Use of low point density ALS data to estimate stand-level structural variables in Mediterranean Aleppo pine forest

Forestry

Volumn 89, Issue 4, 2016, Pages 373-382

  Montealegre, A L ^a   Lamelas, M T ^a,b   De La Riva, J ^a   Garcia Martin A ^a,b   Escribano, F ^b  

^a UNIVERSITY OF ZARAGOZA   (Spain)

^b CENTRO UNIVERSITARIO DE LA DEFENSA   (Spain)

Author keywords

airborne laser scanning; Aleppo pine; forest inventory; LiDAR; Mediterranean environment; multiple regression analysis

Indexed keywords

AIRBORNE SENSOR; CANOPY ARCHITECTURE; CONIFEROUS FOREST; COORDINATE; FOREST INVENTORY; FOREST MANAGEMENT; LASER METHOD; LIDAR; MEDITERRANEAN ENVIRONMENT; REGRESSION ANALYSIS; STAND STRUCTURE;

MEDITERRANEAN REGION; SPAIN;

PINUS HALEPENSIS;

EID: 84984791543     PISSN: 0015752X     EISSN: 14643626     Source Type: Journal    
DOI: 10.1093/forestry/cpw008     Document Type: Article

References (59)

1. 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.
2. Baskerville, G.L. 1972 Use of logarithmic regression in the estimation of plant biomass. Can. J. For. Res. 2, 49-53.
3. Bouvier, M., Durrieu, S., Fournier, R.A. and Renaud, J.-P. 2015 Generalizing predictive models of forest inventory attributes using an area-based approach with airborne LiDAR data. Remote Sens. Environ. 156, 322-334.
4. Chen, Q., Gong, P., Baldocchi, D. and Tian, Y.Q. 2007 Estimating basal area and stem volume for individual trees from LiDAR data. Photogramm. Eng. Remote Sensing. 73, 1355-1365.
5. Chuvieco, E. 2009 Earth Observation of Wildland Fires in Mediterranean Ecosystems. Springer.
6. Coops, N., Hilker, T., Wulder, M., St-Onge, B., Newnham, G., Siggins, A. et al. 2007 Estimating canopy structure of Douglas-fir forest stands from discrete-return LiDAR. Trees Struct. Funct. 21, 295-310.
7. Evans, J.S. and Hudak, A.T. 2007 A multiscale curvature algorithm for classifying discrete return LiDAR in forested environments. IEEE Trans. Geosci. Remote Sens. 45, 1029-1038.
8. Evans, J., Hudak, A., Faux, R. and Smith, A.M. 2009 Discrete return lidar in natural resources: recommendations for project planning, data processing, and deliverables. Remote Sens. 1, 776-794.
9. Finney, D.J. 1941 On the distribution of a variate whose logarithm is normally distributed. Suppl. J. J. R. Stat. Soc. 7, 155-161.
10. Fournier, T.P., Battipaglia, G., Brossier, B. and Carcaillet, C. 2013 Fire-scars and polymodal age-structure provide evidence of fire-events in an Aleppo pine population in southern France. Dendrochronologia 31, 159-164.
11. Garcá, D., Godino, M. and Mauro, F. 2012 Lidar: Aplicación Prá ctica Al Inventario Forestal. Editorial Academia Española, p. 196.
12. Gonzalez-Ferreiro, E., Dieguez-Aranda, U. and Miranda, D. 2012 Estimation of stand variables in Pinus radiata D. Don plantations using different LiDAR pulse densities. Forestry 85, 281-292.
13. González-Olabarria, J.-R., Rodrguez, F., Fernández-Landa, A. and Mola-Yudego, B. 2012 Mapping fire risk in the Model Forest of Urbión (Spain) based on airborne LiDAR measurements. For. Ecol. Manage. 282, 149-156.
14. Hair, J.F., Anderson, R.E., Tatham, R.L. and Black, W.C. 1999 Análisis multivariante. 5 edn. Prentice Hall Iberia, p. 832.
15. 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.
16. Hollaus, M., Wagner, W., Maier, B. and Schadauer, K. 2007 Airborne laser scanning of forest stem volume in a mountainous environment. Sensors 7, 1559-1577.
17. Holmgren, J., Nilsson, M. and Olsson, H. 2003 Estimation of tree height and stem volume on plots using airborne laser scanning. For. Sci. 49, 419-428.
