A fusion approach for tree crown delineation from Lidar data

Photogrammetric Engineering and Remote Sensing

Volumn 78, Issue 7, 2012, Pages 679-692

  Gleason, Colin J ^a,b   Jungho, Im ^b,c  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b 402 Baker Laboratory   (United States)

^c Ulsan National Institute of Science and Technology   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

GENETIC ALGORITHMS; OBJECT DETECTION; OBJECT RECOGNITION; OPTICAL RADAR; PLANTS (BOTANY);

BIOMASS ESTIMATION; CROWN DELINEATION; ENVIRONMENTAL SCIENCE; HILL CLIMBING ALGORITHMS; INDIVIDUAL TREE CROWN; MULTI STEP METHODS; STATE UNIVERSITY OF NEW YORK; TREE CROWN DELINEATION;

FORESTRY;

ACCURACY ASSESSMENT; BIOMASS; CANOPY ARCHITECTURE; COHORT ANALYSIS; CONIFEROUS TREE; GENETIC ALGORITHM; LIDAR; PLANTATION; SATELLITE DATA;

ALGORITHMS; CROWNS; DATA PROCESSING; ESTIMATION; NEW YORK; OPTICAL ACTIVITY; RADAR;

NEW YORK [UNITED STATES]; TULLY [NEW YORK]; UNITED STATES;

PICEA ABIES;

EID: 84864188599     PISSN: 00991112     EISSN: None     Source Type: Journal    
DOI: 10.14358/PERS.78.7.679     Document Type: Article

References (40)

