Algorithm for extracting digital terrain models under forest canopy from airborne LiDAR data

Remote Sensing

Volumn 6, Issue 7, 2014, Pages 6524-6548

  Maguya, Almasi S ^a   Junttila, Virpi ^a   Kauranne, Tuomo ^a  

^a LAPPEENRANTA UNIVERSITY OF TECHNOLOGY   (Finland)

Author keywords

Airborne lidar; Biomass estimation; DTM extraction; Tree height estimation

Indexed keywords

EXTRACTION; FORESTRY; OPTICAL RADAR; ALGORITHMS;

AIRBORNE LIDAR; AIRBORNE LIDAR DATA; BIOMASS ESTIMATION; DIGITAL TERRAIN MODEL; FOREST CANOPIES; POINT DENSITY; TREE HEIGHT ESTIMATION; TREND SURFACE;

ALGORITHMS; FORESTRY;

ALGORITHMS; BIOMASS; EXTRACTION; FORESTRY; RADAR; DATA; FOREST CANOPY; MODELS;

EID: 84904489102     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs6076524     Document Type: Article

References (43)

1. Wehr, A.; Lohr, U. Airborne laser scanning-An introduction and overview. ISPRS J. Photogramm. Remote Sens. 1999, 54, 68-82.
2. Næsset, E. Determination of mean tree height of forest stands using airborne laser sanner data. ISPRS J. Photogramm. Remote Sens. 1997, 52, 49-56.
3. Kraus, K.; Pfeifer, N. Determination of terrain models in wooded areas with airborne laser scanner data. ISPRS J. Photogramm. Remote Sens. 1998, 53, 193-203.
4. Axelsson, P. Processing of laser scanner data-Algorithms and applications. ISPRS J. Photogramm. Remote Sens. 1999, 54, 138-147.
5. Pfeifer, N.; Reiter, T.; Briese, C.; Rieger,W. Interpolation of high quality ground models from laser scanner data in forested areas. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 1999, 32, 31-36.
6. Reutebuch, S.E.; Andersen, H.E.; McGaughey, R.J. Light Detection and Ranging(LiDAR): An emerging tool for multiple resource inventory. J. For. 2005, 103, 286-292.
7. Clark, M.L.; Roberts, D.A.; Ewel, J.J.; Clark, D.B. Estimation of tropical rain forest aboveground biomass with small-footprint LiDAR and hyperspectral sensors. Remote Sens. Environ. 2011, 115, 2931-2942.
8. Lemmens, M. Airborne LiDAR. In Geo-information; Gatrell, J.D., Jensen, R.R., Eds.; Springer Netherlands: Dordrecht, The Netherlands, 2011; Volume 5, pp. 153-170.
9. Full-Waveform Airborne Laser Scanning as a Tool for Archaeological Reconnaissance. Available online: http://w3.riegl.com/uploads/tx_pxpriegldownloads/Doneus_ROME_01.pdf (accessed on 15 July 2014).
10. Ullrich, A.; Studnicka, N.; Hollaus, M.; Briese, C.; Wagner, W.; Doneus, M.; Mücke, W. Improvements in DTM generation by using full-waveform airborne laser scanning data. In Proceedings of the 7th International Conference on Laser Scanning and Digital Aerial Photography, Today and Tomorrow, Moscow, Russia, 6-7 December 2007; Volume 6.
11. Jakubowski, M.K.; Guo, Q.; Kelly, M. Tradeoffs between LiDAR pulse density and forest measurement accuracy. Remote Sens. Environ. 2013, 130, 245-253.
12. Junttila, V.; Finley, A.O.; Bradford, J.B.; Kauranne, T. Strategies for minimizing sample size for use in airborne LiDAR-based forest inventory. For. Ecol. Manag. 2013, 292, 75-85.
13. Akay, A.; Oguz, H.; Karas, I.; Aruga, K. Using LiDAR technology in forestry activities. Environ. Monit. Assess. 2009, 151, 117-125.
14. Wang, C.; Glenn, N.F. A linear regression method for tree canopy height estimation using airborne LiDAR data. Can. J. Remote Sens. 2008, 34, S217-S227.
15. Takahashi, T.; Yamamoto, K.; Senda, Y.; Tsuzuku, M. Estimating individual tree heights of sugi (Cryptomeria japonica D. Don) plantations in mountainous areas using small-footprint airborne LiDAR. J. For. Res. 2005, 10, 135-142.
16. Van Leeuwen, M.; Nieuwenhuis, M. Retrieval of forest structural parameters using LiDAR remote sensing. Eur. J. For. Res. 2010, 129, 749-770.
17. Clark,M.L.; Clark, D.B.; Roberts, D.A. Small-footprint LiDAR estimation of sub-canopy elevation and tree height in a tropical rain forest landscape. Remote Sens. Environ. 2004, 91, 68-89.
18. Yamamoto, K.; Takahashi, T.; Miyachi, Y.; Kondo, N.; Morita, S.; Nakao, M.; Shibayama, T.; Takaichi, Y.; Tsuzuku,M.;Murate, N. Estimation ofmean tree height using small-footprint airborne LiDAR without a digital terrain model. J. For. Res. 2011, 16, 425-431.
19. Nilsson,M. Estimation of tree heights and stand volume using an airborne LiDAR system. Remote Sens. Environ. 1996, 56, 1-7.
20. Guo, Z.; Fang, J.; Pan, Y.; Birdsey, R. Inventory-based estimates of forest biomass carbon stocks in China. For. Ecol. Manag. 2010, 259, 1225-1231.
21. Herold, M.; Román-Cuesta, R.; Mollicone, D.; Hirata, Y.; van Laake, P.; Asner, G.; Souza, C.; Skutsch,M.; Avitabile, V.; MacDicken, K. Options for monitoring and estimating historical carbon emissions from forest degradation in the context of REDD+. Carbon BalanceManag. 2011, 6, 1-7.
