吉林大学学报(地球科学版) ›› 2019, Vol. 49 ›› Issue (6): 1805-1814.doi: 10.13278/j.cnki.jjuese.20180346
• 地球探测与信息技术 • 上一篇
黄盖先, 田波, 周云轩, 袁庆
Huang Gaixian, Tian Bo, Zhou Yunxuan, Yuan Qing
摘要： 连续在线滨海湿地生态物联网观测系统，因传感器技术局限及环境干扰会产生异常观测数据，影响数据使用，有效的数据预处理极为重要。以上海崇明东滩国际重要湿地生态观测数据为研究对象，将异常数据分为数值异常、波动异常与异常事件3种类型，基于回归残差概率分布异常检测算法，使用查找表和多指标时间序列模型，综合多环境要素相互关系，构建针对滨海湿地生态观测的数据预处理方法。相比传统方法，该方法在保证异常数据检测精度的同时，更好地区分了异常事件与传感器异常，减少误判。通过分析9个指标5万余条数据，以10-8~10-20的阈值分别检测出0.18%~8.12%的数值异常和波动异常，以及2次异常事件。分析数据预处理结果，传感器的观测原理、观测季节等因素会影响传感器的稳定性，人类活动是造成观测区异常事件发生的主要因素。
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