سابِق|تال

Data processing methods and applications of airborne LiDAR bathymetry

  • role： First author第一作者
  • Affiliation：

    School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China

  • Email：liuyongmingA401@outlook.com
  • Introduction：刘永明(1990—　)，男，博士研究生，研究方向为水深水质定量遥感。E-mail：liuyongmingA401@outlook.com
Yongming LIU1,  
  • role： Corresponding author通信作者
  • Affiliation：

    School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China

    Guangdong Engineering Research Center of Water Environment Remote Sensing Monitoring, Guangzhou 510275, China

    Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, Guangzhou 510275, China

  • Email：eesdrr@mail.sysu.edu.cn
  • Introduction：邓孺孺(1963—　)，男，教授，研究方向为水质遥感与大气环境遥感。E-mail：eesdrr@mail.sysu.edu.cn
Ruru DENG123*,  
  • Affiliation：

    School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China

Yan QIN1,  
  • Affiliation：

    School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China

Yeheng LIANG1

ملخص

Aside from sonar systems, Airborne LIDAR Bathymetry (ALB) has become the most reliable depthometer. With the commercialization of ALB, several companies have produced powerful ALB, and research institutions have obtained the full-waveform data of water. Meanwhile, several algorithms have been proposed to process the signal of ALB. In this work, we introduce the theoretical basis of ALB and then review algorithms of correction for pulse stretching and peak finding of full waveform. Then, we analyze the main influencing factors of accuracy, including water depth, water color, and reflectance of substrates. We also provide an overview of the new application of ALB in substrate classification. In specific, ALB can help retrieve information from full waveform to the maximum extent. We draw the following conclusions: (1) Pulse stretching is mainly caused by the topography of substrate, whereas algorithms for correcting pulse stretching have been developed under the consideration of general terrain slope or incident angle of pulse. The complex topography of substrate should be considered, especially for the application in coral reef, where substrates distribute inhomogeneity. (2) Algorithms of peak finding of full waveform can be separated into three kinds: echo detection, mathematical approximation, and deconvolution. Echo detection methods run fast but are influenced by environmental noise more easily. The object function of mathematical approximation methods is difficult to be solved, but environmental parameters such as water attenuation coefficient can be derived. Deconvolution methods are stable but need to take effective measures to suppress noise. (3) The proposed algorithm cannot work well for extremely shallow water, especially at depths within centimeter level, but polarization lidar may solve the problem in the future. Low water quality and low reflectance of substrate reduce signal and noise ratio. Thus, new algorithms need to be developed for these conditions in the future. (4) The new application of ALB in substrate classification and data fusion with hyperspectral image indicates that further information in full waveform of water should be retrieved in the future.

مفهوم

airborne LiDAR bathymetry;water depth;substrate classification;full waveform;hyperspectral

