Mapping tree biomass of northern boreal forest using shadowfraction from Quickbird imagery

摘要

Forest mapping from satellite remote sensing images is a convenient approach for regions with limited or absentrnforest inventories. We developed and tested a method to map above-ground biomass of black spruce (Picea mariana)rnstands in northeastern boreal regions of Canada using high resolution satellite images. Development of the methodrninvolved: 1) calculating shadow fraction (SF) using either classification (pixel-based) or segmentation andrnclassification (object-based) algorithms, (ii) generating linear regression relationships between SF and biomass fromrnground sample plots using several combinations of method parameters towards defining the best options,rn(iii) calculating a global linear regression applicable for all sites using the best options, and (iv) mapping biomass as arngrid layer for each site using the global regression. The linear relationships were calibrated using biomass estimatesrnof 108 ground sample plots and the shadow fraction of tree crowns calculated from QuickBird images representingrnthree test sites. The global regression relationship produced R2, RMSE and bias in the range of 85 to 88% (except onerncase at 44%), 14 to 18 t/ha and -3 to 8 t/ha, respectively. The results suggest that the method may be an efficientrnmeans of mapping biomass of black spruce stands in northern Canada.