Study of shrub cover and height using LIDAR data in a Mediterranean area

Forest Science

Volumn 57, Issue 3, 2011, Pages 171-179

  Estornell, Javier ^a   Ruiz, Luis Angel ^a   Velázquez Marti, Borja ^a  

^a UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

Author keywords

Biomass; Canopy height model; Digital terrain models; LIDAR; Shrub height

Indexed keywords

FORESTRY; MEAN SQUARE ERROR; OPTICAL RADAR; SPECTROSCOPY;

CANOPY HEIGHT MODELS; DIGITAL TERRAIN MODEL; DOMINANT HEIGHT; FIELD MEASUREMENT; HIGH-ACCURACY; LIGHT DETECTION AND RANGING; MEDITERRANEAN AREAS; ROOT MEAN SQUARE ERRORS; SHRUB HEIGHT; SPECTRAL IMAGES;

VEGETATION;

EID: 84860408443     PISSN: 0015749X     EISSN: None     Source Type: Journal    
DOI: 10.1093/forestscience/57.3.171     Document Type: Article

References (30)

1. Baltsavias, E.P. 1999. Airborne laser scanning: Existing systems and firms and other resources. ISPRS J. Photogramm. Remote Sens. 54:164-198.
2. Bork, E.W., and J.G. Su. 2007. Integrating lidar data and multispectral imagery for enhanced classification of rangeland vegetation: A meta analysis. Remote Sens. Environ. 111:11-24.
3. Clark, M.L., D.B. Clark, and D.A. Roberts. 2004. Small-footprint lidar estimation of sub-canopy elevation and tree height in a tropical rain forest landscape. Remote Sens. Environ. 91:68-89.
4. Gaveau, D.L.A., and R.A. Hill. 2003. Quantifying canopy height underestimation by laser pulse penetration in small-footprint airborne laser scanning data. Can. J. Remote Sens. 29:650-657.
5. Hill, R.A., and A.G. Thomson. 2005. Mapping woodland species composition and structure using airborne spectral and lidar data. Int. J. Remote Sens. 26:3763-3779.
6. Hopkinson, C., L.E. Chasmer, G. Sass, I.F. Creed, M. Sitar, W. Kalbfleisch, and P. Treitz. 2005. Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment. Can. J. Remote Sens. 31:191-206.
7. Hudak, A.T., N.L. Crookston, J.S. Evans, M.J. Falkowski, A.M.S. Smith, P.E. Gessler, and P. Morgan. 2006. Regression modeling and mapping of coniferous forest basal area and tree density from discrete-return lidar and multispectral satellite data. Can. J. Remote Sens. 32:126-138.
8. Hyyppä, J., H. Hyyppä, D. Leckie, F. Gougeon, X. Yu, and M. Maltamo. 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.
9. Hyyppä, J., and M. Inkinen. 1999. Detecting and estimating attributes for single trees using laser scanner. Photogramm. J. Finl. 16:27-42.
10. Maltamo, M., K. Eerik äinen, J. Pitk änen, J. Hyyppä, and M. Vehmas. 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.
11. Means, J.E., S.A. Acker, J.F. Brandon, M. Renslow, L. Emerson, and C.J. Hendrix. 2000. Predicting forest stand characteristics with airborne scanning lidar. Photogramm. Eng. Remote Sens. 66:1367-1371.
12. Mundt, J.T., D.R. Streutker, and N.F. Glenn. 2006. Mapping sagebrush distribution using fusion of hyperspectral and lidar classifications. Photogramm. Eng. Remote. Sens. 72:47-54.
13. Mutlu, M., S.C. Popescu, C. Stripling, and T. Spencer. 2008. Mapping surface fuel models using lidar and multispectral data fusion for fire behavior. Remote Sens. Environ. 112:274-285.
14. Næsset, E. 2004. Accuracy of forest inventory using airborne laser scanning: evaluating the first Nordic full-scale operational project. Scand. J. For. Res. 19:554-557.
15. Nelson, R., W. Krabill, and J. Tonelli. 1998. Estimating forest biomass and volume using airborne laser data. Remote Sens. Environ. 24:247-267.
16. Nelson, R., A. Short, and M. Valenti. 2004. Measuring biomass and carbon in Delaware using an airborne profiling lidar. Scand. J. For. Res. 19:500-511.
17. Persson, A., J. Holmgren, and U. Söderman. 2002. Detecting and measuring individual trees using an airborne laser scanner. Photogramm. Eng. Remote Sens. 68:925-932.
18. Popescu, S.C. 2007. Estimating biomass of individual pine trees using airborne lidar. Biomass Bioenergy 31:646-655.
19. Popescu, S.C., R.H. Wynne, and R.F. Nelson. 2002. Estimating plot-level tree heights with lidar: Local filtering with a canopy-height based variable window size. Comp. Electr. Agric. 37:71-95.
20. Reutebuch, S.E., H.-E. Andersen, and R.J. McGaughey. 2005. Light detection and ranging (lidar): An emerging tool for multiple resource inventory. J. For. 103:286-292.
21. Riaño, D., E. Chuvieco, S.L. Ustin, J. Salas, J.R. Rodríguez-Pérez, L.M. Ribeiro, D.X. Viegas, J.M. Moreno, and H. Fernández. 2007. Estimation of shrub height for fueltype mapping combining airborne lidar and simultaneous color infrared ortho imaging. Int. J. Wildl. Fire 16:341-348.
22. Sithole, G., and G. Vosselman. 2004. Experimental comparison of filter algorithms for bare-earth extraction from airborne laser scanning point clouds. ISPRS J. Photogramm. Remote Sens. 59:85-101.
23. Streutker, D.R., and N.F. Glenn. 2006. Lidar measurement of sagebrush steppe vegetation heights. Remote Sens. Environ. 102:135-145.
24. Su, J.G., and E.W. Bork. 2006. Influence of vegetation, slope, and lidar sampling angle on DEM accuracy. Photogramm. Eng. Rem. Sens. 72:1265-1274.
25. Verrelst, J., G.W. Geerling, K.V. Sykora, and J.G.P.W. Clevers. 2009. Mapping of aggregated floodplain plant communities using image fusion of CASI and LIDAR data. Int. J. Appl. Earth Observ. Geoinform. 11:83-94.
26. Velázquez-Marti, B., and E. Annevelink. 2009. GIS application to define biomass collection points as sources for linear programming of delivery networks. Trans. ASABE 52(4):1069-1078.
27. Velázquez-Marti, B., and E. Fernández-Gonzalez. 2009. Analysis of the process of biomass harvesting with collectingchippers fed by pick up headers in plantations of olive trees. Biosyst. Eng. 104(2):184-190.
28. Velázquez-Marti, B., and E. Fernández-Gonzalez. 2010. Mathematical algorithms to locate factories to transform biomass in bioenergy focused on logistic network construction. Renew. Energ. 35(9):2136-2142.
29. Velázquez-Marti, B., E. Fernández-Gonzalez, J. Estornell, and L.A. Ruiz. 2010. Dendrometric and dasometric analysis of the bushy biomass in Mediterranean forests. For. Ecol. Manag. 259(5):875-882.
30. Yu, X., J. Hyyppä, H. Kaartinen, and M. Maltamo. 2004. Automatic detection of harvested trees and determination of forest growth using airborne laser scanning. Remote Sens. Environ. 90:451-462.