GIS MODELING OF FOREST COVER ON THE BASIS OF AIRBORNE LASER SCANNING

https://doi.org/10.24057/2414-9179-2015-1-21-420-427

View or download the article (Rus)

About the Authors

I. G. Rizaev

Kuban State University, Krasnodar, Russia
Russian Federation

A. V. Pogorelov

Kuban State University, Krasnodar, Russia
Russian Federation

M. V. Antonenko

Kuban State University, Krasnodar, Russia
Russian Federation

M. V. Kuzyakina

Kuban State University, Krasnodar, Russia
Russian Federation

Abstract

The canopy height models (CHM) derived on the basis of laser scanning technology become popular due to the several important factors. On the one hand, it demonstrates an accuracy of discrete laser points, while on the other hand there is a wide range of image processing methods for their analysis and extraction forest parameters. The remarkable feature of the CHM is that it contains the artifacts representing the local minima (or pits) within tree crowns. Currently there is no clear explanation for existence of these artifacts: they can appear from the data acquisition to the data processing. These artifacts are very unwanted, because they might badly influence the processing of the CHM, such as segmentation of crowns and calculation of forest parameters. In this paper, we propose an original approach to remove these artifacts during creating CHM in a GIS environment.

Keywords

GIS, forest cover, canopy height models, airborne laser scanning.

