Matching remotely sensed and field-measured tree size distributions

Canadian Journal of Forest Research

Volumn 45, Issue 3, 2015, Pages 353-363

  Vauhkonen, Jari ^a,b   Mehtätalo, Lauri ^a  

^a UNIVERSITY OF EASTERN FINLAND   (Finland)

^b UNIVERSITY OF HELSINKI   (Finland)

Author keywords

Airborne laser scanning; Boolean model; Diameter distribution; Forest inventory; Forest structure; Histogram matching; Light detection and ranging (LiDAR); Marked point pattern; Mixed effects modeling

Indexed keywords

DISTRIBUTION FUNCTIONS; FORECASTING; GRAPHIC METHODS; LASER APPLICATIONS; MEAN SQUARE ERROR; METADATA; OPTICAL RADAR; POISSON DISTRIBUTION; REGRESSION ANALYSIS; REMOTE SENSING; SURFACE ANALYSIS;

AIRBORNE LASER SCANNING; BOOLEAN MODEL; DIAMETER DISTRIBUTIONS; FOREST INVENTORY; FOREST STRUCTURE; HISTOGRAM MATCHING; LIGHT DETECTION AND RANGING; MARKED POINT PATTERN; MIXED EFFECTS MODELS;

FORESTRY;

BASAL AREA; BOREAL FOREST; CANOPY ARCHITECTURE; DATA SET; DIAMETER; ERROR ANALYSIS; FIELDWORK; FOREST INVENTORY; FOREST MANAGEMENT; HISTOGRAM; LIDAR; REMOTE SENSING; SIZE DISTRIBUTION; STEM;

FORESTS; INVENTORY CONTROL; LIGHT;

EID: 84924074587     PISSN: 00455067     EISSN: 12086037     Source Type: Journal    
DOI: 10.1139/cjfr-2014-0285     Document Type: Article

References (57)

