Effects of forest degradation classification on the uncertainty of aboveground carbon estimates in the Amazon

Abstract

Background: Tropical forests are critical for the global carbon budget, yet they have been threatened by deforestation and forest degradation by fre, selective logging, and fragmentation. Existing uncertainties on land cover classifcation and in biomass estimates hinder accurate attribution of carbon emissions to specifc forest classes. In this study, we used textural metrics derived from PlanetScope images to implement a probabilistic classifcation framework to identify intact, logged and burned forests in three Amazonian sites. We also estimated biomass for these forest classes using airborne lidar and compared biomass uncertainties using the lidar-derived estimates only to biomass uncertainties considering the forest degradation classifcation as well.

Results: Our classifcation approach reached overall accuracy of 0.86, with accuracy at individual sites varying from 0.69 to 0.93. Logged forests showed variable biomass changes, while burned forests showed an average carbon loss of 35%. We found that including uncertainty in forest degradation classifcation signifcantly increased uncertainty and decreased estimates of mean carbon density in two of the three test sites.

Conclusions: Our fndings indicate that the attribution of biomass changes to forest degradation classes needs to account for the uncertainty in forest degradation classifcation. By combining very high-resolution images with lidar data, we could attribute carbon stock changes to specifc pathways of forest degradation. This approach also allows quantifying uncertainties of carbon emissions associated with forest degradation through logging and fre. Both the attribution and uncertainty quantifcation provide critical information for national greenhouse gas inventories

Citation

Rangel Pinagé, Ekena; Keller, Michael; Peck, Christopher P.; Longo, Marcos; Duffy, Paul; Csillik, Ovidiu. 2023. Effects of forest degradation classification on the uncertainty of aboveground carbon estimates in the Amazon. Carbon Balance and Management. 18(1): 378-. https://doi.org/10.1186/s13021-023-00221-5.