| 来源类型 | Project |
| 规范类型 | 研究项目 |
| Exploring the use of machine learning to detect environmental changes and management options affecting soil carbon storage and greenhouse gas emissions | |
| Matthew Fielding | |
| 开始日期 | 2021 |
| 结束日期 | 2021 |
| 语种 | 英语 |
| 概述 | Using innovative technologies we are investigating new methods to measure and monitor soil organic carbon stocks quickly and at scale. |
| 摘要 | Using artificial intelligence, machine learning, and remote sensing technologies, we are investigating new methods to measure and monitor soil organic carbon stocks quickly and at scale. Our vision is a global monitoring system that will lead to more informed climate strategies. |
| 主题 | Climate : Adaptation, Mitigation ; Governance : Innovation |
| 标签 | soils ; technology ; methodology |
| URL | https://www.sei.org/projects-and-tools/projects/machine-learning-soil-carbon-storage-ghg-emissions/ |
| 来源智库 | Stockholm Environment Institute (Sweden) |
| 资源类型 | 智库项目 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/527367 |
| 推荐引用方式 GB/T 7714 | Matthew Fielding. Exploring the use of machine learning to detect environmental changes and management options affecting soil carbon storage and greenhouse gas emissions. 2021. |
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