A Comparison of two open source LiDAR surface classification algorithms

Remote Sensing

Volumn 3, Issue 3, 2011, Pages 638-649

  Tinkham, Wade T ^a   Huang, Hongyu ^b   Smith, Alistair M S ^a   Shrestha, Rupesh ^c   Falkowski, Michael J ^d   Hudak, Andrew T ^e   Link, Timothy E ^a   Glenn, Nancy F ^c   Marks, Danny G ^f  

^a UNIVERSITY OF IDAHO   (United States)

^b FUZHOU UNIVERSITY   (China)

^c Nucl Eng Idaho State University   (United States)

^d MICHIGAN TECHNOLOGICAL UNIVERSITY   (United States)

^e ROCKY MOUNTAIN RESEARCH STATION   (United States)

^f NORTHWEST WATERSHED RESEARCH CENTER   (United States)

Author keywords

Algorithm; BCAL; DTM; Filtering; LiDAR; MCC

Indexed keywords

BCAL; COVER TYPES; DIGITAL TERRAIN MODEL; DTM; GROUND SURFACES; HIGH-PRECISION SURVEYS; LIDAR (LIGHT DETECTION AND RANGING); MCC; MULTISCALES; OPEN SOURCES; POINT CLOUD; PURCHASE COST; RESOURCE MANAGEMENT; SEMI ARID; SURFACE CLASSIFICATION; VEGETATION TYPE;

INFORMATION MANAGEMENT; OPTICAL RADAR; TEMPERATURE CONTROL;

ALGORITHMS;

EID: 80052018300     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs3030638     Document Type: Letter

References (30)

