A shadow fraction method for mapping biomass of northern boreal black spruce forests using QuickBird imagery

We have developed and tested a method for mapping above-ground 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 acquired over three test sites and 108 ground sample plots (GSP) were used to develop and test the method. SF was calculated from the fraction of tree shadow area over the area of a reference square overlaid on the images. Linear regressions between biomass of GSP and SF from the images for each test site resulted in R2 in the range from 0.85 to 0.87 (except one case at 0.41), RMSE of 11 to 18 t/ha and bias of 2 to 5 t/ha. Statistical tests demonstrated that local regressions for the three test sites were not statistically significantly 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).