Summary
Published in Remote Sensing of Environment, vol. 110, p. 488-500. https://doi.org/10.1016/j.rse.2006.05.025
We developed and tested a method for mapping aboveground forest biomass of black spruce (Picea mariana (Mill.) B.S.P.) stands in northern boreal forests of eastern Canada. The method uses QuickBird images and applies image-processing algorithms to extract tree shadow fraction (SF) as a predictive variable for estimating biomass. Three QuickBird images that were acquired over three test sites and 108 ground sample plots (GSP) were used to develop and test the method. SF was calculated using the tree shadow area over the area of a reference square overlain upon the images. Statistical tests demonstrated that local regressions for the three test sites were not statistically different. Consequently, a global regression was calculated with all GSP and produced R2, RMSE, and bias of 0.84, 14.2 t/ha and 4.2 t/ha, respectively. While generalization of these results to extended areas of the boreal forest would require further assessment, the SF method provided an efficient means for mapping biomass of black spruce stands for three test areas that are characteristic of the northern boreal forest of eastern Canada (Boreal and Taiga Shield Ecozones).
Sector(s):
Forests
Categorie(s):
Scientific Article
Theme(s):
Cartography and Data, Imaging and LiDAR
Departmental author(s):
Author(s)
LEBOEUF, Antoine, André BEAUDOIN, Richard A. FOURNIER, Luc GUINDON, Joan E. LUTHER and Marie-Claude LAMBERT
Year of publication :
2007
How to get the publication :
PDF available upon request. Available at the Direction des inventaires forestiers
Keywords :
Remote sensing, Mapping, Biomass, Subarctic forest, Northern boreal forest, Black spruce, QuickBird, Shadow fraction
