Earth Observation technologies for agricultural carbon credits
a review
- verfasst von
- Theodora Angelopoulou, Athanasios T. Balafoutis, Sabine Chabrillat
- Abstract
Earth Observation (EO) technologies offer accurate measurements of surface composition, enabling the monitoring of key variables linked to carbon credits, such as carbon content and sequestration potential. EO technologies also support the assessment of sustainable agricultural practices by tracking their impact on soil health and ecosystem dynamics. These practices enhance soil organic carbon content, promote biomass growth where applicable, and reduce greenhouse gas emissions, thereby contributing to carbon sequestration. These contributions can be recognized and incentivized through carbon credit systems. EO technologies provide continuous, high-resolution data, and can assist on accurately assessing numerus properties and therefore verify carbon credits, ensuring transparency and reliability in carbon trading markets. This review explores the pivotal role of EO technologies, mainly optical, in the assessment, generation, and verification of carbon credits within the agricultural sector, mainly croplands and aims to provide insights into the advantages of using EO for carbon credit assessment. These include, improved accuracy and reduced monitoring costs, while also discussing the limitations and potential solutions to overcome related obstacles. The findings highlight the transformative potential of EO in enhancing the credibility and efficiency of carbon credit systems, ultimately contributing to global climate change mitigation efforts.
- Organisationseinheit(en)
-
Institut für Bodenkunde
- Externe Organisation(en)
-
GFZ Helmholtz-Zentrum für Geoforschung
Center For Research And Technology - Hellas
- Typ
- Übersichtsarbeit
- Journal
- Smart Agricultural Technology
- Band
- 12
- Publikationsdatum
- 12.2025
- Publikationsstatus
- Veröffentlicht
- Peer-reviewed
- Ja
- ASJC Scopus Sachgebiete
- Informatik (sonstige), Allgemeine Agrar- und Biowissenschaften, Artificial intelligence
- Ziele für nachhaltige Entwicklung
- SDG 2 – Kein Hunger, SDG 13 – Klimaschutzmaßnahmen
- Elektronische Version(en)
-
https://doi.org/10.1016/j.atech.2025.101493 (Zugang:
Offen)