1. Martinuzzi, S.; Vierling, L.A.; Gould, W.A.; Falkowski, M.J.; Evans, J.S.; Hudak, A.T.; Vierling, K.T. Mapping snags and understory shrubs for a lidar-based assessment of wildlife habitat suitability. Remote Sens. Environ. 2009, 113, 2533-2546.
2. Falkowski, M.J.; Evans, J.S.; Martinuzzi, S.; Gessler, P.E.; Hudak, A.T. Characterizing forest succession with lidar data: An evaluation for the Inland Northwest, USA. Remote Sens. Environ. 2009, 113, 946-956.
3. Essery, R.; Bunting, P.; Hardy, J.; Link, T.; Marks, D.; Melloh, R.; Pomeroy, J.; Rowlands, A.; Rutter, N. Radiative transfer modeling of a coniferous canopy characterized by airborne remote sensing. J. Hydrometeorol. 2008, 9, 228-241.
4. Asner, G.P. Tropical forest carbon assessment: Integrating satellite and airborne mapping approaches. Environ. Res. Lett. 2009, 4, 1-11.
5. Abermann, J.; Fischer, A.; Lambrecht, A.; Geist, T. On the potential of very high-resolution repeat DEMs in glacial and periglacial environments. The Cryosphere 2010, 4, 53-65.
6. Marks, K.; Bates, P. Integration of high-resolution topographic data with floodplain flow models. Hydrol. Process. 2000, 14, 2109-2112.
7. Hodgson, M.E.; Jensen, J.; Raber, G.; Tullis, J.; Davis, B.A.; Thompson, G.; Schuckman, K. An evaluation of lidar-derived elevation and terrain slope in leaf-off conditions. Photogramm. Eng. Remote Sensing 2005, 71, 817-823.
8. Hollaus, M.; Wagner, W.; Eberhofer, C.; Karel, W. Accuracy of large-scale canopy heights derived from lidar data under operational constraints in a complex alpine environment. ISPRS J. Photogram. Remote Sens. 2006, 60, 323-338.
9. Baltsavias, E.P. Airborne laser scanning: Existing systems and firms and other resources. ISPRS J. Photogram. Remote Sens. 1999, 54, 165-198.
10. Hodgson, M.E.; Jenson, J.R.; Schmidt, L.; Schill, S.; Davis, B. An evaluation of lidar- and IFSAR-derived digital elevation models in leaf-on conditions with USGS Level 1 and Level 2 DEMs. Remote Sens. Environ. 2003, 84, 295-308.
11. Smith, S.L.; Holland, D.A.; Longley, P.A. The importance of understanding error in lidar digital elevation models. In Proceedings of XXth ISPRS Congress: Commission IV "Geo-Imagery Bridging Continents", Istanbul, Turkey, 12-23 July 2004; Volume 35, pp. 996-1001.
12. Reutebuch, S.E.; McGaughey, R.J.; Andersen, H.-E.; Carson, W.W. Accuracy of a high-resolution lidar terrain model under a conifer forest canopy. Can. J. Remote Sens. 2003, 29, 527-535.
13. Hodgson, M.E.; Bresnahan, E. Accuracy of airborne lidar-derived elevation: Empirical assessment and error budget. Photogram. Eng. Remote Sensing 2004, 70, 331-339.
14. Anderson, E.S.; Thompson, J.A.; Austin, R.E. Lidar density and linear interpolator effects on elevation estimates. Int. J. Remote Sens. 2005, 26, 3889-3900.
15. Hyyppä, H.; Yu, Z.; Hyyppa, J.; Kaartinen, H.; Kaasalainen, S.; Honkavaara, E.; Ronnholm, P. Factors affecting the quality of DTM generation in forested areas. In Proceedings of the ISPRS Workshop Laser Scanning 2005, Enschede, The Netherlands, 12-14 September 2005; Volume 36, Part 3/W19, pp. 97-102.
16. Su, J.; Bork, E. Influence of vegetation, slope, and lidar sampling angle on DEM accuracy. Photogram. Eng. Remote Sensing 2006, 72, 1265-1274.
17. Bates, C.W.; Coops, N.C. Evaluating error associated with lidar-derived DEM interpolation. Comput. Geosci. 2008, 35, 289-300.
18. Shan, J.; Toth, C.K. Topographic Laser Ranging and Scanning: Principles and Processing; CRC Press: Boca Raton, FL, USA, 2009.
19. Spaete, L.P.; Glenn, N.F.; Derryberry, D.P.; Sanki, T.T.; Mitchell, J.; Hardegree, S.P. The effects of slope and vegetation cover type on the accuracy of a small-footprint airborne lidar derived digital elevation model. Remote Sens. Lett. 2011, in press.
20. Guo, Q.; Li, W.; Yu, H.; Alvarez, O. Effects of topographic variability and lidar sampling density on several DEM interpolation methods. Photogram. Eng. Remote Sensing 2010, 76, 1-12.
21. Evans, J.S.; Hudak, A.T.; Faux, R.; Smith, A.M.S. Discrete return lidar in natural resources: Recommendations for project planning, data processing, and deliverables. Remote Sens. 2009, 1, 776-794.
22. Jensen, J.R. Active and passive microwave remote sensing. In Remote Sensing of the Environment: An Earth Resource Perspective; Prentice Hall: Upper Saddle River, NJ, USA, 2007; pp. 335-354.
23. Evans, J.S.; Hudak, A.T. A multiscale curvature algorithm for classifying discrete return lidar in forested environments. IEEE Trans. Geosci. Remote Sens. 2007, 45, 1029-1038.
24. Streutker, D.; Glenn, N. lidar measurement of sagebrush steppe vegetation heights. Remote Sens. Environ. 2006, 102, 135-145.
25. Hudak, A.T.; Crookston, N.L.; Evans, J.S.; Falkowski, M.J.; Smith, A.M.S.; Gessler, P.E.; Morgan, P. Regression modeling and mapping of coniferous forest basal area and tree density from discrete-return lidar and multispectral satellite data. Can. J. Remote Sens. 2006, 32, 126-138.
26. Hudak, A.T.; Crookston, N.L.; Evans, J.S.; Hall, D.E.; Falkowski, M.J. Nearest neighbor imputation of species-level, plot-scale forest structure attributes from lidar data. Remote Sens. Environ. 2008, 112, 2232-2245.
27. Jensen, J.L.R.; Humes, K.S.; Vierling, L.A.; Hudak, A.T. Discrete return lidar-based prediction of leaf area index in two conifer forests. Remote Sens. Environ. 2008, 112, 3947-3957.
28. Falkowski, M.J.; Hudak, A.T.; Crookston, N.L.; Gessler, P.E.; Uebler, E.; Smith, A.M.S. Landscape-scale parameterization of a tree-level forest growth model: A k-nearest neighbor imputation approach incorporating lidar data. Can. J. For. Res. 2010, 40, 184-199.
29. Glenn, N.F.; Spaete, L.; Sankey, T.; Derryberry, D.R.; Hardegree, S. Lidar-derived shrub height and crown area: development of methods and the lack of influence from sloped terrain. J. Arid Environ. 2011, in press.
30. Sankey, T.T.; Bond, P. LiDAR-based classification of sagebrush community types. Rangeland Ecol. Manage. 2011, 64, 92-98.