Digital soil mapping in the Eastern Amazon: algorithm performance and classification uncertainty in hydromorphic and well-drained landscapes
Fabrício do Carmo Farias·João Fernandes da Silva Júnior·Lívia da Silva Santos·Gener Tadeu Pereira·Daniel Pereira Pinheiro·Rose Luiza Moraes Tavares·Rômulo José Alencar Sobrinho
Context Pedological mapping in the Amazon is essential but highly challenging, particularly in hydromorphic environments where soil properties and boundaries are difficult to delineate. Improving mapping accuracy is critical for sustainable land-use planning and ecosystem management, yet conventional approaches are often time-consuming and costly. Digital soil mapping (DSM) offers a promising alternative by integrating machine learning algorithms with geospatial data to predict soil mapping unit