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Abstract Soil erosion threatens ecological security and water conservation in mountainous small watersheds. To improve pixel-level assessment under complex terrain and incomplete multi-source raster inputs, we developed ST-TransUNet-R, a deep-learning framework that integrates a ResNet-50 encoder, a Transformer module, a joint-validity mask, and masked mean squared error loss.
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