1. Baddeley, A., and Turner, R. 2005. Spatstat: an R package for analyzing spatial point patterns. J. Stat. Softw. 12: 1-42. Available from www.jstatsoft.org/v12/ i06/.
2. Baffetta, F., Corona, P., and Fattorini, L. 2012. A matching procedure to improve k-NN estimation of forest attribute maps. For. Ecol. Manage. 272: 35-50. doi:10.1016/j.foreco.2011.06.037.
3. Bailey, T.C., and Gatrell, A.C. 1995. Interactive spatial data analysis. Addison Wesley Longman Limited, Essex, England.
4. Bondesson, L., and Fahlen, J. 2003. Mean and variance of vacancy for hard-core disc processes and applications. Scandinavian Journal of Statistics, 30(4): 797-816. doi:10.1111/1467-9469.00365.
5. Breidenbach, J., and Astrup, R. 2014. The semi-individual tree crown approach. In Forestry applications of airborne laser scanning-concepts and case studies. Edited by M. Maltamo, E. Næsset, and J. Vauhkonen. Managing Forest Ecosystems 27. Springer, the Netherlands. pp. 113-133.
6. Breidenbach, J., Næsset, E., Lien, V., Gobakken, T., and Solberg, S. 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 Sens. Environ. 114: 911-924. doi:10.1016/j.rse. 2009.12.004.
7. Clark, P.J., and Evans, F.C. 1954. Distance to nearest neighbour as a measure of spatial relationships in populations. Ecology, 35: 445-453. doi:10.2307/ 1931034.
8. Donnelly, K. 1978. Simulations to determine the variance and edge-effect of total nearest neighbour distance. In Simulation studies in archaeology. Edited by I. Hodder. Cambridge University Press, New York. pp. 91-95.
9. Falkowski, M.J., Smith, A.M.S., Gessler, P.E., Hudak, A.T., Vierling, L.A., and Evans, J.S. 2008. The influence of conifer forest canopy cover on the accuracy of two individual tree measurement algorithms using lidar data. Can. J. Remote Sens. 34(Suppl. 2): S338-S350. doi:10.5589/m08-055.
10. Flewelling, J.W. 2008. Probability models for individually segmented tree crown images in a sampling context. In Proceedings of SilviLaser 2008, 8th International Conference on LiDAR Applications in Forest assessment and Inventory, Heriot-Watt University, Edinburgh, UK, 17-19 September 2008. Edited by R. Hill, J. Rosette, and J. Suárez. pp. 284-294.
11. Gilichinsky, M., Sandström, P., Reese, H., Kivinen, S., Moen, J., and Nilsson, M. 2011. Mapping ground lichens using forest inventory and optical satellite data. Int. J. Remote Sens. 32: 455-472. doi:10.1080/01431160903474962.
12. Gilichinsky, M., Heiskanen, J., Barth, A., Wallerman, J., Egberth, M., and Nilsson, M. 2012. Histogram matching for the calibration of kNN stem volume estimates. Int. J. Remote Sens. 33: 7117-7131. doi:10.1080/01431161.2012. 700134.
13. Gittleman, J.L., and Kot, M. 1990. Adaptation: statistics and a null model for estimating phylogenetic effects. Syst. Zool. 39: 227-241. doi:10.2307/2992183.
14. Gonzalez, R., and Woods, R.E. 2008. Digital image processing. 3rd edition. Prentice Hall, U.S.A.
15. Hopkinson, C., Lovell, J., Chasmer, L., Jupp, D., Kljun, N., and van Gorsel, E. 2013. Integrating terrestrial and airborne lidar to calibrate a 3D canopy model of effective leaf area index. Remote Sens. Environ. 136: 301-314. doi:10.1016/j. rse.2013.05.012.
16. Hyyppä, J., and Inkinen, M. 1999. Detecting and estimating attributes for single trees using laser scanner. The Photogrammetric Journal of Finland, 16: 27-42.
17. Hyyppä, J., Hyyppä, H., Leckie, D., Gougeon, F., Yu, X., and Maltamo, M. 2008. Review of methods of small-footprint airborne laser scanning for extracting forest inventory data in boreal forests. Int. J. Remote Sens. 29: 1339-1366. doi:10.1080/01431160701736489.
18. Kalliovirta, J., and Tokola, T. 2005. Functions for estimating stem diameter and tree age using tree height, crown width and existing stand database information. Silva Fenn. 39: 227-248. doi:10.14214/sf.386.
19. Ke, Y., and Quackenbush, L.J. 2011. A review of methods for automatic individual tree-crown detection and delineation from passive remote sensing. Int. J. Remote Sens. 32: 4725-4747. doi:10.1080/01431161.2010.494184.
20. Kendall, W.S., van Lieshout, M.N.M., and Baddeley, A.J. 1999. Quermassinteraction processes: conditions for stability. Adv. Appl. Probab. 31(2): 315- 342. doi:10.1239/aap/1029955137.
21. Koch, B., Heyder, U., and Weinacker, H. 2006. Detection of individual tree crowns in airborne LIDAR data. Photogramm. Eng. Remote Sens. 72: 357-363. doi:10.14358/PERS.72.4.357.