References

  1. Axelsson P. DEM generation from laser scanner data using adaptive TIN models // International Archives of Photogrammetry and Remote Sensing. 2000. Vol. 33, part B4/1, P. 110–117.
  2. Ben-Arie J.R., Hay G.J., Powers R.P., Castilla G., St-Onge B. Development of a pit filling algorithm for LiDAR canopy height models // Computers & Geosciences. 2009. Vol. 35, No 9, P. 1940–1949.
  3. Brandtberg T., Warner T.A., Landenberger R.E., McGraw J.B. Detection and analysis of individual leaf-off tree crowns in small footprint, high sampling density lidar data from the eastern deciduous forest in North America // Remote Sensing of Environment. 2003. V. 85, No 3, P. 290–303.
  4. Gonzalez R.C., Woods R.E. Digital Image Processing, 2nd edition. Prentice Hall. 2002. 793 p.
  5. Hosoi F., Matsugami H., Watanuki K., Shimizu Y., Omasa K. Accurate detection of tree apexes in coniferous canopies from airborne scanning light detection and ranging images based on crown-extraction filtering // Journal of Applied Remote Sensing. 2012. Vol. 6, 13 p.
  6. 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 Transactions on Geoscience and Remote Sensing. 2001. Vol. 39, No 5, P. 969–975.
  7. Hyyppä J., Inkinen M. Detecting and estimating attributes for single trees using laser scanner // The Photogrammetric Journal of Finland. 1999. Vol. 16, No 2, P. 27–43.
  8. Jakubowski M.K., Li W., Guo Q., Kelly M. Delineating Individual Trees from Lidar Data: A Comparison of Vector- and Raster-based Segmentation Approaches // Remote Sensing. 2013. Vol. 5, No 9, P. 4163–4186.
  9. Kankare V., Räty M., Yu X., Holopainen M., Vastaranta M., Kantola T., Hyyppä J., Hyyppä H., Alho P., Viitala R. Single tree biomass modelling using airborne laser scanning // ISPRS Journal of Photogrammetry and Remote Sensing. 2013. Vol. 85, P. 66–73.
  10. Khosravipour A., A. K. Skidmore, M. Isenburg, T. Wang, Hussin Y. A. Generating Pit-free Canopy Height Models from Airborne Lidar // Photogrammetric Engineering & Remote Sensing. 2014. Vol. 80, No 9, 2014, P. 863–872.
  11. Leckie D., Gougeon F., Hill D., Quinn R., Armstrong L., Shreenan R. Combined high-density lidar and multispectral imagery for individual tree crown analysis // Can. J. Remote Sensing. 2003. Vol. 29, No 5, P. 633–649.
  12. Li W., Guo Q., Jakubowski M.K., Kelly M. A New Method for Segmenting Individual Trees from the Lidar Point Cloud // Photogrammetric Engineering & Remote Sensing. 2012. Vol. 78, No 1, P. 75–84.
  13. Maltamo M., Eerikainen K., Pitkanen J., Hyyppa J., Vehmas M. Estimation of timber volume and stem density based on scanning laser altimetry and expected tree size distribution functions // Remote Sensing of Environment. 2004a. Vol. 90, No 3, P. 319–330.
  14. Maltamo M., Mustonen K., Hyyppa J., Pitkanen J., Yu X. The accuracy of estimating individual tree variables with airborne laser scanning in a boreal nature reserve // Canadian Journal of Forest Research. Vol. 34, No 9, 2004b, P. 1791–1801.
  15. Mather P.M. Computer Processing of Remotely-Sensed Images: An Introduction, 3rd edition. John Wiley and Sons, Chichester. 2004. 324 p.
  16. Nelson R., Short A., Valenti M. Measuring biomass and carbon in Delaware using an airborne profiling LIDAR // Scandinavian Journal of Forest Research. 2004. Vol. 19, No 6, P. 500–511.
  17. Nixon M.S., Aguado A.S. Feature Extraction & Image Processing for Computer Vision, 3rd edition. Academic Press. 2012. 609 p.
  18. Persson A., Holmgren J., Soderman U. Detecting and measuring individual trees using an airborne laser scanner // Photogrammetric Engineering & Remote Sensing. 2002. Vol. 68, No 9, P. 925–932.
  19. Puttonen E., Litkey P., Hyyppa J. Individual Tree Species Classification by Illuminated-Shaded Area Separation // Remote Sensing, 2010. Vol. 2, No 1, P. 19–35.
  20. Ronnholm P., Hyyppa J., Hyyppa H., Haggren H., Yu X., Kaartinen H. Calibration of laser-derived tree height estimates by means of photogrammetric techniques // Scandinavian Journal of Forest Research. 2004. Vol. 19, No 6, P. 524–528.
  21. Rowell E., Seielstad C., Vierling L., Queen L., Shepperd W. Using Laser Altimetry-based Segmentation to Refine Automated Tree Identification in Managed Forests of the Black Hills, South Dakota // Photogrammetric Engineering & Remote Sensing. 2006. Vol. 72, No 12, P. 1379–1388.
  22. Russ J.C. The Image Processing Handbook, 6th edition. CRC Press. 2011. 885 p.
  23. Shamsoddini A., Turner R., Trinder J.C. Improving lidar-based forest structure mapping with crown-level pit removal // Journal of Spatial Science. 2013. Vol. 58, No 1, P. 29–51.
  24. Shan J., Toth Ch. K. Topographic laser ranging and scanning: principles and processing. CRC Press (Taylor & Francis Group). 2008. 590 p.
  25. Simard M., Pinto N., Fisher J.B., Baccini A. Mapping forest canopy height globally with spaceborne lidar // Journal of Geophysical Research. 2011. Vol. 116, No G4, P. 1–12.
  26. St-Onge B.A. Estimating individual tree heights of the boreal forest using airborne laser altimetry and digital videography // ISPRS Journal of Photogrammetry and Remote Sensing. 1999. Vol. 32, part 3/W14, P. 179–185.
  27. Turner R. An airborne Lidar canopy segmentation approach for estimating above-ground biomass in coastal eucalypt forests, PhD thesis, University of New South Wales, Sydney, Australia. 2006. 354 p.
  28. Wu S., Li J., Huang G.H. A study on DEM-derived primary topographic attributes for hydrologic applications: Sensitivity to elevation data resolution // Applied Geography. 2008. Vol. 28, No 3, P. 210–223.
  29. Yu X., Hyyppa J., Vastaranta M., Holopainen M., Viitala R. Predicting individual tree attributes from airborne laser point clouds based on the random forests technique // ISPRS Journal of Photogrammetry and Remote Sensing. 2011. Vol. 66, No 1, P. 28–37.
  30. Zhao D., Pang Y., Li Z., Sun G. Filling invalid values in a lidar-derived canopy height model with morphological crown control // International Journal of Remote Sensing. 2013. Vol. 34, No 13, P. 4636–4654.
  31. Zhao K., Popescu S., Nelson R. Lidar remote sensing of forest biomass: A scale-invariant estimation approach using airborne lasers // Remote Sensing of Environment. 2009. Vol. 113, No 1, P. 182–196.
  32. Ризаев И.Г., Антоненко М.В., Погорелов А.В. Геоинформационный метод определения артефактов в цифровых моделях растительного покрова // Актуальные проблемы гуманитарных и естественных наук. 2014. № 12–2. С. 336–341.
  33. Rizaev I.G., Pogorelov A.V., Antonenko M.V. Geoinformacionnyj metod opredelenija artefaktov v cifrovyh modeljah rastitel'nogo pokrova [GIS method of defining artifacts in LiDAR-based canopy height model], Actual problems of humanities and natural sciences. 2014. No 12–2, pp. 336–341 (in Russian).

For citation: Rizaev I.G., Pogorelov A.V., Antonenko M.V., Kuzyakina M.V. GIS MODELING OF FOREST COVER ON THE BASIS OF AIRBORNE LASER SCANNING. Proceedings of the International conference “InterCarto. InterGIS”. 2015;21(1):420-427. https://doi.org/10.24057/2414-9179-2015-1-21-420-427