1. Bortolot, Z.J., and R.H. Wynne, 2005. Estimating forest biomass using small footprint lidar data: An individual tree-based approach that incorporates training data, ISPRS Journal of Photogrammetry and Remote Sensing, 59(6):342-360
2. Brandtberg, T., 2007. Classifying individual tree species under leafoff and leaf-on conditions using airborne lidar, ISPRS Journal of Photogrammetry and Remote Sensing, 61(5):325-340.
3. Breidenbach, J., E. Næsset, V. Lien, T. Gobakken, and S. Solberg, 2010. Prediction of species specific forest inventory attributes using a nonparametric semi-individual tree crown approach based on fused airborne laser scanning and multispectral data, Remote Sensing of Environment, 114(4):911-924.
4. Bunting, P., and R. Lucas, 2006. The delineation of tree crowns in Australian mixed species forests using hyperspectral compact airborne spectrographic imager (CASI) data, Remote Sensing of Environment, 101(2):230-248.
5. Castilla, G., G.J. Hay, and J.R. Ruiz-Gallardo, 2008. Size-constrained region merging (SCRM): An automated delineation tool for assisted photointerpretation, Photogrammetric Engineering & Remote Sensing, 74(4):409-419.
6. Chan, T., and L. Vese, 2001. Active contours without edges, IEEE Transactions on Image Processing, 10:266-277.
7. Chang, D., X. Zhang, and C. Zheng, 2009. A genetic algorithm with gene rearrangement for k-means clustering, Pattern Recognition, 42(7):1210-1222.
8. Chen, G., G.J. Hay, and Y. Zhou, 2010. Estimation of forest height, biomass and volume using support vector regression and segmentation from LiDAR transects and QuickBird imagery, Proceedings of the 2010 18th International Conference on Geoinformatics, 18-20 June, Beijing, China.
9. Chen, Q., D. Baldocchi, P. Gong, and M. Kelly, 2006. Isolating individual trees in a savanna woodland using small footprint LiDAR data, Photogrammetric Engineering & Remote Sensing, 72(8):923-932.
10. Chen, Q., P. Gong, D. Baldocchi, and Y.Q. Tian, 2007. Estimating basal area and stem volume for individual trees from LiDAR data, Photogrammetric Engineering & Remote Sensing, 73(12):1355-1365.
11. Coops, N.C., M.A. Wulder, D.S. Culvenor, and B. St-Onge, 2004. Comparison of forest attributes extracted from fine spatial resolution multispectral and LiDAR data, Canadian Journal of Remote Sensing, 30(6):855-866.
12. Fang, H., S. Liang, and A. Kuusk, 2003. Retrieving leaf area index using a genetic algorithm with a canopy radiative transfer model, Remote Sensing of Environment, 85(3):257-270.
13. Gleason, C.J., and J. Im, 2011. A review of remote sensing of forest biomass and biofuel: Options for small scale applications, GIScience and Remote Sensing, 48(2):141-170.
14. Gleason, C.J., and J. Im, 2012. Forest biomass estimation from airborne LiDAR data using machine learning approaches, Remote Sensing of Environment, in press.
15. Goldberg, D.E., 1989. Genetic Algorithm in Search, Optimization, and Machine Learning, Addison-Wesley, Boston, Massachusetts.
16. Gong, B., J. Im, and G. Mountrakis, 2011. An artificial immune network approach to multi-sensor land use/land cover classification, Remote Sensing of Environment, 115(2):600-614.
17. Gonzalez, P., G.P. Asner, J.J. Battles, M.A. Lefsky, K.M. Waring, and M. Palace, 2010. Forest carbon densities and uncertainties from LiDAR, QuickBird, and field measurements in California, Remote Sensing of Environment, 114(7):1561-1575.
18. Gougeon, F.A., 1995. A crown-following approach to the automatic delineation of individual tree crowns in high spatial resolution aerial images, Canadian Journal of Remote Sensing, 21(3):274-284.
19. Im, J., Z. Lu, and J.R. Jensen, 2011. A genetic algorithm approach to moving threshold optimization for binary change detection, Photogrammetric Engineering & Remote Sensing, 77(2):167-180.
20. Jang, J., V. Payan, A.A. Viau, and A. Devost, 2008. The use of airborne LiDAR for orchard tree inventory, International Journal of Remote Sensing, 29(6):1767-1780.
21. Kato, A., L.M. Moskal, P. Schiess, M.E. Swanson, D. Calhoun, and W. Stuetzle, 2009. Capturing tree crown formation through implicit surface reconstruction using airborne LiDAR data, Remote Sensing of Environment, 113(6):1148-1162.
22. Ke, Y., W. Zhang, and L.J. Quackenbush, 2010. Active contour and hill climbing for tree crown detection and delineation, Photogrammetric Engineering & Remote Sensing, 76(10):1169-1181.
23. Koch B., 2010. Status and future of laser scanning, synthetic aperture radar and hyperspectral remote sensing data for forest biomass assessment, ISPRS Journal of Photogrammetry and Remote Sensing, 65(6):581-590.
24. Kwak, D., W. Lee, H. Cho, S. Lee, Y. Son, M. Kafatos, and S. Kim, 2010. Estimating stem volume and biomass of Pinus koraiensis using LiDAR data, Journal of Plant Research, 123(4):421-432.
25. Kwak, D., W. Lee, J. Lee, G.S. Biging, and P. Gong, 2007. Detection of individual trees and estimation of tree height using LiDAR data, Journal of Forest Research, 12(6):425-434.
26. Li, C., C.Y. Kao, J.C. Gore, and Z. Ding, 2007. Implicit active contours driven by local binary fitting energy, Proceedings of the 2007 IEEE Conference on Computer Vision and Pattern Recognition, 17-22 June, Minneapolis, Minnesota, pp. 1-7.
27. Lin, C., G. Thomson, C. Lo, and M. Yang, 2011. A multi-level morphological active contour algorithm for delineating tree crowns in mountainous forest, Photogrammetric Engineering & Remote Sensing, 77(3):241-249.
28. Næsset, E., and T. Økland, 2002. Estimating tree height and tree crown properties using airborne scanning laser in a boreal nature reserve, Remote Sensing of Environment, 79(1):105-115.
29. Persson, Å., J. Holmgren, and U. Söderman, 2002. Detecting and measuring individual trees using an airborne laser scanner, Photogrammetric Engineering & Remote Sensing, 68(9): 925-932.
30. Popescu, S.C., 2007. Estimating biomass of individual pine trees using airborne LiDAR, Biomass and Bioenergy, 31(9):646-655.
31. Popescu, S.C., and R.H. Wynne, 2004. Seeing the trees in the forest: Using LiDAR and multispectral data fusion with local filtering and variable window size for estimating tree height, Photogrammetric Engineering & Remote Sensing, 70(5):589-604.
32. Popescu, S.C., R.H. Wynne, and R.E. Nelson, 2002. Estimating plotlevel tree heights with LiDAR: Local filtering with a canopyheight based variable window, Computers and Electronics in Agriculture, 37(1-3):71-95.
33. Rezende, M.C.A.F., C.B.B. Costa, A.C. Costa, M.R.W. Maciel, and R.M. Filho, 2008. Optimization of a large scale industrial reactor by genetic algorithms, Chemical Engineering Science, 63(2):330-341.
34. Tseng, M., S. Chen, G. Hwang, and M. Shen, 2008. A genetic algorithm rule-based approach for land-cover classification, ISPRS Journal of Photogrammetry and Remote Sensing, 63(2):202-212.
35. Van Aardt, J.A.N., R.H. Wynne, and J.A. Scrivani, 2008. LiDARbased mapping of forest volume and biomass by taxonomic group using structurally homogenous segments, Photogrammetric Engineering & Remote Sensing, 74(8):1033-1044.
36. Vauhkonen, J., I. Korpela, M. Maltamo, and T. Tokola, 2010. Imputation of single-tree attributes using airborne laser scanning-based height, intensity, and alpha shape metrics, Remote Sensing of Environment, 114(6):1263-1276.
37. Wang, L., P. Gong, and G.S. Biging, 2004. Individual tree-crown delineation and treetop detection in high-spatial-resolution aerial imagery, Photogrammetric Engineering & Remote Sensing, 70(3):351-357.
38. Wang, Y., 2005. A GA-based methodology to determine an optimal curriculum for schools, Expert Systems with Applications, 28(1):163-174.
39. Wulder, M., K.O. Niemann, and D.G. Goodenough, 2000. Local maximum filtering for the extraction of tree locations and basal area from high spatial resolution imagery, Remote Sensing of Environment, 73(1):103-114.
40. Zhao, K., S. Popescu, and R. Nelson, 2009. LiDAR remote sensing of forest biomass: A scale-invariant estimation approach using airborne lasers, Remote Sensing of Environment, 113(1):182-196.