22. Korhonen, L., Peuhkurinen, J., Malinen, J., Suvanto, A., Maltamo, M., Packalén, P., and Kangas, J. 2008. The use of airborne laser scanning to estimate sawlog volumes. Forestry, 81: 499-510. doi:10.1093/forestry/cpn018.
23. Korhonen, L., Korpela, I., Heiskanen, J., and Maltamo, M. 2011. Airborne discretereturn LiDAR data in the estimation of vertical canopy cover, angular canopy closure and leaf area index. Remote Sens. Environ. 115: 1065-1080. doi:10. 1016/j.rse.2010.12.011.
24. Korpela, I. 2004. Individual tree measurements by means of digital aerial photogrammetry. Doctoral thesis, University of Helsinki, Department of Forest Resource Management, Helsinki, Finland. Silva Fennica Monographs 3.
25. Korpela, I. 2007. Incorporation of allometry in single-tree remote sensing with LIDAR and multiple images. In Proceedings of the ISPRS Hannover Workshop 2007-High Resolution Earth Imaging for Geospatial Information, 29 May - 1 June 2007, Hannover, Germany. Edited by C. Heipke, K. Jacobsen, and M. Gerke. Vol. XXXVI, Part I/W51.
26. Korpela, I., and Tokola, T. 2006. Potential of aerial image-based monoscopic and multiview single-tree forest inventory-a simulation approach. For. Sci. 52: 136-147.
27. Korpela, I., Dahlin, B., Schäfer, H., Bruun, E., Haapaniemi, F., Honkasalo, J., Ilvesniemi, S., Kuutti, V., Linkosalmi, M., Mustonen, J., Salo, M., Suomi, O., and Virtanen, H. 2007. Single-tree forest inventory using LiDAR and aerial images for 3D treetop positioning, species recognition, height and crown width estimation. In Proceedings of ISPRS Workshop on Laser Scanning 2007 and SilviLaser 2007, 12-14 September 2007, Espoo, Finland. Edited by P. Rönnholm, H. Hyyppä, and J. Hyyppä. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVI, Part 3/W52. pp. 227-233. Available from www.isprs.org/proceedings/XXXVI/ 3-W52/final_papers/Korpela_2007.pdf.
28. Larsen, M., Eriksson, M., Descombes, X., Perrin, G., Brandtberg, T., and Gougeon, F. 2011. Comparison of six individual tree crown detection algorithms evaluated under varying forest conditions. Int. J. Remote Sens. 32: 5827-5852. doi:10.1080/01431161.2010.507790.
29. Lindberg, E., Holmgren, J., Olofsson, K., Wallerman, J., and Olsson, H. 2010. Estimation of tree lists from airborne laser scanning by combining singletree and area-based methods. Int. J. Remote Sens. 31: 1175-1192. doi:10.1080/ 01431160903380649.
30. Lindstrom, M.J., and Bates, D.M. 1990. Nonlinear mixed-effects models for repeated measures data. Biometrics, 46: 673-687. doi:10.2307/2532087.
31. Maltamo, M., and Gobakken, T. 2014. Predicting tree diameter distributions. In Forestry applications of airborne laser scanning-concepts and case studies. Edited by M. Maltamo, E. Næsset, and J. Vauhkonen. Managing Forest Ecosystems 27, Springer, the Netherlands. pp. 177-191.
32. Maltamo, M., Eerikäinen, K., Pitkänen, J., Hyyppä, J., and Vehmas, M. 2004. Estimation of timber volume and stem density based on scanning laser altimetry and expected tree size distribution functions. Remote Sens. Environ. 90: 319-330. doi:10.1016/j.rse.2004.01.006.
33. Maltamo, M., Packalén, P., Kallio, E., Kangas, J., Uuttera, J., and Heikkilä, J. 2011. Airborne laser scanning based stand level management inventory in Finland. In Proceedings of SilviLaser 2011 - 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems, 16-20 October 2011, Hobart, Australia. Available from www.iufro.org/download/file/8239/5065/40205- silvilaser2011_pdf/.
34. Maltamo, M., Mehtätalo, L., Vauhkonen, J., and Packalén, P. 2012. Predicting and calibrating tree attributes by means of airborne laser scanning and field measurements. Can. J. For. Res. 42(11): 1896-1907. doi:10.1139/x2012-134.
35. McRoberts, R.E., Tomppo, E.O., and Næsset, E. 2010. Advances and emerging issues in national forest inventories. Scand. J. For. Res. 25: 368-381. doi:10. 1080/02827581.2010.496739.
36. Mehtätalo, L. 2006. Eliminating the effect of overlapping crowns from aerial inventory estimates. Can. J. For. Res. 36(7): 1649-1660. doi:10.1139/x06-066.
37. Næsset, E. 2002. Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data. Remote Sens. Environ. 80: 88-99. doi:10.1016/S0034-4257(01)00290-5.
38. Nyström, M., Holmgren, J., and Olsson, H. 2013. Change detection of mountain birch using multi-temporal ALS point clouds. Remote Sens. Lett. 4: 190-199. doi:10.1080/2150704X.2012.714087.