18. Kraus, K. and Pfeifer, N. 1998 Determination of terrain models in wooded areas with airborne laser scanner data. ISPRS J. Photogramm. Remote Sens. 53, 193-203.
19. Kronseder, K., Ballhorn, U., Böhm, V. and Siegert, F. 2012 Above ground biomass estimation across forest types at different degradation levels in Central Kalimantan Using LiDAR data. Int. J. Appl. Earth Obs. Geoinform. 18, 37-48.
20. Leboeuf, A., Fournier, R.A., Luther, J.E., Beaudoin, A. and Guindon, L. 2012 Forest attribute estimation of northeastern Canadian forests using QuickBird imagery and a shadow fraction method. For. Ecol. Manage. 266, 66-74.
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.
22. Lefsky, M.A., Cohen,W.B., Harding, D.J., Parker, G.G., Acker, S.A. and Gower, S.T. 2002a Lidar remote sensing of above-ground biomass in three biomes. Global Ecol. Biogeogr. 11, 393-399.
23. Lefsky, M.A., Cohen,W.B., Parker, G.G. and Harding, D.J. 2002b Lidar remote sensing for ecosystem studies. BioScience 52, 19-30.
24. Le Toan, T., Beaudoin, A., Riom, J. and Guyon, D. 1992 Relating forest biomass to SAR data. IEEE Trans. Geosci. Remote Sens. 30, 403-411.
25. Li, Y., Andersen, H.-E. and McGaughey, R. 2008 A comparison of statistical methods for estimating forest biomass from light detection and ranging data. West. J. Appl. Forest. 23, 223-231.
26. Li, W., Guo, Q., Jakubowski, M.K. and Kelly, M. 2012 A new method for segmenting individual trees from the lidar point cloud. Photogramm. Eng. Remote Sens. 78, 75-84.
27. Lim, K., Treitz, P., Wulder, M., St-Onge, B. and Flood, M. 2003 LiDAR remote sensing of forest structure. Prog. Phys. Geogr. 27, 88-106.
28. Magnussen, S., Eggermont, P. and LaRiccia, V.N. 1999 Recovering tree heights from airborne laser scanner data. Forest Sci. 45, 407-422.
29. 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.
30. Maltamo, M., Næsset, E. and Vauhkonen, J. 2014 Forestry Applications of Airborne Laser Scanning: Concepts and Case Studies. Managing Forest Ecosystems. Springer London, Limited.
31. McGaughey, R. 2009 FUSION/LDV: Software for LIDAR Data Analysis and Visualization. US Department of Agriculture, Forest Service, Pacific Northwest Research Station.
32. Means, J., Acker, S., Harding, D., Blair, J., Lefsky, M., Cohen,W. et al. 1999 Use of large-footprint scanning airborne LiDAR to estimate forest stand characteristics in the Western Cascades of Oregon. Remote Sens. Environ. 67, 298-308.
33. Means, J.E., Acker, S.A., Fitt, B.J., Renslow, M., Emerson, L. and Hendrix, C.J. 2000 Predicting forest stand characteristics with airborne Lidar. Photogramm. Eng. Remote Sens. 66, 1367-1371.
34. Montealegre, A., Lamelas, M., Tanase, M. and de la Riva, J. 2014 Forest fire severity assessment using ALS data in a Mediterranean environment. Remote Sens. 6, 4240-4265.
35. Montealegre, A., Lamelas, M. and de la Riva, J. 2015 A comparison of open source LiDAR filtering algorithms in a Mediterranean forest environment. IEEE J. Select. Top. Appl. Earth Observ. Remote Sens. 8, 4072-4085.
36. Moya, D., De las Heras, J., López-Serrano, F.R. and Leone, V. 2008 Optimal intensity and age of management in young Aleppo pine stands for post-fire resilience. For. Ecol. Manage. 255, 3270-3280.
37. Næsset, E. 1997a Determination of mean tree height of forest stands using airborne laser scanner data. ISPRS J. Photogramm. Remote Sens. 52, 49-56.
38. Næsset, E. 1997b Estimating timber volume of forest stands using airborne laser scanner data. Remote Sens. Environ. 61, 246-253.
