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农田土壤的时空空间监测有机碳从太空变化

Tom Broeg^1,2, Axel Don³, Martin Wiesmeier⁴

¹Thünen Earth Observation (ThEO), Thünen Institute of Farm Economics, Braunschweig, Germany.

Global change biology

|December 9, 2024

概括

这项研究使用卫星数据和长期土壤样本建模了土壤有机碳 (SOC) 趋势. 虽然预测SOC是准确的,但验证SOC趋势需要仔细考虑时间不确定性和足够的数据持续时间.

科学领域:

环境科学环境科学
土壤科学土壤科学
遥感遥感遥感遥感

背景情况:

准确的土壤有机碳 (SOC) 监测对于了解土壤健康和气候变化至关重要.
使用地球观测 (EO) 数据的时空SOC模型提供了大规模的监测潜力,但需要强大的时间验证.
长期土壤采样数据对于验证随时间推移推导的SOC趋势的准确性至关重要.

研究的目的:

通过使用卫星数据和长期土壤样本,对近四十年的农田SOC趋势进行高分辨率建模.
进行时间模型不确定性和精度的深入验证,以获得SOC趋势.
评估土壤特性和管理实践对SOC趋势预测准确性的影响.

主要方法:

利用从1986年到2022年重复 SOC 样本和时间序列多光谱卫星数据 (Landsat,Sentinel-2).
开发了时空SOC模型,并使用100个长期监测站点的网络与5年重新采样间隔进行验证.
分析了模型不确定性,预测准确性以及SOC内容和耕作实践对趋势检测的影响.

主要成果:

一般SOC预测的准确性很高 (R2=0.61),但趋势验证显示了更大的不确定性 (R2=0.16).
尽管存在不确定性,但95%的地点在SOC下降,增加或稳定趋势方面被正确分类.
在SOC含量较高的土壤和耕作减少的土地上,趋势预测的准确性得到改善.

结论:

基于EO的SOC趋势图显示了大规模土壤碳监测的巨大潜力.
通过重复的土壤样本和长期测量进行直接验证对于可靠的SOC趋势评估至关重要.
检测SOC趋势所需的时间框架取决于绝对SOC变化的大小.

关键词:

裸露的土壤裸露的土壤碳封存是一种碳封存方式.变化检测检测的变化检测气候变化气候变化气候变化地球观测地球观测远程传感是一种遥感技术.土壤反射率复合材料的复合材料空间时间模型.

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