Temporal transformers for biomass estimation
This work proposes a hybrid CNN-Transformer framework for accurate above-ground biomass estimation from multi-temporal Sentinel-1 and Sentinel-2 imagery, introducing a Transformer-based temporal aggregation module with learnable positional encodings and multi-head self-attention, enabling the model to adaptively weight...