Professional paper
An assessment of airborne lidar for forest growth studies
A.S. Woodget
; Department of Geography, University of Durham, Science Laboratories, Durham, United Kingdom
D.N.M. Donoghue
; Department of Geography, University of Durham, Science Laboratories
P. Carbonneau
; Department of Geography, University of Durham, Science Laboratories
Abstract
Accurate and up-to-date information on forest growth rates is important for management purposes. Recent studies indicate that airborne LiDAR offers a rapid and more cost-effective approach that challenges traditional methods of forest inventorying and may have the potential not only to revolutionise forest management but also to provide key data for assessing terrestrial carbon stocks. This study aims to assess the potential of LIDAR to estimate forest growth of the temperate Sitka spruce plantation forests using canopy height distribution models at Kielder Forest, Northumberland. LIDAR data from 2003 and 2006 provides an excellent opportunity to contribute to existing work which has so far been limited in focus, looking primarily at individual tree level growth in the less densely stocked, slow-growing, cold climate forests of Scandinavia. LIDAR point cloud data from the first and last pulse returns are filtered and classified. Ground returns are used to create digital elevation models (DEM), and first returns used to create digital canopy height models (DCHM). Processed LIDAR data from both years are compared to estimate forest growth. In continuation, LIDAR plot height and growth values are extracted. The results are compared with plot level ground-based data. Height correlations are strong and positive. Growth is detected at all plot locations but correlations with ground-based data are weak and mostly negative.
Potential explanations for the lack of correlation are presented and discussed. Further study is necessary to quantify and eliminate systematic and random error within both the LiDAR and ground-based data before LIDAR may be used routinely for forest management purposes.
Keywords
LiDAR; Forestry; Growth; Kielder
Hrčak ID:
20678
URI
Publication date:
31.12.2007.
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