Work

Overcoming spectral and tidal challenges in mangrove mapping with a multi-modal deep learning network fusing phenological and texture features

Year: 2026

Type: article

Abstract: • 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.

Source: International Journal of Applied Earth Observation and Geoinformation

DOI: 10.1016/j.jag.2026.105377

Authors: Wenting Wu, Xiaojin Huang, Chunpeng Chen, Mengmeng Li

Institutions: Fuzhou University, State Key Laboratory of Estuarine and Coastal Research, East China Normal University

Language: English

Topic: Remote-Sensing Image Classification

Subfield: Media Technology

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,550

Funders: National Natural Science Foundation of China, State Key Laboratory of Estuarine and Coastal Research