References

  1. 1.
    Abady L, Bailly J S, Baghdadi N, Pastol Y and Abdallah H. 2014. Assessment of quadrilateral fitting of the water column contribution in lidar waveforms on bathymetry estimates. IEEE Geoscience and Remote Sensing Letters, 11(4): 813–817
  2. 2.
    Abdallah H, Baghdadi N, Bailly J S, Pastol Y and Fabre F. 2012. Wa-LiD: a new LiDAR simulator for waters. IEEE Geoscience and Remote Sensing Letters, 9(4): 744–748
  3. 3.
    Abdallah H, Bailly J S, Baghdadi N N, Saint-Geours N and Fabre F. 2013. Potential of space-borne LiDAR sensors for global bathymetry in coastal and inland waters. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(1): 202–216
  4. 4.
    Allouis T, Bailly J S, Pastol Y and Le Roux C. 2010. Comparison of LiDAR waveform processing methods for very shallow water bathymetry using Raman, near-infrared and green signals. Earth Surface Processes and Landforms, 35(6): 640–650
  5. 5.
    Axelsson A. 2010. Rapid topographic and bathymetric reconnaissance using airborne lidar. Proceedings of SPIE - The International Society for Optical Engineering: 783503–783503-10
  6. 6.
    Bailly J S, Le Coarer Y, Languille P, Stigermark C J and Allouis T. 2010. Geostatistical estimations of bathymetric LiDAR errors on rivers. Earth Surface Processes and Landforms, 35(10): 1199–1210
  7. 7.
    Battaglia N F. 2010. Utility of Satellite LIDAR Waveform Data in Shallow Water. Monterey CA: Naval Postgraduate School
  8. 8.
    Bi S P, Bie J and Zhang Y. 2012. Application of airborne LiDAR to coastial topographic survey. Marine Geology Frontiers, 28(11): 59–64 (
  9. 9.
    Bouhdaoui A, Bailly J S, Baghdadi N and Abady L. 2014. Modeling the water bottom geometry effect on peak time shifting in LiDAR bathymetric waveforms. IEEE Geoscience and Remote Sensing Letters, 11(7): 1285–1289
  10. 10.
    Brown E D, Churnside J H, Collins R L, Veenstra T, Wilson J J and Abnett K. 2002. Remote sensing of capelin and other biological features in the North Pacific using lidar and video technology. ICES Journal of Marine Science, 59(5): 1120–1130
  11. 11.
    Chauve A, Mallet C, Bretar F, Durrieu S, Pierrot-Deseilligny M and Puech W. 2007. Processing full-waveform lidar data: modelling raw signals//International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 2007. Espoo, Finland: [s.n.]: 102–107
  12. 12.
    Cheng H. 2015. Study on the Signal Processing of Lidar. Chengdu: Graduate University of Chinese Academy of Sciences (The Institute of Optics and Electronics)
  13. 13.
    Collin A, Archambault P and Long B. 2008a. Mapping the shallow water seabed habitat with the SHOALS. IEEE Transactions on Geoscience and Remote Sensing, 46(10): 2947–2955
  14. 14.
    Collin A, Long B and Archambault P. 2008b. The use of the SHOALS waveforms to mapping habitat within the seamless benthoscape//Proceedings of IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2008. Boston, Massachusetts, USA: IEEE: 1144–1147 [DOI: 10.1109/IGARSS.2008.4779202]
  15. 15.
    Costa B M, Battista T A and Pittman S J. 2009. Comparative evaluation of airborne LiDAR and ship-based multibeam SoNAR bathymetry and intensity for mapping coral reef ecosystems. Remote Sensing of Environment, 113(5): 1082–1100
  16. 16.
    Deng R R, He Z J and Chen X X. 2003. Model for water pollution remote sensing based on double scattering and its application on the Zhujiang River Estuary. Acta Oceanologica Sinica, 25(6): 69–78 (
  17. 17.
    Doneus M, Doneus N, Briese C, Pregesbauer M, Mandlburger G and Verhoeven G. 2012. Airborne laser bathymetry–detecting and recording submerged archaeological sites from the air. Journal of Archaeological Science, 40(4): 2136–2151
  18. 18.
    Feigels V I. 1992. Lidars for oceanological research: criteria for comparison, main limitations, perspectives//Proceedings of the SPIE 1750, Ocean Optics XI. San Diego, CA, United States: SPIE, 1750: 473–484 [DOI: 10.1117/12.140676]
  19. 19.
    Fernandez-Diaz J C, Glennie C L, Carter W E, Shrestha R L, Sartori M P, Singhania A, Legleiter C J and Overstreet B T. 2014. Early results of simultaneous terrain and shallow water bathymetry mapping using a single-wavelength airborne lidar sensor. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 7(2): 623–635
  20. 20.
    Goodman J A, Purkis S J and Phinn S R. 2013. Coral Reef Remote Sensing. Dordrecht, Netherlands: Springer
