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<p>Carbon markets face growing criticism over unreliable measurements of carbon credits. Tropical peatlands, which contain some of Earth’s most concentrated carbon, represent a huge, untapped opportunity for emission reductions, but remain excluded from the market due to challenges in measuring emissions due to degradation. Here, we demonstrate satellite L-band Interferometric Synthetic Aperture Radar as a solution to estimate carbon dioxide emissions by accurately measuring peat subsidence. Our framework accounts for major radar noise sources in tropical environments that were previously unaddressed, and is validated against high-rate ground-measured peat motion in both space and time. The radar results capture episodic peat motion linked to dry-wet cycles across different land uses, and long-term rates accurate up to 0.6 mm yr<sup>−1</sup>, equivalent to 0.97 t CO<sub>2</sub> ha<sup>−1</sup> yr<sup>−1</sup> in emissions. This scalable, cost-effective approach provides a robust tool for Monitoring, Reporting, and Verification, benefitting carbon markets, local regulation, and global climate mitigation efforts.</p>

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Satellite radar advances carbon emissions accountability over tropical peat

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月26日

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  • Cheryl Tay,
  • A. Jonay Jovani-Sancho,
  • Lisna Yulianti,
  • Chris Evans,
  • Nathan Callaghan,
  • Adi Jaya,
  • Rino Salman,
  • Yujie Zheng,
  • Susilo Susilo,
  • Salampak Dohong,
  • Sang-Ho Yun

摘要

Carbon markets face growing criticism over unreliable measurements of carbon credits. Tropical peatlands, which contain some of Earth’s most concentrated carbon, represent a huge, untapped opportunity for emission reductions, but remain excluded from the market due to challenges in measuring emissions due to degradation. Here, we demonstrate satellite L-band Interferometric Synthetic Aperture Radar as a solution to estimate carbon dioxide emissions by accurately measuring peat subsidence. Our framework accounts for major radar noise sources in tropical environments that were previously unaddressed, and is validated against high-rate ground-measured peat motion in both space and time. The radar results capture episodic peat motion linked to dry-wet cycles across different land uses, and long-term rates accurate up to 0.6 mm yr−1, equivalent to 0.97 t CO2 ha−1 yr−1 in emissions. This scalable, cost-effective approach provides a robust tool for Monitoring, Reporting, and Verification, benefitting carbon markets, local regulation, and global climate mitigation efforts.