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Simulation of multi-view stereo optical imagery for extraction of forest canopy height

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：yaoyuan19@mails.ucas.ac.cn
  • Introduction：姚远，研究方向为森林遥感。E-mail： yaoyuan19@mails.ucas.ac.cn
YAO Yuan12,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：niwj@aircas.ac.cn
  • Introduction：倪文俭，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@aircas.ac.cn
NI Wenjian12*,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

ZHANG Zhiyu1

resumen

Canopy height is one of important indicators of carbon storage in forest ecosystems. Previous studies have demonstrated that optical stereo imagery held great potential for deriving forest canopy height. However, optical images are easily affected by cloud coverage and rains. The regional mapping of forest canopy height has to be achieved by the synthesis of multi-sensor and multi-temporal imagery. The spatial resolutions and viewing angles of existing spaceborne stereoscopic systems are quite different. It is essential to make a systematic investigation about the impact of image spatial resolutions and viewing angles on the vertical distribution of stereoscopic point clouds, which is the basis for the synergy of images acquired at different seasons even by different cameras. The theoretical model for the simulation of optical stereo imagery over forested areas is necessary for such studies. The LandStereo is such kind of model, which can simulate the along-track(only In-track viewing) stereoscopic imagery like ALOS/PRISM and ZY-3. However, the current version of LandStereo has no mode to simulate the along-track(including In-track and Cross-track) stereoscopic imagery like Worldview-1/2/3.Therefore, this study reported the modification of the LandStereo model to have it being able to simulate images acquired by any possible viewing directions in forest areas. Firstly, the calculation method of linear array projection center coordinates is improved, from originally only considering the change of observation altitude angle to considering the change of azimuth angle and altitude angle. Secondly, Rigorous imaging geometric model is improved to obtain RPC of images acquired by any possible viewing directions. Based on the improved LandStereo model, the bare and mountainous forest images with altitude angle of 75° and azimuth angle of 0°, 90° , and 225° are simulated to verify the accuracy and extract forest canopy height.The surface elevation extracted by the improved LandStereo model is consistent with the input DTM with high accuracy (r=0.99, RMSE=1.507), which proves the geometric accuracy of the improved LandStereo model. There are certain differences in the extraction accuracy of forest canopy height between stereo images of different angles.The results showed that the modified model could correctly simulate the stereoscopic features of forest canopy with given view direction, also initially demonstrated that view angle was an important factor affecting the estimation accuracy of forest canopy height by stereoscopic images.

palabra clave

forest height;multi-view;stereoscopic observations;imagery simulation;LandStereo;POV-ray;vegetation optical model

References

  1. 1.
    Avtar R and Sawada H. 2013. Use of DEM data to monitor height changes due to deforestation. Arabian Journal of Geosciences, 6(12): 4859-4871
  2. 2.
    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
  3. 3.
    Duncanson L I, Niemann K O and Wulder M A. 2010. Estimating forest canopy height and terrain relief from GLAS waveform metrics. Remote Sensing of Environment, 114(1): 138-154
  4. 4.
    Hobi M L and Ginzler C. 2012. Accuracy assessment of digital surface models based on WorldView-2 and ADS80 stereo remote sensing data. Sensors, 12(5): 6347-6368
  5. 5.
    Khati U, Lavalle M and Singh G. 2019. Spaceborne tomography of multi-species Indian tropical forests. Remote Sensing of Environment, 229: 193-212
  6. 6.
    Lei Y, Treuhaft R and Gonçalves F. 2021. Automated estimation of forest height and underlying topography over a Brazilian tropical forest with single-baseline single-polarization TanDEM-X SAR interferometry. Remote Sensing of Environment, 252: 112132
  7. 7.
    Liang S L, Bai R, Chen X N, Cheng J, Fan W J, He T, Jia K, Jiang B, Jiang L M, Jiao Z T, Liu Y B, Ni W J, Qiu F, Song L L, Sun L, Tang B H, Wen J G, Wu G P, Xie D H, Yao Y J, Yuan W P, Zhang Y G, Zhang Y Z, Zhang Y T, Zhang X T, Zhao T J and Zhao X. 2020. Review of China's land surface quantitative remote sensing development in 2019. Journal of Remote Sensing, 24(6): 618-671
  8. 8.
    Montesano P M, Neigh C, Sun G Q, Duncanson L, Van Den Hoek J and Ranson K J. 2017. The use of sun elevation angle for stereogrammetric boreal forest height in open canopies. Remote Sensing of Environment, 196: 76-88
  9. 9.
    Neigh C S R, Masek J G, Bourget P, Cook B, Huang C Q, Rishmawi K and Zhao F. 2014. Deciphering the precision of stereo IKONOS canopy height models for US forests with G-LiHT Airborne LiDAR. Remote Sensing, 6(3): 1762-1782
  10. 10.
    Ni W J, Guo Z F, Zhang Z Y, Sun G Q and Huang W L. 2012. Semi-automatic extraction of digital surface model using ALOS/PRISM data with ENVI//2012 IEEE International Geoscience and Remote Sensing Symposium. Munich: IEEE: 6557-6560
  11. 11.
    Ni W J, Ranson K J, Zhang Z Y and Sun G Q. 2014. Features of point clouds synthesized from multi-view ALOS/PRISM data and comparisons with LiDAR data in forested areas. Remote Sensing of Environment, 149: 47-57
  12. 12.
    Ni W J, Zhang D F, Wang Y, Pang Y, Zhang Z Y, Liu J L, He Y T and Guo W. 2018. Extraction of forest height by using GF-2 cross-track stereo images. Journal of Remote Sensing, 22(3): 392-399
  13. 13.
    Ni W J, Zhang Z Y, Sun G Q and Liu Q H. 2019. Modeling the stereoscopic features of mountainous forest landscapes for the extraction of forest heights from stereo imagery. Remote Sensing, 11(10): 1222
  14. 14.
    Persson H J and Perko R. 2016. Assessment of boreal forest height from WorldView-2 satellite stereo images. Remote Sensing Letters, 7(12): 1150-1159
  15. 15.
    Potapov P, Li X Y, Hernandez-Serna A, Tyukavina A, Hansen M C, Kommareddy A, Pickens A, Turubanova S, Tang H, Silva C E, Armston J, Dubayah R, Blair J B and Hofton M. 2021. Mapping global forest canopy height through integration of GEDI and Landsat data. Remote Sensing of Environment, 253: 112165
  16. 16.
    Qi W L, Lee S K, Hancock S, Luthcke S, Tang H, Armston J and Dubayah R. 2019. Improved forest height estimation by fusion of simulated GEDI Lidar data and TanDEM-X InSAR data. Remote Sensing of Environment, 221: 621-634
  17. 17.
    St-Onge B, Hu Y and Vega C. 2008. Mapping the height and above-ground biomass of a mixed forest using lidar and stereo Ikonos images. International Journal of Remote Sensing, 29(5): 1277-1294
  18. 18.
    Tao C V and Hu Y. 2001. A comprehensive study of the rational function model for photogrammetric processing. Photogrammetric Engineering and Remote Sensing, 67(12): 1347-1357
  19. 19.
    Tian J J, Schneider T, Straub C, Kugler F and Reinartz P. 2017. Exploring digital surface models from nine different sensors for forest monitoring and change detection. Remote Sensing, 9(3): 287

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