Demonstrates superior mangrove mapping accuracy using a multi-modal deep learning approach, indicating robust performance despite limited training samples.
• A novel multi-modal deep learning framework for mangrove mapping. • Integrates tide-resilient phenology and spatial texture features. • Employs attention mechanisms for adaptive feature fusion. • Achieves superior accuracy across three Chinese coastal sites. • Demonstrates robust performance with limited training samples.
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Wu et al. (2026) studied this question.
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