摘要
土壤CO_2浓度时间序列的数据质量易受到外界环境及土壤监测仪质量的影响,导致不能精确的测定土壤呼吸。针对土壤CO_2浓度时间序列的数据质量问题,本文提出小波包变换和Fick第二定律结合的方法对时间序列进行去噪分析。实验结果显示,无论从均值,信噪比,均方根误差和斜率距离来看,本文算法都优于由传统方法计算得到的结果。同时,在研究区域分别测量了早中晚三个时间段的土壤CO_2浓度,对其进行去噪处理之后,利用Fick第一定律计算获得的土壤碳通量与LI-8100测得的仅相距1μmol/m^2/s左右。说明通过本文算法不仅精确算得了开放型气室内任意时间任意位置的CO_2浓度时间序列,并且通过计算处理后的时间序列获得了与LI-8100相近的土壤碳通量。
The data quality of soil CO2 concentration time series is easily affected by the external environment and the quality of the soil monitor,which makes it impossible to accurately determine soil respiration. Aiming at the data quality problem of soil CO2 concentration time series,this paper proposes a method combining wavelet packet transform and Fick second law to denoise time series. The experimental results show that the algorithm is superior to the traditional method for calculating the mean,signal-to-noise ratio,root mean square error and slope distance.At the same time,the soil CO2 concentration in the early,middle and late periods was measured in the study area. After denoising,the soil carbon flux calculated by the first law of Fick was only about1μmol/m2/s distance from the measured by LI-8100.The algorithm not only accurately calculates the CO2 concentration time series at any position in the open gas chamber at any time,but also obtains the soil carbon flux similar to LI-8100 by calculating the time series after processing.
作者
谢宝良
胡军国
李烨斐
陈芳
毛国平
XIE Baoliang;HU Junguo;LI Yefei;CHEN Fang;MAO Guoping(College of information engineering,Key Laboratory of State Forestry and Grassland Administration on Forestry Sensing Technologyand Intelligent Equipment,Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province,Zhejiang A&F University,Hangzhou311300,China)
出处
《传感技术学报》
CAS
CSCD
北大核心
2019年第5期715-722,共8页
Chinese Journal of Sensors and Actuators
基金
国家自然基金项目(31570629)
浙江省公益技术研究工业项目(2015C31004)
