Estimating tree aboveground biomass in an Atlantic Forest remnant using different modelling methods - Zuñe, Felipe; Rodrigues, Pablo José Francisco Pena; Silva, Nílber Gonçalves da; Rojas-Idrogo, Consuelo; Delgado-Paredes, Guillermo Eduardo; Enrich-Prast, Alex; Sakuragui, Cássia Mônica (Journal of Environmental Analysis and Progress, 2024)
The Atlantic Forest stores vast amounts of aboveground biomass (AGB), yet it is still a challenge to estimate these stocks. We aimed to predict the AGB stock of the largest biodiversity remnant of Serra da Tiririca State Park (Rio de Janeiro, Brazil) by comparing the accuracy of generalized linear models (GLM) and random forest (RF) models, using data from field plots, remote sensing, and environmental variables. The plots showed an AGB of 371.12 Mg/ha. The comparison between the modelling methods revealed that the GLM is more accurate, still the RF is also fit to estimate the AGB of the remnant. The most accurate GLM predicted an AGB of 405.31 Mg/ha. We observed that the accuracy of the models improved when all predictor variables were combined. This study allowed us to improve the AGB estimates, and produce an AGB map useful for the management and conservation of the remnant