ArticleScientific reports2025
Towards a remote sensing-based assessment of carbon emissions from peatlands.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Hierarchical feature alignment for cross-view geo-localization.Scientific reports · 2026Article
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Authors and funding
4 authors.
Funding
Abstract
Among greenhouse gases-generating sources, biosphere sources from natural carbon (C) reservoirs play a significant role. A vital component of the biosphere is peatlands-the largest natural terrestrial carbon storage on the earth. Peatlands function as both C sink and C source, showing their pivot role in mitigating GHGs. Releasing C results from peat oxidation-the decomposition of organic matter in the peat. This decomposition reduces the volume of peat and, hence, causes subsidence. This study introduces an exclusive remote-sensing-based framework for estimating carbon emissions from peatlands using subsidence rates. This framework integrates peat properties-bulk density and soil organic carbon-with the oxidated peat subsidence, which refers to the proportion of subsidence attributed to the oxidation process rather than shrinkage. Achieving a fully remote-sensing-based approach promises time-effective, cost-effective, and consistent C emission monitoring even in unreachable places in peatlands, addressing the critical need for global climate change mitigation strategies. However, this achievement requires collaborative efforts among researchers to implement it in other sites to improve dataset accuracy for each parameter. By improving this framework, the scientific community can pave the way for robust, large-scale assessments of peatland C emission.
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Registered trials
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