Estimation of standing dead tree class distributions in northwest coastal forests using lidar remote sensing

Canadian Journal of Forest Research

Volumn 39, Issue 6, 2009, Pages 1080-1091

  Bater, Christopher W ^a   Coops, Nicholas C ^a   Gergel, Sarah E ^a   LeMay, Valerie ^a   Collins, Denis ^b  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b RESEARCH BRANCH   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

CLASS DISTRIBUTIONS; COASTAL FOREST; COEFFICIENT OF VARIATION; DEAD TREES; DEAD WOOD; FIELD PLOT; FOREST BIODIVERSITY; FOREST PLOTS; FOREST STAND; HABITAT AVAILABILITY; LIDAR REMOTE SENSING; LIGHT DETECTION AND RANGING; ORDINAL REGRESSION; PREDICTOR VARIABLES; RELATIVE ABUNDANCE; SPATIAL EXTENT; STANDING DEAD TREES; STRUCTURAL HETEROGENEITY; VEGETATION STRUCTURE;

BIODIVERSITY; FORESTRY; REMOTE SENSING;

OPTICAL RADAR;

BIODIVERSITY; COASTAL ZONE; DETECTION METHOD; ESTIMATION METHOD; FOREST; HETEROGENEITY; LIDAR; PREDICTION; RELATIVE ABUNDANCE; REMOTE SENSING;

BIODIVERSITY; DEAD WOOD; FORESTS; PLANTS; RADAR; REGRESSION ANALYSIS; REMOTE SENSING; TREES;

EID: 67649371193     PISSN: 00455067     EISSN: None     Source Type: Journal    
DOI: 10.1139/X09-030     Document Type: Article

References (46)

