Title :
Aboveground carbon estimation of forests
Author :
Goodenough, D.G. ; Gordon, Paula ; Chen, Huanting ; Niemann, K. Olaf ; Ma, Xiao-Li
Author_Institution :
Dept. of Comput. Sci., Univ. of Victoria, Victoria, BC, Canada
Abstract :
With increasing CO2 in the atmosphere due to fossil fuel burning, there is a need to quantitatively measure the aboveground carbon in forests. The best remote sensing sensors for this task in Canada are hyperspectral sensors to obtain major forest species, and lidar to measure tree height (H). The Greater Victoria Watershed District on Vancouver Island was selected as a test site and imaged with airborne AVIRIS 4m data and AISA 2m data. Fifty-four ground plots provided excellent ground reference data. Knowing the species, tree heights, and allometric equations relating to these species permits us to determine the aboveground carbon. This paper discusses these measurements, and the variation in carbon estimates due to errors of tree height and species classification.
Keywords :
atmospheric boundary layer; atmospheric composition; carbon compounds; hyperspectral imaging; remote sensing; AISA data; Canada; Greater Victoria Watershed District; Vancouver Island; airborne AVIRIS data; atmospheric carbon dioxide; forest aboveground carbon estimation; fossil fuel burning; hyperspectral sensors; lidar; remote sensing sensors; tree height; Biomass; Carbon; Equations; Hyperspectral sensors; Laser radar; Mathematical model; Vegetation; Carbon; Forest; Hyperspectral;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4799-1114-1
DOI :
10.1109/IGARSS.2013.6721322