Forests with high above ground biomass (AGB), including those growing on peat swamps, have historically not been thought suitable for biomass mapping and change detection using Synthetic Aperture Radar (SAR). However, by integrating L-band (λ = 0.23 m) SAR with lidar data from the ALOS and ICESat earth-observing satellites respectively, and 56 forest plots, we were able to create a forest biomass and change map for a 10.7 Mha section of eastern Sumatra that still contains high AGB peat swamp forest. Using a time series of SAR data we estimated changes in both forest area and AGB. We estimate that there were 274 ± 68 Tg AGB remaining in natural forest (≥ 20 m height) in the study area in 2007, with this stock reducing by approximately 11.4% over the subsequent 3 years. A total of 137.4 kha of the study area were deforested between 2007 and 2010; an average rate of 3.8% yr−1. The ability to attribute forest loss to different initial biomass values allows for far more effective monitoring and baseline modelling for avoided deforestation projects than traditional, optical-based remote sensing. Furthermore, given SAR's ability to penetrate the smoke and cloud which normally obscure land cover change in this region, SAR-based forest monitoring can be relied on to provide frequent imagery. This study demonstrates that even at L-band, which typically saturates at medium biomass levels (ca. 150 Mg ha−1), it is possible to make reliable estimates of not just the area but the carbon emissions resulting from land use change.