Estimating aboveground carbon density and its uncertainty in Borneo's structurally complex tropical forests using airborne laser scanning

Abstract. Borneo contains some of the world's most biodiverse and carbon-dense tropical forest, but this 750 000 km2 island has lost 62 % of its old-growth forests within the last 40 years. Efforts to protect and restore the remaining forests of Borneo hinge on recognizing the ecosystem services they provide, including their ability to store and sequester carbon. Airborne laser scanning (ALS) is a remote sensing technology that allows forest structural properties to be captured in great detail across vast geographic areas. In recent years ALS has been integrated into statewide assessments of forest carbon in Neotropical and African regions, but not yet in Asia. For this to happen new regional models need to be developed for estimating carbon stocks from ALS in tropical Asia, as the forests of this region are structurally and compositionally distinct from those found elsewhere in the tropics. By combining ALS imagery with data from 173 permanent forest plots spanning the lowland rainforests of Sabah on the island of Borneo, we develop a simple yet general model for estimating forest carbon stocks using ALS-derived canopy height and canopy cover as input metrics. An advanced feature of this new model is the propagation of uncertainty in both ALS- and ground-based data, allowing uncertainty in hectare-scale estimates of carbon stocks to be quantified robustly. We show that the model effectively captures variation in aboveground carbon stocks across extreme disturbance gradients spanning tall dipterocarp forests and heavily logged regions and clearly outperforms existing ALS-based models calibrated for the tropics, as well as currently available satellite-derived products. Our model provides a simple, generalized and effective approach for mapping forest carbon stocks in Borneo and underpins ongoing efforts to safeguard and facilitate the restoration of its unique tropical forests.This study was funded by the UK Natural Environment Research Council’s (NERC) Human Modified Tropical Forests research programme (grant numbers NE/K016377/1 and NE/K016407/1 awarded to the BALI and LOMBOK consortiums, respectively). We are grateful to NERC’s Airborne Research Facility and Data Analysis Node for conducting the survey and preprocessing the airborne data and to Abdullah Ghani for manning the GPS base station. David A. Coomes was supported in part by an International Academic Fellowship from the Leverhulme Trust. The Carnegie Airborne Observatory portion of the study was supported by the UN Development Programme, the Avatar Alliance Foundation, the Roundtable on Sustainable Palm Oil, the World Wildlife Fund and the Rainforest Trust. The Carnegie Airborne Observatory is made possible by grants and donations to Gregory P. Asner from the Avatar Alliance Foundation, the Margaret A. Cargill Foundation, the David and Lucile Packard Foundation, the Gordon and Betty Moore Foundation, the Grantham Foundation for the Protection of the Environment, the W. M. Keck Foundation, the John D. and Catherine T. MacArthur Foundation, the Andrew Mellon Foundation, Mary Anne Nyburg Baker and G. Leonard Baker Jr., and William R. Hearst III. The SAFE project was supported by the Sime Darby Foundation.pData\Local\Programs\Python\Python36-32\python.exe %USERPROFILE%\Documents\GitHub\OATs\oasis.py %USERPROFILE%\AppData\Local\Programs\Python\Python35-32\python.exe %USERPROFILE%\OATS\oasis.p