This analysis demonstrates improved classification accuracy using remote sensing and feature optimization for wetlands, suggesting better environmental management strategies.
Key Points
Classification accuracy improved by 1.81% using multi-temporal remote sensing data and deep learning, achieving 98.31%.
The proposed model, based on feature optimization, surpassed single-temporal and non-feature-based classification methods.
Observational analysis using coastal wetlands in Liaoning Province, applying a fine classification network tailored for complex ecological systems.
Results highlight the effectiveness of integrating multiple satellite images for enhanced wetland monitoring and decision-making.