Improving the efficiency and accuracy of individual tree crowndelineation from high-density LiDAR data

International Journal of Applied Earth Observation and Geoinformation

Volumn 26, Issue 1, 2014, Pages 145-155

  Hu, Baoxin ^a   Li, Jili ^a   Jing, Linhai ^b   Judah, Aaron ^a  

^a YORK UNIVERSITY   (Canada)

^b CENTER FOR EARTH OBSERVATION AND DIGITAL EARTH   (China)

Author keywords

3 D structures; Individual tree crown (ITC) delineation; Knowledge based; LiDAR; Multi scale

Indexed keywords

ACCURACY ASSESSMENT; CANOPY ARCHITECTURE; DECIDUOUS FOREST; FOREST CANOPY; FOREST INVENTORY; LIDAR; MIXED FOREST; THREE-DIMENSIONAL MODELING;

CANADA; ONTARIO [CANADA];

EID: 84897886317     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2013.06.003     Document Type: Article

References (40)

1. Brandtberg, T., Walter, F., 1998. Automated delineation of individual tree crowns inhigh spatial resolution aerial images by multiple-scale analysis. Machine Visionand Applications 11 (2), 64-73.
2. Chen, Q., Baldocchi, D., Gong, P., Kelly, M., 2006. Isolating individual trees in a savannawoodland using small footprint lidar data. Photogrammetric Engineering andRemote Sensing 72 (8), 923-932.
3. Clark, I., 1979. Practical Geostatistics. Applied Science Publishers.
4. Culvenor, D.S., 2002. TIDA: an algorithm for the delineation of tree crowns in highspatial resolution remotely sensed imagery. Computers & Geosciences 28 (1),33-44.
5. Erikson, M., 2003. Segmentation of individual tree crowns in colour aerial pho-tographs using region growing supported by fuzzy rules. Canadian Journal ofForest Research-Revue Canadienne De Recherche Forestiere 33 (8), 1557-1563.
6. Falkowski, M.J., et al., 2006. Automated estimation of individual conifer tree heightand crown diameter via two-dimensional spatial wavelet analysis of lidar data.Canadian Journal of Remote Sensing 32 (2), 153-161.
7. Garrigues, S., Allard, D., Baret, F., Weiss, M., 2006. Quantifying spatial heterogeneityat the landscape scale using variogram models. Remote Sensing of Environment103 (1), 81-96.
8. Gong, P., Sheng, Y., Biging, G.S., 2002. 3D model-based tree measurement from high-resolution aerial imagery. Photogrammetric Engineering and Remote Sensing 68(11), 1203-1212.
9. Gougeon, F., 1995. A crown-following approach to the automatic delineation of indi-vidual tree crowns in high spatial resolution aerial images. Canadian Journal ofRemote Sensing 21 (3), 274-284.
10. Hartigan, J.A., Wong, M.A., 1979. Algorithm AS 136: A K-Means Clustering Algo-rithm. Journal of the Royal Statistical Society, Series C (Applied Statistics) 28 (1),100-108.
11. Holmgren, J., Barth, A., Larsson, H., Olsson, H., 2010. Prediction of stem attributes bycombining airborne laser scanning and measurements from harvesting machin-ery. In: SilviLaser 2010 10th International Conference on LiDAR Applications forAssessing Forest Ecosystems, Freiburg, Germany.
12. Hyyppä, J., et al., 2008. Review of methods of small-footprint airborne laser scanningfor extracting forest inventory data in boreal forests. International Journal ofRemote Sensing 29 (5), 1339-1366.
13. Hyyppä, J., Inkinen, M., 1999. Detecting and estimating attributes for single treesusing laser scanner. The Photogrammetric Journal of Finland 16 (2), 27-42.
14. Hyyppä, J., Kelle, O., Lehikoinen, M., Inkinen, M., 2001. A segmentation-based methodto retrieve stem volume estimates from 3-D tree height models produced bylaser scanners. IEEE Transactions on Geoscience and Remote Sensing 39 (5),969-975.
15. Jing, L., Hu, B., Li, J., Noland, T., 2013. Automated tree crown delineation fromimagery based on morphological techniques. IEEE Transactions on Geoscienceand Remote Sensing (submitted).
16. Jing, L., Hu, B., Li, J., Noland, T., 2012a. Automated delineation of individual treecrowns from Lidar data by multi-scale analysis and segmentation. Photogram-metric Engineering and Remote Sensing 78 (12), 1275-1284.
17. Jing, L., Hu, B., Noland, T., Li, J., 2012b. An individual tree crown delineation methodbased on multi-scale segmentation of imagery. ISPRS Journal of Photogramme-try and Remote Sensing 70, 88-98.
18. Koch, B., Heyder, U., Weinacker, H., 2006. Detection of individual tree crowns inairborne lidar data. Photogrammetric Engineering and Remote Sensing 72 (4),357-363.
