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将数据可靠性作为有序变量进行分级,在理论上使数据可靠性与主要生态过程、次级生态过程、外部过程等数据源建立关联,构建了一种生态监测数据质量评估方法,提供了一个新的数据质量指数.它通过观察记录的合格率来估计数据集的质量,其检测结果包括了每一条数据的可靠性级别、标记为离群或错误数据的原因,以及完整数据集的质量指数值.将该方法应用于CERN的两个乔木生长数据集,发现该数据质量指数可以定量评估乔木生长数据集的质量.该方法为相关软件的开发提供了基础.
The reliability of data is classified as orderly variables, and in theory, data reliability is correlated with data sources such as major ecological processes, secondary ecological processes and external processes, and a method for evaluating the quality of ecological monitoring data is constructed, providing a The new data quality index, which estimates the quality of a data set by observing the pass rate of the record, includes the reliability level for each piece of data, the reason for the marked as outlier or incorrect data, and the quality index of the complete data set The method was applied to two CERN tree growth data sets and found that the data quality index can quantitatively assess the quality of the tree growth data set.This method provides the basis for the development of related software.