Tree species classification based on stem-related feature parameters derived from static terrestrial laser scanning data

International Journal of Remote Sensing

Volumn 37, Issue 18, 2016, Pages 4420-4440

  Wei, Tian ^a,b   Lin, Yi ^a,c   Yan, Lei ^a   Zhang, Lifu ^d  

^a PEKING UNIVERSITY   (China)

^b HEBEI UNITED UNIVERSITY   (China)

^c FINNISH GEODETIC INSTITUTE   (Finland)

^d INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ECOLOGY; FORESTRY; LASER APPLICATIONS; REMOTE SENSING; SEEBECK EFFECT; STATISTICAL METHODS; STEEL BEAMS AND GIRDERS; SUPPORT VECTOR MACHINES; SURFACE ANALYSIS; SURVEYING INSTRUMENTS;

CLASSIFICATION ACCURACY; ECOLOGICAL STUDIES; FOREST ENVIRONMENTS; LEAVE-ONE-OUT CROSS-VALIDATION (LOOCV); REMOTE SENSING TECHNOLOGY; REPRESENTATIVE CASE; TERRESTRIAL LASER SCANNING; TREE SPECIES INFORMATION;

CLASSIFICATION (OF INFORMATION);

IMAGE CLASSIFICATION; LASER METHOD; REMOTE SENSING; STEM; SUPPORT VECTOR MACHINE; TREE;

PICEA ABIES; PINUS SYLVESTRIS; POPULUS TREMULA; QUERCUS ROBUR;

EID: 84979943828     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2016.1213920     Document Type: Article

References (43)