  21. 21.
    Guenther G and Thomas R. 1983. System design and performance factors for airborne laser hydrography//Proceedings of Oceans’83. San Francisco, CA, USA: IEEE: 425–430 [DOI: 10.1109/OCEANS.1983.1152162]
  22. 22.
    Guenther G C, Cunningham A G, Larocque P E and Reid D J. 2000. Meeting the accuracy challenge in airborne lidar bathymetry.Proc. earsel Symp. Workshop on Lidar Remote Sensing of Land and Sea: (1), 1.
  23. 23.
    Guenther G C and Mesick H C. 1988. Analysis of airborne laser hydrography waveforms. Orlando Technical Symposium. International Society for Optics and Photonics, 925: 232–241
  24. 24.
    Guenther G C. 2007. Airborne lidar bathymetry//Maune D. Applications: The DEM Users Manual. 2nd ed. Bethesda: American Society for Photogrammetry and Remote Sensing
  25. 25.
    Harsdorf S and Reuter R. 2000. Stable deconvolution of noisy lidar signals//Proceedings of EARSeL-SIG-Workshop LIDAR. Dresden: [s.n.]
  26. 26.
    Hossain M S, Bujang J S, Zakaria M H and Hashim M. 2014. The application of remote sensing to seagrass ecosystems: an overview and future research prospects. International Journal of Remote Sensing, 36(1): 61–114
  27. 27.
    Jacovitti G and Scarano G. 1993. Discrete time techniques for time delay estimation. IEEE Transactions on Signal Processing, 41(2): 525–533
  28. 28.
    Jutzi B and Stilla U. 2006. Range determination with waveform recording laser systems using a Wiener Filter. ISPRS Journal of Photogrammetry and Remote Sensing, 61(2): 95–107
  29. 29.
    Kinzel P J, Legleiter C J and Nelson J M. 2013. Mapping river bathymetry with a small footprint green lidar: applications and challenges. JAWRA Journal of the American Water Resources Association, 49(1): 183–204
  30. 30.
    Kinzel P J, Wright C W, Nelson J M and Burman A R. 2007. Evaluation of an experimental LiDAR for surveying a shallow, braided, sand-bedded river. Journal of Hydraulic Engineering, 133(7): 838–842
  31. 31.
    Klemas V. 2016. Beach profiling and LIDAR bathymetry: an overview with case studies. Journal of Coastal Research, 27(6): 1019–1028
  32. 32.
    Klonowski W M, Fearns P R C S and Lynch M J. 2007. Retrieving key benthic cover types and bathymetry from hyperspectral imagery. Journal of Applied Remote Sensing, 1(1): 6656–6659
  33. 33.
    Kopilevich Y I, Feygels V I, Tuell G H and Surkov A. 2005. Measurement of ocean water optical properties and seafloor reflectance with scanning hydrographic operational airborne lidar survey (SHOALS): I. Theoretical background//Proceedings of the SPIE 5885, Remote Sensing of the Coastal Oceanic Environment. San Diego, California, United States: SPIE, 5585: 58850D [DOI: 10.1117/12.618923]
  34. 34.
    Lee Z, Carder K L, Mobley C D, Steward R G and Patch J S. 1999. Hyperspectral remote sensing for shallow waters. 2. Deriving bottom depths and water properties by optimization. Applied Optics, 38(18): 3831–3843
  35. 35.
    Lee Z, Casey B, Arnone R, Weidemann A, Parsons R, Montes M J, Gao B C, Goode W, Davis C and Dye J. 2007. Water and bottom properties of a coastal environment derived from Hyperion data measured from the EO-1 spacecraft platform. Journal of Applied Remote Sensing, 1(1): 011502
  36. 36.
    Lee Z, Shang S L, Lin G, Chen J and Doxaran D. 2016. On the modeling of hyperspectral remote-sensing reflectance of high-sediment-load waters in the visible to shortwave-infrared domain. Applied Optics, 55(7): 1738–1750
  37. 37.
    Legleiter C J, Overstreet B T, Glennie C L, Pan Z G, Fernandez-Diaz J C and Singhania A. 2016. Evaluating the capabilities of the CASI hyperspectral imaging system and Aquarius bathymetric LiDAR for measuring channel morphology in two distinct river environments. Earth Surface Processes and Landforms, 41(3): 344–363
  38. 38.
    Li K, Tong X C, Zhang Y S, Ha C L and Shen E H. 2015. Inversion of diffuse attenuation coefficient spectral in the yellow sea/East China Sea and evaluation of laser bathymetric performance. Journal of Remote Sensing, 19(5): 761–769 (
  39. 39.
    Lucy L B. 1974. An iterative technique for the rectification of observed distributions. Astronomical Journal, 79(6): 745–754
  40. 40.
    Ma H C and Li Q. 2009. Modified EM algorithm and its application to the decomposition of laser scanning waveform data. Journal of Remote Sensing, 13(1): 35–41 (
  41. 41.