22. Avtar, R.; Sawada, H. Use of DEM data to monitor height changes due to deforestation. Arab. J. Geosci. 2012, 6, 4859-4871.
23. Liu, X. Airborne LiDAR for DEM generation: Some critical issues. Progress Phys. Geogr. 2008, 32, 31-49.
24. Kraus, K.; Pfeifer, N. Advanced DTM generation from LiDAR data. Int. Arch. Photogramm. Remote Sens. 2001, XXXIV-3/W4, 23-30.
25. Vosselman, G. Slope based filtering of laser altimetry data. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2000, XXXIII, 935-942.
26. Sithole, G. Filtering of laser altimetry data using a slope adaptive filter. Int. Arch. Photogramm. Remote Sens. 2001, XXXIV-3/W4, 203-210.
27. Chen, Q.; Gong, P.; Baldocchi, D.; Xie, G. Filtering airborne laser scanning data with morphological methods. Photogramm. Eng. Remote Sens. 2007, 73, 175-185.
28. Kobler, A.; Pfeifer, N.; Ogrinc, P.; Todorovski, L.; Oštir, K.; Džeroski, S. Repetitive interpolation: A robust algorithm for DTMgeneration from Aerial Laser Scanner Data in forested terrain. Remote Sens. Environ. 2006, 108, 9-23.
29. Bao, Y.; LiïijN G.; Cao, C.; Li, X.; Zhang, H.; He, Q.; Bai, L.; Chang, C. Classification of LiDAR point cloud and generation of DTM from LiDAR height and intensity data in forested area. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2008, XXXVII, 313-318.
30. Mongus, D.; Žalik, B. Parameter-free ground filtering of LiDAR data for automatic DTM generation. ISPRS J. Photogramm. Remote Sens. 2012, 67, 1-12.
31. Sithole, G.; Vosselman, G. Experimental comparison of filter algorithms for bare-earth extraction from airborne laser scanning point clouds. ISPRS J. Photogramm. Remote Sens. 2004, 59, 85-101.
32. Hyyppä, H.; Yu, X.; Hyyppä, J.; Kaasalainen, H.; Honkavaara, E.; Rönnholm, P. Factors affecting the quality of DTM generation in forested areas. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2005, 36, 85-90.
33. Holmgren, J.; Nilsson, M.; Olsson, H. Simulating the effects of LiDAR scanning angle for estimation of mean tree height and canopy closure. Can. J. Remote Sens. 2003, 29, 623-632.
34. Hopkinson, C. The influence of flying altitude, beam divergence, and pulse repetition frequency on laser pulse return intensity and canopy frequency distribution. Can. J. Remote Sens. 2007, 33, 312-324.
35. Hopkinson, D.; Chasmer, L.E.; Zsigovics, G.; Creed, I.F.; Sitar,M.; Treitz, P.;Maher, R.V. Errors in LiDAR ground elevation and wetland vegetation height estimates. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2004, 36, 108-113.
36. Takahashi, T.; Yamamoto, K.; Miyachi, Y.; Senda, Y.; Tsuzuku, M. The penetration rate of laser pulses transmitted from a small-footprint airborne LiDAR: A case study in closed canopy, middle-aged pure sugi (Cryptomeria japonica D. Don) and hinoki cypress (Chamaecyparis obtusa Sieb. et Zucc.) stands in Japan. J. For. Res. 2006, 11, 117-123.
37. Fisher, P.F.; Tate, N.J. Causes and consequences of error in digital elevation models. Prog. Phys. Geogr. 2006, 30, 467-489.
38. Meng, X.; Currit, N.; Zhao, K. Ground filtering algorithms for airborne LiDAR data: A review of critical issues. Remote Sens. 2010, 2, 833-860.
39. Maguya, A.; Junttila, V.; Kauranne, T. Adaptive algorithm for large scale dtm interpolation from LiDAR data for forestry applications in steep forested terrain. ISPRS J. Photogramm. Remote Sens. 2013, 85, 74-83.
40. Sah, B.P.; Hämäläinen, J.M.; Sah, A.K.; Honji, K.; Foli, E.G.; Awudi, C. The use of satellite imagery to guide field plot sampling scheme for biomass estimation in Ghanaian forest. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 2012, I-4, 221-226.
41. Gautam, B.; Peuhkurinen, J.; Kauranne, T.; Gunia, K.; Tegel, K.; Latva-Käyrä, P.; Rana, P.; Eivazi, A.; Kolesnikov,A.; Hämäläinen, J.; et al. Estimation of forest carbon using LiDAR-Assisted Multi-Resource Programme (LAMP) in Nepal. Presented at International Conference on Advanced Geospatial Technologies for Sustainable Environment and Culture, Pokhara, Nepal, 12-13 September 2013.
42. McGaughey, R.J.; Carson,W.W. Fusing LiDAR data, photographs, and other data using 2D and 3D visualization techniques. In Proceedings of Terrain Data: Applications and Visualization-Making the Connection, Charleston, SC, USA, 28-30 October 2003; pp. 16-24.
43. Terrascan. Terrasolid's Software for LiDAR Data Processing and 3D Vector Data Creation, 2012. Available online: http://www.terrasolid.com/products/terrascanpage.html (accesed on 28 January 2014).