1. A.S.Antonarakis, 2011. “Evaluating Forest Biometrics Obtained from Ground Lidar in Complex Riparian Forests.” Remote Sensing Letters 2:61–70. doi:10.1080/01431161.2010.493899.
2. D.Blanchette, R.A.Fournier, J.E.Luther, and J.-F.Côté. 2015. “Predicting Wood Fiber Attributes Using Local-Scale Metrics from Terrestrial Lidar Data:A Case Study of Newfoundland Conifer Species.” Forest Ecology and Management 347:116–129. doi:10.1016/j.foreco.2015.03.013.
3. K.Calders, J.Armston, G.Newnham, M.Herold, and N.Goodwin. 2014. “Implications of Sensor Configuration and Topography on Vertical Plant Profiles Derived from Terrestrial Lidar.” Agriculturaland Forest Meteorology 194:104–117. doi:10.1016/j.agrformet.2014.03.022.
4. C.-C.Chang, and C.-J.Lin. 2001. “LIBSVM:A Library for Support Vector Machines. Software.” Accessed June12 2014. http://www.csie.ntu.edu.tw/~cjlin/libsvm
5. M.Colgan, C.Baldeck, J.Féret, and G.Asner. 2012. “Mapping Savanna Tree Species at Ecosystem Scales Using Support Vector Machine Classification and BRDF Correction on Airborne Hyperspectral and Lidar Data.” Remote Sensing 4:3462–3480. doi:10.3390/rs4113462.
6. J.Cope, D.Corney, J.Clark, P.Remagnino, and P.Wilkin. 2012. “Plant Species Identification Using Digital Morphometrics:A Review.” Expert Systems with Applications 39:7562–7573. doi:10.1016/j.eswa.2012.01.073.
7. M.Dalponte, L.Bruzzone, and D.Gianelle. 2012. “Tree Species Classification in the Southern Alps Based on the Fusion of Very High Geometrical Resolution Multispectral/Hyperspectral Images and Lidar Data.” Remote Sensing of Environment 123:258–270. doi:10.1016/j.rse.2012.03.013.
8. E.S.Douglas, J.Martel, Z.Li, G.Howe, K.Hewawasam, R.A.Marshall, C.L.Schaaf, et al. 2015. “Finding Leaves in the Forest:The Dual-Wavelength Echidna Lidar.” IEEE Geoscience and Remote Sensing Letters 12:776–780. doi:10.1109/LGRS.2014.2361812.
9. S.Franklin, R.Hall, L.Moskal, A.Maudie, and M.Lavigne. 2000. “Incorporating Texture into Classification of Forest Species Composition from Airborne Multispectral Images.” International Journal of Remote Sensing 21:61–79. doi:10.1080/014311600210993.
10. R.George, H.Padalia, and S.Kushwaha. 2014. “Forest Tree Species Discrimination in Western Himalaya Using EO-1 Hyperion.” International Journal of Applied Earth Observation and Geoinformation 28:140–149. doi:10.1016/j.jag.2013.11.011.
11. D.González-Aguilera, P.Rodríguez-Gonzálvez, and J.Gómez-Lahoz. 2009. “An Automatic Procedure for Co-Registration of Terrestrial Laser Scanners and Digital Cameras.” ISPRS Journal of Photogrammetry and Remote Sensing 64:308–316. doi:10.1016/j.isprsjprs.2008.10.002.
12. R.Haralick, K.Shanmugam, and I.Dinstein. 1973. “Textural Features for Image Classification.” IEEE Transactions on Systems, Man and Cybernetics 3 (6):610–621. doi:10.1109/TSMC.1973.4309314.
13. M.Hauglin, T.Gobakken, R.Astrup, L.Ene, and E.Næsset. 2014. “Estimating Single-Tree Crown Biomass of Norway Spruce by Airborne Laser Scanning:A Comparison of Methods with and without the Use of Terrestrial Laser Scanning to Obtain the Ground Reference Data.” Forests 5:384–403. doi:10.3390/f5030384.
14. J.Heinzel, and B.Koch. 2011. “Exploring Full-Waveform Lidar Parameters for Tree Species Classification.” International Journal of Applied Earth Observation and Geoinformation 13:152–160. doi:10.1016/j.jag.2010.09.010.
15. J.Heinzel, and B.Koch. 2012. “Investigating Multiple Data Sources for Tree Species Classification in Temperate Forest and Use for Single Tree Delineation.” International Journal of Applied Earth Observation and Geoinformation 18:101–110. doi:10.1016/j.jag.2012.01.025.
16. J.G.Henning, and P.J.Radtke. 2006. “Detailed Stem Measurements of Standing Trees from Ground-Based Scanning Lidar.” Forest Science 52:67–80.
17. J.Holmgren, and Å.Persson. 2004. “Identifying Species of Individual Trees Using Airborne Laser Scanner.” Remote Sensing of Environment 90:415–423. doi:10.1016/S0034-4257(03)00140-8.
18. M.Holopainen, V.Kankare, M.Vastaranta, X.Liang, Y.Lin, M.Vaaja, X.Yu, et al. 2013. “Tree Mapping Using Airborne, Terrestrial and Mobile Laser Scanning – A Case Study in A Heterogeneous Urban Forest.” Urban Forestry & Urban Greening 12 (4):546–553. doi:10.1016/j.ufug.2013.06.002.
19. M.Holopainen, and M.Talvitie. 2006. “Effect of Data Acquisition Accuracy on Timing of Stand Harvests and Expected Net Present Value.” Silva Fennica 40:531–543. doi:10.14214/sf.335.
20. C.Hopkinson, L.Chasmer, C.Young-Pow, and P.Treitz. 2004. “Assessing Forest Metrics with a Ground-Based Scanning Lidar.” Canadian Journal of Forest Research 34:573–583. doi:10.1139/x03-225.
21. F.Hosoi, and K.Omasa. 2006. “Voxel-Based 3-D Modeling of Individual Trees for Estimating Leaf Area Density Using High-Resolution Portable Scanning Lidar.” IEEE Transactions on Geoscience and Remote Sensing 44:3610–3618. doi:10.1109/TGRS.2006.881743.
22. M.Lehtomäki, A.Jaakkola, J.Hyyppä, A.Kukko, and H.Kaartinen. 2010. “Detection of Vertical Pole-Like Objects in a Road Environment Using Vehicle-Based Laser Scanning Data.” Remote Sensing 2:641–664. doi:10.3390/rs2030641.
