Mapping species-specific aboveground forest biomass for Guangxi using wall-to-wall airborne laser scanning data

• Used two data sources to develop species-specific AGB models. • AGB model developed with GAM provided the best performance. • Used such a model, DOM, and ALS data to generate species-specific AGB map. • In future, dynamically accurate AGB estimation is possible using this AGB map. Estimates of aboveground forest biomass (AGB) and carbon fluxes, especially on a species-specific basis, over an extensive area are crucial in decision-making in forestry. This study generated the species-specific AGB map with a resolution of 20 m using three data sources (field measurement, wall-to-wall airborne laser scanning (ALS) data, and aerial digital orthophoto map (DOM)). Field measurement and corresponding ALS data (point cloud density ≥ 2.0/m 2 ) were collected from 1086 sample plots located across four arbor forest types (Chinese fir (Cunninghamia lanceolata) , Eucalyptus (Eucalyptus grandis × Eucalyptus urophylla) , Masson pine (Pinus massoniana) , and other mixed broadleaved forests) in Guangxi province, China, between 2017 and 2019. Firstly, we developed the species-specific AGB models based on field measurement and ALS data using four modeling algorithms (linear regression (LR), support vector regression (SVR), random forest (RF), generalized additive modeling (GAM)). GAM models performed the best, with a relative RMSE ranged from 13.6 % to 35.3 %. Secondly, forest type assigned to each grid cell in the rasterized wall-to-wall ALS data was derived from DOM-derived forest-type distribution map. Finally, a species-specific AGB map with a resolution of 20 m was generated by inputting forest type and ALS metrics for each grid cell in the rasterized wall-to-wall ALS data into the species-specific GAM models. Our AGB map could be useful to formulate the effective strategies of forest management. In the future, one can monitor the changes of AGB or carbon storage in Guangxi using our AGB map.