July 25, 2025Open Access

Semantic Segmentation of High-Resolution Remote Sensing Images Based on RS³Mamba: An Investigation on the Extraction Algorithm of Rural Compound Utilization Status

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Research demonstrates improved feature extraction accuracy in rural compound images, suggesting advanced algorithms enhance remote sensing analysis.

MAIN FINDING: The RS³Mamba model achieves an average mIoU of 79.64% for extracting rural compound features.
KEY EVIDENCE: The approach shows an 8.35% improvement in F1 score compared to traditional models like U-Net and ResNet.
APPROACH: Utilizing Gaofen-2 satellite images, the study employs a multiscale attention feature fusion for enhanced segmentation.
SIGNIFICANCE: This research provides valuable tools for accurately assessing rural compound utilization, aiding in land management.

Fang et al. (2025) studied this question.

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July 25, 2025Open Access

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Authors

Research demonstrates improved feature extraction accuracy in rural compound images, suggesting advanced algorithms enhance remote sensing analysis.

MAIN FINDING: The RS³Mamba model achieves an average mIoU of 79.64% for extracting rural compound features.
KEY EVIDENCE: The approach shows an 8.35% improvement in F1 score compared to traditional models like U-Net and ResNet.
APPROACH: Utilizing Gaofen-2 satellite images, the study employs a multiscale attention feature fusion for enhanced segmentation.
SIGNIFICANCE: This research provides valuable tools for accurately assessing rural compound utilization, aiding in land management.

Fang et al. (2025) studied this question.

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