Linear regression models to estimate carbon balance of boreal forests have been developed on the basis of CO2 flux measurements at several sites of the FLUXNET global network. Model estimations are in a satisfactory agreement with the data of the measurement taken in boreal forests of Canada (Manitoba, Thompson) and Russia (Krasnoyarsk region, Zotino). The correlation coefficient between calculated and measured values for needle forests is better than 0,9, while the annual regression model error versus experimental balance results is within 50 gC/m2/year. Monthly average values of the carbon balance for needle forests of the Krasnoyarsk region in 2001 were derived from ground-based and satellite meteorological data. Proceeding from satellite-derived data for vegetable cover types, maps of monthly average and annual carbon balance have been plotted, which illustrate a spatial-temporal distribution of CO2 absorption or emission intensity. It was shown that the major part of needle forests in the Krasnoyarsk region is СО2 sink with absorption of up to 300 gC/m2/year during the complete vegetative season.
satellite monitoring, carbon balance, boreal forests, regression models