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We estimated forest Above Ground Biomass (AGB) of tropical peat swamp forests in the Indonesian province of Central Kalimantan through correlating airborne Light Detection And Ranging (LiDAR) data to forest inventory data. Two LiDAR point cloud metrics, the Quadratic Mean Canopy profile Height (QMCH) and the Centroid Height (CH), were correlated to the field derived AGB estimates. The regression models could be improved through the use of the LiDAR point densities as input. The highest coefficient of determination was achieved for CH (R2= 0.88; n= 52). Surveying with a LiDAR point density between 2-4 points per square meter (pt/m2) resulted in the best cost-benefit ratio. It was also shown that impact from logging and the associated AGB losses dating back more than 10 years could still be assessed by LiDAR but not by multispectral satellite imagery. Comparison with a Landsat based AGB estimate showed an overestimation of 60.8% in a 3.0 million ha study area.