1. Aber, J.D. 1979a. Foliage-height profiles and succession in northern hardwood forests. Ecology, 60: 18-23. doi: 10.2307/1936462.
2. Aber, J.D. 1979b. A method for measuring foliage-height profiles in broad-leaved forests. J. Ecol. 67: 35-40. doi: 10.2307/ 2259335.
3. Andersen, H.-E., McGaughey, R.J., and Reutebuch, S.E. 2005. Estimating forest canopy fuel parameters using LIDAR data. Remote Sens. Environ. 94: 441-449. doi:10.1016/j.rse.2004.10.013.
4. BC Stats. 2005. Quick facts about British Columbia. British Columbia Ministry of Labour and Citizen's Services. Available from, http://www.bcstats. gov.bc.ca/data/qf.pdf [accessed 12 October 2006].
5. Breckenridge, R.P., Kepner, W.G., and Mouat, D.A. 1995. A process for selecting indicators for monitoring conditions of rangeland health. Environ. Monit. Assess. 36: 45-60. doi:10.1007/ BF00546984.
6. Bunnell, F.L. 2008. Indicators for sustaining biological diversity in Canada's most controversial forest type -coastal temperate rainforest. Ecol. Indic. 8: 149-157. doi:10.1016/j.ecolind.2006. 11.007.
7. Clark, D.B., Castas, C.S., Alvarado, L.D.A., and Read, J.M. 2004. Quantifying mortality of tropical rain forest trees using highspatial-resolution satellite data. Ecol. Lett. 7: 52-59. doi: 10. 1046/J.1461-0248.2003. 00547.X.
8. Clayoquot Sound. Scientific Panel. 1995. Sustainable ecosystem management in Clayoquot Sound. Rep. 5. Available from http:// www.for.gov.bc.ca/hfd/ library/documents/bibl2571.pdf [accessed 22 April 2008].
9. Coops, N.C., Hilker, T., Wulder, M.A., St-Onge, B., Newnham, G., Siggins, A., and Troymow, J.A. 2007. Estimating canopy structure of Douglas-fir forest stands from discrete-return LiDAR. Trees (BerL), 21: 295-310. doi:10.1007/s00468-006-0119-6.
10. DeLong, C.S., Burton, P.J., and Harrison, M. 2004. Assessing the relative quality of old-growth forests: an example from the Robson Valley, British Columbia. BC J. Ecosyst. Manage. 4(2): 116.
11. Demarchi, D.A., Marsh, R.D., Harcombe, A.P., and Lea, E.C. 1990. The environment (of British Columbia). In The birds of British Columbia. Edited by R.W. Campbell, N.K. Dawe, I. McTaggart-Cowan, J.M. Cooper, G.W. Kaiser, and M.C.E. McNall. Royal British Columbia Museum, Environment Canada, and Canadian Wildlife Service, Victoria, B.C. pp. 55-142.
12. Environment Canada. 2006. Canadian Climate Normals 19712000, Torino A, British Columbia. Available from http://www. climate.weatheroffice.ec.gc.ca/ climate-normals/index-e.html [last accessed 22 April 2008].
13. Gobakken, T., and Nassset, E. 2005. Weibull and percentile models for lidar-based estimation of basal area distribution. Scand. J. For. Res. 20: 490-502. doi: 10.1080/02827580500373186.
14. Hall, S.A., Burke, I.C, Box, D.O., Kaufmann, M.R., and Stoker, J.M. 2005. Estimating stand structure using discrete-return lidar: an example from, low-density, fire prone ponderosa pine forests. For. Ecol. Manage. 208: 189-209. doi:10.1016/j.foreco.2004.12. 001.
15. Hill, T., and Lewicki, P. 2006. Statistics: methods and applications. Statsoft, Tulsa, Okla.
16. Hill, R.A., Hinsley, S.A., Gaveau, D.L.A., and Bellamy, P.E. 2004. Predicting habitat quality for great tits (Pants major) with airborne laser scanning data. Int. J. Remote Sens. 25: 4851-4855. doi:10.1080/0143116031000139962.
17. Hopkinson, C., Chasmer, L., Lim, K., Treitz, P., and Creed, I. 2006. Towards a universal lidar canopy height indicator. Can. J. Rem. Sens. 32: 139-152.
18. Hosmer, D.W., and Lemeshow, S. 2000. Applied logistic regression. 2nd ed. John Wiley and Sons, Toronto, Ont.
19. Hudak, A.T., Lefsky, M.A., Cohen, W.B., and Berterretche, M. 2002. Integration of lidar and Landsat ETM+ data for estimating and mapping forest canopy height. Remote Sens. Environ. 82: 397-416. doi:10.1016/S0034- 4257(02)00056-1.
20. Hyde, P., Dubayah, R., Walker, W., Blair, J.B., Hofton, M., and Hunsaker, C. 2006. Mapping forest structure for wildlife habitat analysis using multi-sensor (LiDAR, SAR/InSAR, ETM+, Quickbird) synergy. Remote Sens. Environ. 102: 63-73. doi: 10. 1016/j.rse.2006.01.021.
21. Lefsky, M.A., Cohen, W.B., Acker, S.A., Parker, G.G., Spies, T.A., and Harding, D. 1999. LiDAR remote sensing of the canopy structure and biophysical properties of Douglas-fir western hemlock forests. Remote Sens. Environ. 70: 339-361. doi:10.1016/ S0034-4257(99)00052-8.
