Estimation of above ground forest biomass at Muğla using ICESat/GLAS and Landsat data

Abstract Accurate estimation of aboveground forest biomass (AGB) is essential for carbon budgets. In this study we present the use of both satellite lidar (ICESat/GLAS) and optical (Landsat) data for estimation of AGB at Mugla province of Turkey. We collected field data in 2013 and 2014. Plot-level AGB estimates were calculated using equations representative to the species at the study area. Various GLAS parameters and Landsat vegetation indices were modeled using multiple regression analysis to estimate AGB. In the first model (Model 1 ) height of median energy (HOME) and the ratio of HOME to maximum vegetation height (%HOME) parameter of GLAS showed relation with field based AGB estimates with a coefficient of determination (R 2 ) of 0.88. The second model (Model 2 ) that uses the AGB estimations of Model 1 and the variables obtained from Landsat TM indices had a R 2 of 0.73. The resulting map was validated with field measurements and it has been found that calculation of AGB using Model 1 and Model 2 allows us to explain 79% of the variability of AGB at the study area with a RMSE of ±28.16 t/ha. This study is the very first study on estimation of above ground forest biomass across Turkey, using a Lidar sensor, ICESat/GLAS with the combination of an optical system, Landsat. The results presented in this paper provide an example of the ability to use ICESat/GLAS waveforms and Landsat imagery for assessing aboveground biomass at the areas where airborne lidar data is not widely available.