19. Leckie, D., Gougeon, F., Hill, D., Quinn, R., Armstrong, L., Shreenan, R., 2003. Combinedhigh-density lidar and multispectral imagery for individual tree crown analysis.Canadian Journal of Remote Sensing 29 (5), 633-649.
20. Lee, H., Slatton, K.C., Roth, B.E., Cropper, W.P., 2010. Adaptive clustering of airborneLiDAR data to segment individual tree crowns in managed pine forests. Interna-tional Journal of Remote Sensing 31 (1), 117-139.
21. Li, W., Guo, Q., Jakubowski, M., Kelly, M., 2012. A new method for segmenting individ-ual trees from the Lidar Point Cloud. Photogrammetric Engineering and RemoteSensing 78 (1), 75-84.
22. Lichstein, J.W., et al., 2010. Unlocking the forest inventory data: relating individualtree performance to unmeasured environmental factors. Ecological Applications20 (3), 684-699.
23. Morsdorf, F., et al., 2004. LIDAR-based geometric reconstruction of boreal type foreststands at single tree level for forest and wildland fire management. RemoteSensing of Environment 92 (3), 353-362.
24. Pitkänen, J., Maltamo, M., Hyyppä, J., Yu, X., 2004. Adaptive methods for individualtree detection on airborne laser based canopy height model. In: ISPRS WorkingGroup VIII/2: Laser-Scanners for Forest and Landscape Assessment, Freiburg,Germany, pp. 187-191.
25. Pollock, R., 1996. The automatic recognition of individual trees in aerial imageof forests based on a synthetic tree crown image model. University of BritishColumbia (PhD dissertation).
26. Popescu, S.C., Wynne, R.H., Nelson, R.F., 2003. Measuring individual treecrown diameter with lidar and assessing its influence on estimating for-est volume and biomass. Canadian Journal of Remote Sensing 29 (5),564-577.
27. Pouliot, D.A., King, D.J., Bell, F.W., Pitt, D.G., 2002. Automated tree crowndetection and delineation in high-resolution digital camera imagery ofconiferous forest regeneration. Remote Sensing of Environment 82 (2-3),322-334.
28. Reitberger, J., Schnorr, C., Krzystek, P., Stilla, U., 2009. 3D segmentation of singletrees exploiting full waveform LIDAR data. ISPRS Journal of Photogrammetryand Remote Sensing 64 (6), 561-574.
29. Schardt, M., Ziegler, M., Wimmer, A., Wack, R., Hyyppa, J., 2002. Assessment of forestparameters by means of laser scanning. In: ISPRS Commission III, Symposium2002: Photogrammetric Computer Vision, Graz, Austria, pp. 302-309.
30. Serra, J., 1982. Image Analysis and Mathematical Morphology. Academic Press, NewYork, pp. 610.
31. Soille, P., 1999. Morphological Image Analysis: Principles and Applications. Springer,New York.
32. Solberg, S., Naesset, E., Bollandsas, O.M., 2006. Single tree segmentationusing airborne laser scanner data in a structurally heterogeneous spruceforest. Photogrammetric Engineering and Remote Sensing 72 (12),1369-1378.
33. St-Onge, B.A., Cavayas, F., 1995. Estimating forest stand structure from high-resolution imagery using the directional variogram. International Journal ofRemote Sensing 16 (11), 1999-2021.
34. Vauhkonen, J., et al., 2010. Comparative testing of single-tree detec-tion algorithms. In: SilviLaser 2010 10th International Conferenceon LiDAR Applications for Assessing Forest Ecosystems, Freiburg,Germany.
35. Wang, L., 2010. A multi-scale approach for delineating individual tree crowns withvery high resolution imagery. Photogrammetric Engineering and Remote Sens-ing 76 (4), 371-378.
36. Warner, T.A., Yeol Lee, J., McGraw, J.B., 1998. In: Hill, D.A., Leckie, D.G. (Eds.), Delin-eation and identification of individual trees in the eastern deciduous forest.Victoria, BC, pp. 81-92.
37. Wolf, B.M., Heipke, C., 2007. Automatic extraction and delineation of singletrees from remote sensing data. Machine Vision and Applications 18 (5),317-330.
38. Woodcock, C.E., Strahler, A.H., Jupp, D.L.B., 1988. The use of variograms in remote-sensing. 1. Scene models and simulated images. Remote Sensing of Environment25 (3), 323-348.
39. Mathworks, The MathWorks, Inc., http://www.mathworks.com/help/signal/ug/residual-analysis-with-autocorrelation.html, last accessed: May 9, 2013.
40. Hoel, P.G., Port, S.C., Stone, C.J., 1971. Testing Hypotheses. Ch. 3 in Introduction toStatistical Theory, vol. 5. Houghton Mifflin, New York, pp. 2-110.