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Monitoring fine-scale natural and logging-related tropical forest degradation using Sentinel-1

Sentinel-1 C-band radar data can effectively detect fine-scale natural and logging-related canopy disturbances in tropical forests, achieving over 80% detection rates for gaps larger than 300 m² using a physical-based method and validated with drone-based imagery, signaling a significant improvement over existing radar-based disturbance detection methods. The results highlight that gap size primarily drives detection […]

Sentinel-1 C-band radar data can effectively detect fine-scale natural and logging-related canopy disturbances in tropical forests, achieving over 80% detection rates for gaps larger than 300 m² using a physical-based method and validated with drone-based imagery, signaling a significant improvement over existing radar-based disturbance detection methods. The results highlight that gap size primarily drives detection accuracy, while gap depth has a smaller, but significant effect.

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