Dynamics of the Swedish forest carbon pool between 2010 and 2015 estimated from satellite L-band SAR observations

Estimation of carbon stocks in forests and tracking their dynamics over time requires repeated and spatially dense observations. Sweden is one of the major forested countries on Earth with a carbon pool of approximately 1 PgC. Statistics on forest resources are regularly quantified by data collected at field inventory plots by the Swedish National Forest Inventory (NFI). Nonetheless, the sampling by the inventory does not provide detailed spatial knowledge of carbon stored in forests. Thanks to one of the worldwide densest datasets of L-band satellite synthetic aperture radar (SAR) images collected over the years, we assessed the estimation of carbon density on two years, i.e., 2010 and 2015, at pixel (25 m), landscape, county and national level, and investigated the reliability of changes over five years. While the maps of carbon density were obtained with a well-established approach, the uncertainty of the estimates were obtained with a novel procedure that accounted for observational variances and co-variances. The high spatial resolution of the maps revealed the small-scale patterns of carbon density in Swedish forests. However, the substantial uncertainties at the pixel level (25%–62% of the estimated value) prevented from a reliable estimate of carbon density difference at the pixel level. Average values at landscape and county scale were instead unbiased and in strong agreement with corresponding numbers from the Swedish NFI. The uncertainty at county level was between 3% and 12% of the reference mean value. Overall, the net carbon balance for Sweden was positive, with a magnitude comparable to estimates derived from data collected by the NFI. Between 2010 and 2015, Swedish forests acted as a carbon sink, with a net increase of carbon stocks by 2.5%. The high level of confidence in our results indicate that satellite L-band observations are potentially suitable for tracking large-scale forest carbon dynamics in boreal forests provided that multiple observations are available per year and that they are acquired with the same viewing geometry. •First assessment of forest carbon dynamics with L-band SAR data in Sweden.•Full characterization of per-pixel carbon density estimates and uncertainties.•Poor reliability of estimates at pixel level (25%–62% uncertainty).•Unbiased estimates and reduced uncertainty (3% - 12%) for averages at county level.•Carbon dynamics in Sweden from remote sensing agree with inventory-based statistics.