39. 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.
40. Næsset, E. and Bjerknes, K.-O. 2001 Estimating tree heights and number of stems in young forest stands using airborne laser scanner data. Remote Sens. Environ. 78, 328-340.
41. Næsset, E. and Gobakken, T. 2008 Estimation of above-and below-ground biomass across regions of the boreal forest zone using airborne laser. Remote Sens. Environ. 112, 3079-3090.
42. Naesset, E. and Okland, T. 2002 Estimating tree height and tree crown properties using airborne scanning laser in a boreal nature reserve. Remote Sens. Environ. 79, 105-115.
43. Næsset, E., Gobakken, T., Holmgren, J., Hyyppä , H., Hyyppä , J., Maltamo, M. et al. 2004 Laser scanning of forest resources: the nordic experience. Scand. J. Forest Res. 19, 482-499.
44. Nilsson, M. 1996 Estimation of tree heights and stand volume using an airborne lidar system. Remote Sens. Environ. 56, 1-7.
45. Patenaude, G., Hill, R.A., Milne, R., Gaveau, D.L.A., Briggs, B.B.J. and Dawson, T.P. 2004 Quantifying forest above ground carbon content using LiDAR remote sensing. Remote Sens. Environ. 93, 368-380.
46. Popescu, S.C. and Zhao, K. 2008 A voxel-based lidar method for estimating crown base height for deciduous and pine trees. Remote Sens. Environ. 112, 767-781.
47. Renslow, M. 2013 Manual of Airborne Topographic Lidar. The American Society for Photogrammetry and Remote Sensing.
48. Smith, D.M. 1997 The Practice of Silviculture: Applied Forest Ecology. Wiley.
49. Sprugel, D.G. 1983 Correcting for bias in log-transformed allometric equations. Ecology 64, 209-210.
50. Stone, C., Penman, T. and Turner, R. 2011 Determining an optimal model for processing lidardata at the plot level: results fora Pinus radiata plantation in New SouthWales, Australia. N. Zeal. J. Forest. Sci. 41, 191-205.
51. Tanase, M.,dela Riva, J., Santoro, M., Pé rez-Cabello, F.andKasischke, E.2011 Sensitivity of SAR data to post-fire forest regrowth in Mediterranean and boreal forests. Remote Sens. Environ. 115, 2075-2085.
52. Temesgen, H., LeMay, V. and Mitchell, S.J. 2005 Tree crown ratio models for multi-species and multi-layered stands of southeastern British Columbia. Forest. Chron. 81, 133-141.
53. Treitz, P., Lim, K.,Woods, M., Pitt, D., Nesbitt, D. and Etheridge, D. 2012 LiDAR sampling density for forest resource inventories in Ontario, Canada. Remote Sens. 4, 830-848.
54. Véga, C. and Durrieu, S. 2011 Multi-level filtering segmentation to measure individual tree parameters based on Lidar data: application to a mountainous forest with heterogeneous stands. Int. J. Appl. Earth Observ. Geoinform. 13, 646-656.
55. Vicente-Serrano, S.M., Lasanta, T. and Gracia, C. 2010 Aridification determines changes in forest growth in Pinus halepensis forests under semiarid Mediterranean climate conditions. Agr. Forest Meteorol. 150, 614-628.
56. Vosselman, G. and Maas, H.-G. 2010 Airborne and Terrestrial Laser Scanning. Whittles Publishing, p. 320.
57. Watt, P.andWatt, M.2013Development ofanationalmodelof Pinus radiata stand volume from LiDAR metrics for New Zealand. Int. J. Remote Sens. 34, 5892-5904.
58. Watt, M., Meredith, A.,Watt, P. and Gunn, A. 2013 Use of LiDAR to estimate stand characteristics for thinning operations in young Douglas-fir plantations. N. Zeal. J. Forest. Sci. 43, 18.
59. Zhao, K., Popescu, S. and Nelson, R. 2009 Lidar remote sensing of forest biomass: a scale-invariant estimation approach using airborne lasers. Remote Sens. Environ. 113, 182-196.