23. X.Liang, and J.Hyyppä. 2013. “Automatic Stem Mapping by Merging Several Terrestrial Laser Scans at the Feature and Decision Levels.” Sensors 13:1614–1634. doi:10.3390/s130201614.
24. X.Liang, P.Litkey, J.Hyyppä, H.Kaartinen, M.Vastaranta, and M.Holopainen. 2012. “Automatic Stem Mapping Using Single-Scan Terrestrial Laser Scanning.” IEEE Transactions on Geoscience and Remote Sensing 50:661–670. doi:10.1109/TGRS.2011.2161613.
25. C.Lin, S.C.Popescu, G.Thomson, K.Tsogt, and C.Chang. 2015. “Classification of Tree Species in Overstorey Canopy of Subtropical Forest Using Quickbird Images.” PLoS One 10 (5):e0125554. doi:10.1371/journal.pone.0125554.
26. Y.Lin, and M.Herold. 2016. “Tree Species Classification Based on Explicit Tree Structure Feature Parameters Derived from Static Terrestrial Laser Scanning Data.” Agriculturaland Forest Meteorology 216:105–114. doi:10.1016/j.agrformet.2015.10.008.
27. Y.Lin, J.Hyyppä, A.Kukko, A.Jaakkola, and H.Kaartinen. 2012. “Tree Height Growth Measurement with Single-Scan Airborne, Static Terrestrial and Mobile Laser Scanning.” Sensors 12:12798–12813. doi:10.3390/s120912798.
28. E.Lindberg, L.Eysn, M.Hollaus, J.Holmgren, and N.Pfeifer. 2014. “Delineation of Tree Crowns and Tree Species Classification from Full-Waveform Airborne Laser Scanning Data Using 3-D Ellipsoidal Clustering.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7:3174–3181. doi:10.1109/JSTARS.2014.2331276.
29. J.L.Lovell, D.L.B.Jupp, G.J.Newnham, and D.S.Culvenor. 2011. “Measuring Tree Stem Diameters Using Intensity Profiles from Ground-Based Scanning Lidar from a Fixed Viewpoint.” ISPRS Journal of Photogrammetry and Remote Sensing 66:46–55. doi:10.1016/j.isprsjprs.2010.08.006.
30. F.Melgani, and L.Bruzzone. 2004. “Classification of Hyperspectral Remote Sensing Images with Support Vector Machines.” IEEE Transactions on Geoscience and Remote Sensing 42:1778–1790. doi:10.1109/TGRS.2004.831865.
31. L.Naidoo, M.A.Cho, R.Mathieu, and G.Asner. 2012. “Classification of Savanna Tree Species, in the Greater Kruger National Park Region, by Integrating Hyperspectral and Lidar Data in a Random Forest Data Mining Environment.” ISPRS Journal of Photogrammetry and Remote Sensing 69:167–179. doi:10.1016/j.isprsjprs.2012.03.005.
32. K.Olofsson, J.Holmgren, and H.Olsson. 2014. “Tree Stem and Height Measurements Using Terrestrial Laser Scanning and the RANSAC Algorithm.” Remote Sensing 6:4323–4344. doi:10.3390/rs6054323.
33. A.Othmani, L.F.C.Voon, C.Stolz, and A.Piboule. 2013. “Single Tree Species Classification from Terrestrial Laser Scanning Data for Forest Inventory.” Pattern Recognition Letters 34:2144–2150. doi:10.1016/j.patrec.2013.08.004.
34. M.A.Pinard, F.E.Putz, D.Rumı́z, R.Guzmán, and A.Jardim. 1999. “Ecological Characterization of Tree Species for Guiding Forest Management Decisions in Seasonally Dry Forests in Lomerı́o, Bolivia.” Forest Ecology and Management 113:201–213. doi:10.1016/S0378-1127(98)00426-5.
35. E.Puttonen, J.Suomalainen, T.Hakala, E.Räikkönen, H.Kaartinen, S.Kaasalainen, and P.Litkey. 2010. “Tree Species Classification from Fused Active Hyperspectral Reflectance and LIDAR Measurements.” Forest Ecology and Management 260:1843–1852. doi:10.1016/j.foreco.2010.08.031.
36. P.Raumonen, M.Kaasalainen, M.Åkerblom, S.Kaasalainen, H.Kaartinen, M.Vastaranta, M.Holopainen, M.Disney, and P.Lewis. 2013. “Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data.” Remote Sensing 5:491–520. doi:10.3390/rs5020491.
37. C.Sabatia, and H.Burkhart. 2014. “Predicting Site Index of Plantation Loblolly Pine from Biophysical Variables.” Forest Ecology and Management 326:142–156. doi:10.1016/j.foreco.2014.04.019.
38. D.Seidel, C.Leuschner, A.Müller, and B.Krause. 2011. “Crown Plasticity in Mixed Forests - Quantifying Asymmetry as a Measure of Competition Using Terrestrial Laser Scanning.” Forest Ecology and Management 261:2123–2132. doi:10.1016/j.foreco.2011.03.008.
39. A.H.Strahler, D.L.B.Jupp, C.E.Woodcock, C.B.Schaaf, T.Yao, F.Zhao, X.Yang, et al. 2008. “Retrieval of Forest Structural Parameters Using a Ground-Based Lidar Instrument (Echidna®).” Canadian Journal of Remote Sensing 34:S426–440. doi:10.5589/m08-046.
40. M.Thies, N.Pfeifer, D.Winterhalder, and B.G.H.Gorte. 2004. “Three-Dimensional Reconstruction of Stems for Assessment of Taper, Sweep and Lean Based on Laser Scanning of Standing Trees.” Scandinavian Journal of Forest Research 19:571–581. doi:10.1080/02827580410019562.
41. J.Van Der Sanden, and D.Hoekman. 2005. “Review of Relationships between Grey-Tone Co-Occurrence, Semivariance and Autocorrelation Based Image Texture Analysis Approaches.” Canadian Journal of Remote Sensing 31:207–213. doi:10.5589/m05-008.
42. X.Yu, P.Litkey, J.Hyyppä, M.Holopainen, and M.Vastaranta. 2014. “Assessment of Low Density Full-Waveform Airborne Laser Scanning for Individual Tree Detection and Tree Species Classification.” Forests 5:1011–1031. doi:10.3390/f5051011.
43. K.Zhang, and B.Hu. 2012. “Individual Urban Tree Species Classification Using Very High Spatial Resolution Airborne Multi-Spectral Imagery Using Longitudinal Profiles.” Remote Sensing 4:1741–1757. doi:10.3390/rs4061741.