The application of satellite remote sensing and machine learning for modelling impacts of regenerative farming practices

卫星遥感和机器学习在再生农业实践影响建模中的应用

• 批准号: 2842273
• 金额: --
• 依托单位: University of Leicester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2842273
• 关键词: application; satellite; remote; sensing; machine

Background Earth observations from satellite remote sensing, data analytics and machine learning are rapidly evolving fields of research. They offer the potential to unlock scaling challenges to enable tracking of the impact of regenerative farming practices in terms of reducing greenhouse gas emissions and improving soil health. Understanding the impact of these practices requires measurements of factors including, but not limited to, soil organic matter (SOM), soil organic carbon (SOC), soil hydraulic properties and soil compaction.

来自卫星遥感的地球观测、数据分析和机器学习是快速发展的研究领域。它们提供了解决规模挑战的潜力，使跟踪再生农业实践在减少温室气体排放和改善土壤健康方面的影响成为可能。了解这些做法的影响需要测量因素，包括但不限于土壤有机质（SOM）、土壤有机碳（SOC）、土壤水力特性和土壤压实度。