22. Lefsky, M.A., Hudak, A.T., Cohen, W.B., and Acker, S.A. 2005a. Geographic variability in lidar predictions of forest stand structure in the Pacific Northwest. Remote Sens. Environ. 95: 532548. doi:10.1016/j.rse.2005.01. 010.
23. Lefsky, M.A., Turner, D.P., Guzy, M., and Cohen, W.B. 2005b. Combining lidar estimates of aboveground biomass and Landsat estimates of stand age for spatially extensive validation of modeled, forest productivity. Remote Sens. Environ. 95: 549-558. doi:10.1016/j.rse.2004.12.022.
24. MacArthur, R.H., and Horn, H.S. 1969. Foliage profile by vertical measurements. Ecology, 50: 802-804. doi: 10.2307/1933693.
25. Magnussen, S., and Boudewn, P. 1998. Derivation of stand heights from airborne laser scanner data with canopy-based quantile estimators. Can. J. For. Res. 28: 1016-1031. doi:10.1139/cjfr-287-1016.
26. McElhinny, C., Gibbons, P., Brack, C., and Bauhas, J. 2005. Forest and woodland structural complexity: its definition and measurement. For. Ecol. Manage. 218: 1-24. doi:10.1016/j.foreco.2005. 08.034.
27. Meidinger, D., and Pojar, J. 1991. Ecosystems of British Columbia. B.C. Min. For. Special Rep. Ser. 6.
28. Mitchell, W.R., Green, R.N., Hope, F.D., and Klinka, K. 1989. Methods for biogeoclimatic ecosystem mapping. B.C. Min. For. Resour. Rep. RR89002-KL.
29. Morrison, M.L., and Raphael, M.G. 1993. Modeling the dynamics of snags. Ecol. Appl. 3(2): 322-330. doi:10.2307/1941835.
30. Nassset, 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.
31. Nsset, E. 2004. Practical large-scale forest stand inventory using a small-footprint airborne scanning laser. Scand. J. For. Res. 19: 164-179. doi:10.1080/02827580310019257.
32. Nsset, E., and Økland, T. 2002. Estimating tree height and tree crown properties using airborne scanning laser in a boreal nature reserve. Remote Sens. Environ. 79: 105-115. doi:10.1016/ S0034-4257(01)00243-7.
33. Norušis, MJ. 2008. Ordinal regression. In SPSS 16.0: advanced statistical procedures companion. Prentice Hall, Upper Saddle River, N.J. pp. 69-89.
34. Noss, R.F. 1999. Assessing and monitoring forest biodiversity: a suggested framework and indicators. For. Ecol. Manage. 115: 135-146. doi:10.1016/S0378-1127(98)00394-6.
35. O'Connell, A. 2006. Logistic regression models for ordinal response variables. Sage Publications, London, UK.
36. Oliver, C.D., and Larson, B.C. 1996. Forest stand dynamics. John Wiley & Sons, Toronto, Ont.
37. Pesonen, A., Maltamo, M., Eerikäinen, K., and Pakalèn, P. 2008. Airborne laser scanning-based prediction of coarse woody debris volumes in a conservation area. For. Ecol. Manage. 255: 32883296. doi:10.1016/j.foreco.2008.02.017.
38. Province of British Columbia. 2005. Monitoring and evaluation strategy. FRPA Resource Evaluation Program. B.C. Min. For. Ranges, B.C. Min. Environ., B.C. Min. Agric. Lands.
39. Reutebuch, S.E., Andersen, H.E., and McGaughey, R.J. 2005. Light detection and ranging (lidar): an emerging tool for multiple resource inventory. J. For. 103: 286-292.
40. Sambridge, M., Braun, J., and McQueen, H. 1995. Geophysical parameterisation and interpolation of irregular data using natural neighbours. Geophys. J. Int. 122: 837-857. doi:10.1111/j.1365246X.1995.tb06841.x.
41. Seielstad, C.A., and Queen, L.P. 2003. Using airborne laser altimetry to determine fuel models for estimating fire behavior. J. For. 101(4): 10-15.
42. Sibson, R. 1981. A brief description of natural neighbour interpolation. In Interpreting multivariate data. Edited by V. Barnett. Wiley, Chichester, UK. pp. 21-36.
43. Tabachnick, B.G., and Fidell, L.S. 2001. Using multivariate statistics. 4th ed. Allyn and Bacon, Toronto, Ont.
44. Vepakomma, U., St-Onge, B., and Kneeshaw, D. 2008. Spatially explicit characterization of boreal forest gap dynamics using multi-temporal lidar data. Remote Sens. Environ. 112: 23262340. doi:10.1016/j.rse.2007.10.001.
45. Warren Wilson, J. 1960. Inclined point quadrats. New Phytol. 59(1): 1-8. doi:10.1111/j.l469-8137.1960.tb06195.x.
46. Warren Wilson, J. 1963. Estimation of foliage denseness and foliage angle by inclined point quadrats. Aust. J. Bot. 11: 95-105. doi:10.1071/BT9630095.