The Improvement of Region Substitution Method for Thermal Discharge Monitoring by Remote Sensing Based on Time-Space Series Analysis
The Improvement of Region Substitution Method for Thermal Discharge Monitoring by Remote Sensing Based on Time-Space Series Analysis
复制标题
基于时空序列分析的遥感热放电监测区域替代方法的改进
DOI：
10.1007/s12524-015-0479-8
复制
发表时间：
2016-04
影响因子：
2.5
通讯作者：
Zhang, YongHong
中科院分区：
文献类型：
--
作者：
Yu, Tao;Li, JiaGuo;Yang, HongYan;Zhang, YongHong
为提高核电站热排放监测精度，以红沿河核电站为研究对象，利用多年HJ-1B/IRS数据对传统的区域替代法进行改进。通过图像网格化建立最佳相似性度量，提取以平均温度为参考温度的最佳非放电网格。为了评价新方法的性能，将新方法与另外两种现有方法--取水量法和平均间隔法的结果进行了比较和评价。新方法的参考温度和背景温度之间的D值范围为-1至1 °C。新方法的绝对D值的平均值和标准偏差范围为0.1至0.3 °C。结果表明，新方法不仅取得了更好的精度，而且克服了两种方法的缺点。该方法具有良好的推广应用前景。
In order to improve the monitoring accuracy of nuclear power plant thermal discharge, this study takes HongYanHe nuclear power plant as the object to improve the traditional region substitution method with years of HJ-1B/IRS data. After establishment of the optimum similarity measurement by image meshing, the optimum non-discharge grids whose average temperature was taken as the reference temperature were extracted. To evaluate the performance of the new method, results of the new method and other two existing method---water intake method and average bay method were compared and assessed. D-value between reference temperature and background temperature of the new method ranges from −1 to 1 °C. The mean and standard deviation of the absolute D-value of the new method ranges from 0.1 to 0.3 °C. Results suggest that the new method not only achieved better accuracy, but also over comes weakness of the two compared method. It is promising that the new improved method can be extended and applied further in thermal discharge monitoring.
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DOI：
10.1016/j.eswa.2005.06.009
发表时间：
2005-11
期刊：
Expert Syst. Appl.
影响因子：
--
作者：
C. Romero;Jiefeng Shan
通讯作者：
C. Romero;Jiefeng Shan
影响因子：
3.3
作者：
Ahn, YH;Shanmugam, P;Kang, YQ
通讯作者：
Kang, YQ
影响因子：
5.8
作者：
S. Suh
通讯作者：
S. Suh
DOI：
10.1016/s1364-8152(01)00065-2
发表时间：
2002
期刊：
Environ. Model. Softw.
影响因子：
--
作者：
S.P Schreiner;T.A Krebs;D.E Strebel;A. Brindley
通讯作者：
S.P Schreiner;T.A Krebs;D.E Strebel;A. Brindley
影响因子：
3.4
作者：
C. Wu;Q. Wang;Z. Yang;W. Wang
通讯作者：
C. Wu;Q. Wang;Z. Yang;W. Wang