Improved Cerrado Wetland Mapping Through Seasonal Moisture Metrics, Terrain Information and Semantic Segmentation

ABSTRACT

Wetlands, especially peatlands, are fundamental to the functioning of the Brazilian Cerrado. They play essential roles in hydrological and carbon cycling, biodiversity conservation, and the support of local livelihoods. However, they remain poorly mapped and are not regularly monitored. Ongoing large‐scale land use change combined with the climate crisis is intensifying the drying and degradation of these wetlands, highlighting the need for specific wetland assessments to inform adaptive conservation and management strategies. To extend the thematic details of current land cover products, we present a new approach to map swamp savanna and gallery forest, two ecologically distinct and carbon‐rich wetland types in the Cerrado. We tested combinations of Sentinel‐2‐based spectral‐temporal moisture metrics and Sentinel‐1 polarized metrics from different time periods of a year using a U‐Net architecture for image classification. Class‐wise F1 scores reached 0.91 and 0.89, respectively, over the training area with homogeneous and consistent predictions. Adding Sentinel‐1 VV and VH spectral‐temporal metrics produced heterogeneous results, partly improving models. The segmentation models were applied with high accuracies to a transfer region of comparable environmental characteristics (F1: 0.85–0.90) and with lower accuracies to an environmentally differing region (F1: 0.67–0.73). From a methods perspective, the results suggest that upscaling to the entire Cerrado with such a model is feasible, despite the need for regional retraining for better model robustness.