39. Olsson, H. 1993. Regression functions for multitemporal relative calibration of Thematic Mapper data over boreal forest. Remote Sens. Environ. 46: 89-102. doi:10.1016/0034-4257(93)90034-U.
40. Packalén, P., and Maltamo, M. 2008. Estimation of species-specific diameter distributions using airborne laser scanning and aerial photographs. Can. J. For. Res. 38(7): 1750-1760. doi:10.1139/X08-037.
41. Packalén, P., Vauhkonen, J., Kallio, E., Peuhkurinen, J., Pitkänen, J., Pippuri, I., Strunk, J., and Maltamo, M. 2013. Predicting the spatial pattern of trees with airborne laser scanning. Int. J. Remote Sens. 34: 5154-5165. doi:10.1080/ 01431161.2013.787501.
42. Pantze, A., Santoro, M., and Fransson, J.E.S. 2014. Change detection of boreal forest using bi-temporal ALOS PALSAR backscatter data. Remote Sens. Environ. 155: 120-128. doi:10.1016/j.rse.2013.08.050.
43. Persson, Å., Holmgren, J., and Söderman, U. 2002. Detecting and measuring individual trees using an airborne laser scanner. Photogramm. Eng. Remote Sens. 68: 925-932.
44. Peuhkurinen, J., Maltamo, M., Malinen, J., Pitkänen, J., and Packalén, P. 2007. Preharvest measurement of marked stands using airborne laser scanning. For. Sci. 53: 653-661.
45. Peuhkurinen, J., Mehtätalo, L., and Maltamo, M. 2011. Comparing individual tree detection and the area-based statistical approach for the retrieval of forest stand characteristics using airborne laser scanning in Scots pine stands. Can. J. For. Res. 41(3): 583-598. doi:10.1139/X10-223.
46. Pinheiro, J.C., and Bates, D.M. 2000. Mixed-effects models in S and S-PLUS. Springer-Verlag, New York.
47. Pinheiro, J., Bates, D., DebRoy, S., and Sarkar, D., and R Core Team. 2013. nlme: linear and nonlinear mixed effects models. R package version 3.1-111. Available from cran.r-project.org/web/packages/nlme.
48. Pitkänen, J. 2005. A multi-scale method for segmentation of trees in aerial images. In Proceedings of the SNS Meeting at Sjusjøen - Forest Inventory and Planning in Nordic Countries, Norway, 6-8 September 2004. Edited by K. Hobbelstad. NIJOS Report 09/05, Norwegian Institute of Land Inventory, Oslo, Norway.
49. Pitkänen, J., Maltamo, M., Hyyppä, J., and Yu, X. 2004. Adaptive methods for individual tree detection on airborne laser based canopy height model. In Proceedings of ISPRS working group VIII/2: Laser-Scanners for Forest and Landscape Assessment. Edited by M. Theis, B. Koch, H. Spiecker, and H. Weinacker. University of Freiburg, Freiburg, Germany. pp. 187-191.
50. Reynolds, M.R., Burk, T.E., and Huang, W.C. 1988. Goodness-of-fit tests and model selection procedures for diameter distribution models. For. Sci. 34: 373-399.
51. Stoyan, D., Kendall, W.S., and Mecke, J. 1995. Stochastic geometry and its applications. 2nd edition. Wiley, Chichester, UK.
52. Thompson, S.K. 2012. Sampling. 3rd edition. John Wiley & Sons, Hoboken, New Jersey.
53. Vauhkonen, J., Korpela, I., Maltamo, M., and Tokola, T. 2010. Imputation of single-tree attributes using airborne laser scanning-based height, intensity, and alpha shape metrics. Remote Sens. Environ. 114: 1263-1276. doi:10.1016/ j.rse.2010.01.016.
54. Vauhkonen, J., Mehtätalo, L., and Packalén, P. 2011. Combining tree height samples produced by airborne laser scanning and stand management records to estimate plot volume in Eucalyptus plantations. Can. J. For. Res. 41(8): 1649- 1658. doi:10.1139/x11-083.
55. Vauhkonen, J., Ene, L., Gupta, S., Heinzel, J., Holmgren, J., Pitkänen, J., Solberg, S., Wang, Y., Weinacker, H., Hauglin, K.M., Lien, V., Packalén, P., Gobakken, T., Koch, B., Næsset, E., Tokola, T., and Maltamo, M. 2012. Comparative testing of single-tree detection algorithms under different types of forest. Forestry, 85: 27-40. doi:10.1093/forestry/cpr051.
56. Vauhkonen, J., Packalen, P., Malinen, J., Pitkänen, J., and Maltamo, M. 2014. Airborne laser scanning based decision support for wood procurement planning. Scand. J. For. Res. 29(Suppl. 1): 132-143. doi:10.1080/02827581.2013.813063.
57. Xu, Q., Hou, Z., Maltamo, M., and Tokola, T. 2014. Calibration of area based diameter distribution with individual tree based diameter estimates using airborne laser scanning. ISPRS J. Photogramm. Remote Sens. 93: 65-75. doi: 10.1016/j.isprsjprs.2014.03.005.