    Mallet C and Bretar F. 2009. Full-waveform topographic lidar: state-of-the-art. ISPRS Journal of Photogrammetry and Remote Sensing, 64(1): 1–16
  42. 42.
    Mallet C, Lafarge F, Bretar F, Soergel U and Heipke C. 2013. Lidar waveform modeling using a marked point process. IEEE International Conference on Image Processing. IEEE, 2013: 1713–1716
  43. 43.
    Mandlburger G, Pfennigbauer M and Pfeifer N. 2013. Analyzing near water surface penetration in laser bathymetry-a case study at the River Pielach. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, Ⅱ-5/W2: 175–180 [DOI: 10.5194/isprsannals-Ⅱ-5-W2-175-2013]
  44. 44.
    Mitchell S, Thayer J P and Hayman M. 2010. Polarization lidar for shallow water depth measurement. Applied Optics, 49(36): 6995–7000
  45. 45.
    Mobley C D, Zhang H and Voss K J. 2003. Effects of optically shallow bottoms on upwelling radiances: bidirectional reflectance distribution function effects. Limnology and Oceanography, 48(1part2): 337–345
  46. 46.
    Mobley C D. 1994. Light and Water: Radiative Transfer in Natural Waters. San Diego: Academic Press
  47. 47.
    Muirhead K and Cracknell A P. 1986. Airborne lidar bathymetry. International Journal of Remote Sensing, 7(5): 597–614
  48. 48.
    Nayegandhi A, Brock J C and Wright C W. 2009. Small-footprint, waveform-resolving lidar estimation of submerged and sub-canopy topography in coastal environments. International Journal of Remote Sensing, 30(4): 861–878
  49. 49.
    Nordin L. 2006. Analysis of Waveform Data from Airborne Laser Scanner Systems. North Province: Luleå University of Technology
  50. 50.
    Pan Z G, Glennie C, Hartzell P, Fernandez-Diaz J, Legleiter C and Overstreet B. 2015. Performance assessment of high resolution airborne full waveform lidar for shallow river bathymetry. Remote Sensing, 7(5): 5133–5159
  51. 51.
    Pan Z G, Glennie C L, Fernandez-Diaz J C, Legleiter C J and Overstreet B. 2016. Fusion of LiDAR orthowaveforms and hyperspectral imagery for shallow river bathymetry and turbidity estimation. IEEE Transactions on Geoscience and Remote Sensing, 54(7): 4165–4177
  52. 52.
    Park J Y, Ramnath V and Tuell G. 2014. Using lidar waveforms to detect environmental hazards through visualization of the water column. Oceans IEEE, 43: 1–5.
  53. 53.
    Parker H and Sinclair M. 2012. The successful application of Airborne LiDAR Bathymetry surveys using latest technology//Proceedings of Yeosu OCEANS, 2012. Yeosu: IEEE: 1–4 [DOI: 10.1109/OCEANS-Yeosu.2012.6263588]
  54. 54.
    Parrish C E and Nowak R D. 2009. Improved approach to LIDAR airport obstruction surveying using full-waveform data. Journal of Surveying Engineering, 135(2): 72–82
  55. 55.
    Parrish C E, Jeong I, Nowak R D and Smith R B. 2011. Empirical comparison of full-waveform lidar algorithms. Photogrammetric Engineering and Remote Sensing, 77(8): 825–838
  56. 56.
    Pe’eri S and Philpot W. 2007. Increasing the existence of very shallow-water LIDAR measurements using the red-channel waveforms. IEEE Transactions on Geoscience and Remote Sensing, 45(5): 1217–1223 [DOI: 10.1109/TGRS.2007.894584]
  57. 57.
    Persson Å, Söderman U, Töpel J and Ahlberg S. 2005. Visualization and analysis of full-waveform airborne laser scanner data. Proceedings of SPIE-The International Society for Optical Engineering, 36(3), 103–108.
  58. 58.
    Pfennigbauer M, Ullrich A, Steinbacher and Aufleger M. 2011. High-resolution hydrographic airborne laser scanner for surveying inland waters and shallow coastal zones//Proceedings of the SPIE 8037, Laser Radar Technology and Applications XVI. Orlando, Florida, United States: SPIE, 8037: 803706 [DOI: 10.1117/12.883910]
  59. 59.
    Pruksch M and Fleischmann F. 1998. Positive iterative deconvolution in comparison to richardson-lucy like algorithms//Albrecht R, Hook R N and Bushouse H A, eds. Astronomical Data Analysis Software and Systems VⅡ: ASP Conference Series. [s.l.]: Astronomical Society of the Pacific, 145: 496–499
  60. 60.
    Reif M K, Macon C L and Wozencraft J M. 2012. Post-katrina land-cover, elevation, and volume change assessment along the south shore of lake pontchartrain, louisiana, U.S.A. Journal of Coastal Research, 62: 30–39
  61. 61.
    Roncat A, Wagner W, Melzer T and Ullrich A. 2008. Echo detection and localization in full-waveform airborne laser scanner data using the averaged square difference function estimator. Photogrammetric Journal of Finland, 21(1): 62–75
