat validation of SRTM C-band digital elevation models. Geophysical Research Letters, 32(22): L22S01
  4. 4.
    Carabajal C C and Harding D J. 2006. SRTM C-band and ICESat laser altimetry elevation comparisons as a function of tree cover and relief. Photogrammetric Engineering and Remote Sensing, 72(3): 287–298
  5. 5.
    Chen Q. 2010. Retrieving vegetation height of forests and woodlands over mountainous areas in the Pacific Coast region using satellite laser altimetry. Remote Sensing of Environment, 114(7): 1610–1627
  6. 6.
    Chi H. 2011. Research on Forest Aboveground Biomass Estimation in China Based on ICESat/GLAS and MODIS Data. Beijing: Institute of Remote Sensing Applications Chinese Academy Sciences
  7. 7.
    Drake J B, Dubayah R O, Clark D B, Knox R G, Blair J B, Hofton M A, Chazdon R L, Weishampel J F and Prince S. 2002. Estimation of tropical forest structural characteristics using large-footprint lidar. Remote Sensing of Environment, 79(2/3): 305–319
  8. 8.
    Dubayah R O and Drake J B. 2000. Lidar remote sensing for forestry. Journal of Forestry, 98(6): 44–46
  9. 9.
    Duong V H, Lindenbergh R, Pfeifer N and Vosselman G. 2008. Single and two epoch analysis of ICESat full waveform data over forested areas. International Journal of Remote Sensing, 29(5): 1453–1473
  10. 10.
    Enßle F, Heinzel J and Koch B. 2014. Accuracy of vegetation height and terrain elevation derived from ICESat/GLAS in forested areas. International Journal of Applied Earth Observation and Geoinformation, 31: 37–44
  11. 11.
    Field C B and Raupach M R. 2004. The Global Carbon Cycle: Integrating Humans, Climate, and the Natural World. Washington: Island Press
  12. 12.
    Harding D J, Lefsky M A, Parker G G and Blair J B. 2001. Laser altimeter canopy height profiles: methods and validation for closed-canopy, broadleaf forests. Remote Sensing of Environment, 76(3): 283–297
  13. 13.
    Hayashi M, Saigusa N, Oguma H and Yamagata Y. 2013. Forest canopy height estimation using ICESat/GLAS data and error factor analysis in Hokkaido, Japan. ISPRS Journal of Photogrammetry and Remote Sensing, 81: 12–18
  14. 14.
    Hilbert C and Schmullius C. 2012. Influence of surface topography on ICESat/GLAS forest height estimation and waveform shape. Remote Sensing, 4(8): 2210–1125
  15. 15.
    Lee S, Ni-Meister W, Yang W Z and Chen Q. 2011. Physically based vertical vegetation structure retrieval from ICESat data: validation using LVIS in White Mountain National Forest, New Hampshire, USA. Remote Sensing of Environment, 115(11): 2776–2785
  16. 16.
    Lefsky M A, Harding D J, Keller M, Cohen W B, Carabajal C C, Del Bom Espirito-Santo F, Hunter M O and De Oliveira Jr R. 2005. Estimates of forest canopy height and aboveground biomass using ICESat. Geophysical Research Letters, 32(22): L22S02
  17. 17.
    Lefsky M A, Keller M, Pang Y, De Camargo P B and Hunter M O. 2007. Revised method for forest canopy height estimation from geoscience laser altimeter system waveforms. Journal of Applied Remote Sensing, 1(1): 013537
  18. 18.
    Nie S, Wang C, Zeng H C, Xi X H and Xia S B. 2015. A revised terrain correction method for forest canopy height estimation using ICESat/GLAS data. ISPRS Journal of Photogrammetry and Remote Sensing, 108: 183–190
  19. 19.
    Pagnutti M and Ryan R E. 2009. Automated DEM validation using ICESat GLAS data//Proceedings of ASPRS/MAPPS 2009 Fall Conference. San Antonio, Texas: ASPRS
  20. 20.
