Biomass Detection, Production and Usage by Edited by: Darko Matovic

By Edited by: Darko Matovic

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DTM was produced using the bisection principle. They also applied spline function interpolation in order to obtain the height above the ground. But in this work it is not obvious whether first or last return has been used to extract the canopy height, effecting the result significantly. 3 Applications To provide reliable results on tree location, height, and number of detected trees the local maximum detection method is introduced by Vazirabad and Karslioglu (2009). This method determines the canopy height by applying a variable window size.

2009). Testing LiDAR models of fractional cover across multiple forest ecozones, Remote Sensing of Environment, Vol. 113 (1), pp. E. J. (2008). Nearest neighbour imputation of species-level, plot-scale forest structure attributes from LiDAR data, Remote Sensing of Environment, Vol. 112 (5), pp. ; Kaartinen H. & Hyyppa H. (1999). Dectecting and stimating attributes for single trees using laser scanner, The Photogrammetric Journal of Finland, Vol. 16, pp. ; Kukko, A. & Holopainen, M. (2009). In: Shan, J.

156–171 Tovari, D. & Pfeifer, N. (2005). H. A. (2008). LiDAR-based mapping of forest volume and biomass by taxonomic group using structurally homogenous segments. Photogrammetric Engineering & Remote Sensing, Vol. 74 (8), pp. 1033–1044 Vosselman, G. (2000). J. B. (2004). Canopy structure parameters derived from multi-angular remote sensing data for terrestrial carbon studies. Climatic Change, Vol. 67, pp. ; Zhang, J. & Wang, L. (2010). An improved method for estimating forest canopy height using ICESat-GLAS full waveform data over sloping terrain A case study in Changbai mountains, China, International Journal of Applied Earth Observation and Geoinformation, Vol.

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