  62. 62.
    Steinvall O K, Koppari K R, Lejdebrink U, Winell J, Nilsson M, Ellsen R and Gjellan E. 1996. Depth-sounding lidar: performance and models. Proceedings of the SPIE 2748, Laser Radar Technology and Applications. Orlando, FL: SPIE, 2748: 18–38 [DOI: 10.1117/12.243551]
  63. 63.
    Tuell G, Barbor K and Wozencraft J. 2010. Overview of the coastal zone mapping and imaging lidar (CZMIL): a new multisensor airborne mapping system for the U.S. army corps of engineers//Proceedings of the SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI. Orlando, Florida, United States: SPIE, 7695: 76950R [DOI: 10.1117/12.851905]
  64. 64.
    Tuell G H, Feygels V, Kopilevich Y, Weidemann A D, Cunningham A G, Mani R, Podoba V, Ramnath V, Park J Y and Aitken J. 2005. Measurement of ocean water optical properties and seafloor reflectance with scanning hydrographic operational airborne lidar survey (SHOALS): Ⅱ. Practical results and comparison with independent data//Proceedings of the SPIE 5885, Remote Sensing of the Coastal Oceanic Environment. San Diego, California, United States: SPIE, 5885: 58850E [DOI: 10.1117/12.619215]
  65. 65.
    Tuell G H and Park J Y. 2004. Use of SHOALS bottom reflectance images to constrain the inversion of a hyperspectral radiative transfer model//Proceedings of the SPIE 5412, Laser Radar Technology and Applications IX. Orlando, FL: SPIE, 185–193 [DOI: 10.1117/12.564929]
  66. 66.
    Tulldahl H M and Wikström S A. 2012. Classification of aquatic macrovegetation and substrates with airborne lidar. Remote Sensing of Environment, 121: 347–357
  67. 67.
    Wagner W, Roncat A, Melzer T and Ullrich A. 2007. Waveform analysis techniques in airborne laser scanning. Swiss Federal Institute of Technology Zürich, 3(1): 602–605
  68. 68.
    Wagner W, Ullrich A, Ducic V, Melzer T and Studnicka N. 2006. Gaussian decomposition and calibration of a novel small-footprint full-waveform digitising airborne laser scanner. ISPRS Journal of Photogrammetry and Remote Sensing, 60(2): 100–112
  69. 69.
    Wang A P, Zhang G Y and Liu F. 2009. Research and application of EM algorithm. Computer Technology and Development, 19(9): 108–110 (
  70. 70.
    Wang C K and Philpot W D. 2007. Using airborne bathymetric lidar to detect bottom type variation in shallow waters. Remote Sensing of Environment, 106(1): 123–135
  71. 71.
    Wang C S, Li Q Q, Liu Y X, Wu G F, Liu P and Ding X L. 2015. A comparison of waveform processing algorithms for single-wavelength LiDAR bathymetry. ISPRS Journal of Photogrammetry and Remote Sensing, 101: 22–35
  72. 72.
    Wong H and Antoniou A. 1991. Characterization and decomposition of waveforms for Larsen 500 airborne system. IEEE Transactions on Geoscience and Remote Sensing, 29(6): 912–921
  73. 73.
    Wozencraft J M and Park J Y. 2013. Integrated LiDAR and hyperspectral//Goodman J, Purkis S and Phinn S, eds. Coral Reef Remote Sensing. Dordrecht, Netherlands: Springer [DOI: 10.1007/978-90-481-9292-2_7]
  74. 74.
    Wozencraft J M, Tuell G H and Philpot W D. 2003. Fusion of hyperspectral and bathymetric laser data in kaneohe bay, hawaii. Proc Spie, 5093: 517–527
  75. 75.
    Wu J Y, van Aardt J A N and Asner G P. 2011. A comparison of signal deconvolution algorithms based on small-footprint LiDAR waveform simulation. IEEE Transactions on Geoscience and Remote Sensing, 49(6): 2402–2414
  76. 76.
    Xu Q Y, Yang K T, Wang X B and Xu D S. 2002. Blue-Green Lidar Ocean Survey. Beijing: National Defense Industry Press
  77. 77.
    Ye X S. 2010. Research on Principle and Data Processing Methods of Airborne Laser Bathymetric Technique. Zhengzhou: PLA Information Engineering University
  78. 78.
    Zavalas R, Ierodiaconou D, Ryan D, Rattray A and Monk J. 2014. Habitat classification of temperate marine macroalgal communities using bathymetric LiDAR. Remote Sensing, 6(3): 2154–2175
  79. 79.
    Zhou J P, Zhang A W and Wang S M. 2013. Processing and application of small-footpring full-waveform airborne LiDAR data. Bulletin of Surveying and Mapping, 24(1): 10–13, 24 (
  80. 80.
    Zhou L. 2013. Marine Geodesy. Beijing: Science Press
  81. 81.
    Zou M Y. 2001. Deconvolution and Signal Recovery. Beijing: National Defense Industry Press

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