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通过使用无人机的反射率和植被指数,评估树种类的土壤CO2排放

Fernando Saragosa Rossi¹, João Lucas Della-Silva², Larissa Pereira Ribeiro Teodoro³

¹PPG-Ciência do Solo, State University of São Paulo (UNESP), Jaboticabal, 15385-000, Brazil.

Scientific reports

|August 31, 2024

概括

白树森林中的土壤二氧化碳流与特定物种联系在一起,使用无人机多谱数据. 这有助于环境监测,通过区分欧树物种之间的二氧化碳排放.

科学领域:

环境科学环境科学
林业林业林业林业林业
遥感遥感遥感遥感

背景情况:

树种类对全球碳循环至关重要,影响温室气体的减少和大气中的二氧化碳储存.
评估森林中的土壤二氧化碳排放对于有效的环境监测和碳核算至关重要.

研究的目的:

为了研究土壤二氧化碳 (CO2) 流量 (FCO2) 和植被指数 (VIs) 之间的关系,这些指数来自于无人机基于树的多光谱图像.
为了确定光谱数据是否可以在不同树物种之间区分二氧化碳排放水平.

主要方法:

采集了多光谱图像 (绿色,红边,近红外) 使用无人机上的红杉传感器.
使用LI-COR 8100分析仪测量土壤二氧化碳流量 (FCO2),以及土壤湿度和温度数据.
计算了植被指数 (ATSAVI,GSAVI,SAVI) 并进行了多变量方差分析 (MANOVA).

主要成果:

根据土壤调整的植被指数 (ATSAVI,GSAVI,SAVI) 显示,对于Eucalyptus camaldulensis,Eucalyptus saligna和Eucalyptus urophylla,土壤二氧化碳流 (FCO2) 与土壤二氧化碳流有显著的负相关性.
在考虑树物种因素时,MANOVA证实了变量中的显著差异 (p < 0.01).
在土壤二氧化碳排放数据和特定的树物种之间发现了明显的相关性,允许进行统计差异化.

结论:

基于无人机的多谱数据和衍生的植被指数可以有效地监测树林中的土壤二氧化碳流量.
该研究成功地区分了欧树物种之间的二氧化碳排放水平,突出了特定物种环境评估的潜力.
这种方法为碳循环研究和有关温室气体排放的森林管理战略提供了有价值的数据.

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