    Pang Y, Lefsky M, Andersen H E, Miller M E and Sherrill K. 2008. Validation of the ICEsat vegetation product using crown-area-weighted mean height derived using crown delineation with discrete return lidar data. Canadian Journal of Remote Sensing, 34(S2): S471–S484
  21. 21.
    Pang Y, Lefsky M, Sun G Q and Ranson J. 2011. Impact of footprint diameter and off-nadir pointing on the precision of canopy height estimates from spaceborne lidar. Remote Sensing of Environment, 115(11): 2798–2809
  22. 22.
    Popescu S C, Zhao K G, Neuenschwander A and Lin C. 2011. Satellite lidar vs. small footprint airborne lidar: comparing the accuracy of aboveground biomass estimates and forest structure metrics at footprint level. Remote Sensing of Environment, 115(11): 2786–2797
  23. 23.
    Ranson K J, Sun G, Knox R G, Levine E R, Weishampel J F and Fifer S T. 2001. Northern forest ecosystem dynamics using coupled models and remote sensing. Remote Sensing of Environment, 75(2): 291–302
  24. 24.
    Rosette J A, North P R J, Suárez J C and Armston J D. 2009. A comparison of biophysical parameter retrieval for forestry using airborne and satellite LiDAR. International Journal of Remote Sensing, 30(19): 5229–5237
  25. 25.
    Rosette J A B, North P R J and Suárez J C. 2008. Vegetation height estimates for a mixed temperate forest using satellite laser altimetry. International Journal of Remote Sensing, 29(5): 1475–1493
  26. 26.
    Smith T M and Urban D L. 1988. Scale and resolution of forest structural pattern. Vegetatio, 74(2/3): 143–150
  27. 27.
    Sun G, Ranson K J, Kimes D S, Blair J B and Kovacs K. 2008. Forest vertical structure from GLAS: an evaluation using LVIS and SRTM data. Remote Sensing of Environment, 112(1): 107–117
  28. 28.
    Sun G Q and Ranson K J. 2000. Modeling lidar returns from forest canopies. IEEE Transactions on Geoscience and Remote Sensing, 38(6): 2617–2626
  29. 29.
    Sun G Q, Ranson K J, Guo Z, Zhang Z, Montesano P and Kimes D. 2011. Forest biomass mapping from lidar and radar synergies. Remote Sensing of Environment, 115(11): 2906–2916
  30. 30.
    Wang C, Tang F X, Li L W, Li G C, Cheng F and Xi X H. 2013. Wavelet analysis for ICESat/GLAS waveform decomposition and its application in average tree height estimation. IEEE Geoscience and Remote Sensing Letters, 10(1): 115–119
  31. 31.
    Wang X Y, Huang H B, Gong P, Liu C X, Li C C and Li W Y. 2014. Forest canopy height extraction in rugged areas with ICESat/GLAS data. IEEE Transactions on Geoscience and Remote Sensing, 52(8): 4650–4657
  32. 32.
    Wulder M A, White J C, Nelson R F, Næsset E, Ørka H O, Coops N C, Hilker T, Bater C W and Gobakken T. 2012. Lidar sampling for large-area forest characterization: a review. Remote Sensing of Environment, 121: 196–209
  33. 33.
    Xing Y Q, De Gier A, Zhang J J and Wang L H. 2010. An improved method for estimating forest canopy height using ICESat-GLAS full waveform data over sloping terrain: a case study in Changbai mountains, China. International Journal of Applied Earth Observation and Geoinformation, 12(5): 385–392
  34. 34.
    Yang W Z, Ni-Meister W and Lee S. 2011. Assessment of the impacts of surface topography, off-nadir pointing and vegetation structure on vegetation lidar waveforms using an extended geometric optical and radiative transfer model. Remote Sensing of Environment, 115(11): 2810–2822

قراءة النص الكامل

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website