首页 | 本学科首页   官方微博 | 高级检索  
     检索      

Kappa系数的修正及在干旱预测精度及一致性评价中的应用
引用本文:田 苗,王鹏新,严泰来,刘春红.Kappa系数的修正及在干旱预测精度及一致性评价中的应用[J].农业工程学报,2012,28(24):1-7.
作者姓名:田 苗  王鹏新  严泰来  刘春红
作者单位:中国农业大学信息与电气工程学院,北京 100083
基金项目:国家自然科学基金项目(41071235、40871159)、国家科技支撑计划课题(2012BAH29B03)资助和中国农业大学研究生科研创新专项(KYCX2011076)
摘    要:大面积遥感面上干旱预测结果无法应用点上预测精度评价方法对每个像素进行评价,因此该研究引用Kappa系数对一阶自回归模型和季节性求和自回归移动平均模型的关中平原干旱预测结果进行精度和一致性评价。通过将面上VTCI干旱监测结果和预测结果划分为干旱与不旱两种类型,建立转换矩阵,得到了Kappa系数。由于Kappa系数存在两个明显的反论,因此在计算Kappa系数的同时计算了阳性一致率、阴性一致率、PI指数、BI指数、Kappa系数的最大、最小值和PABAK等系列指标,对Kappa系数的反论进行了检验与修正。文章通过对2种预测模型2009年4月上旬、中旬和下旬的干旱预测结果进行评价和对比,得到一阶自回归模型的总体精度优于季节性求和自回归移动平均模型,而季节性求和自回归移动平均模型预测旱情发生的一致性高于一阶自回归模型;得出Kappa系数或修正后的Kappa系数结合阳性一致率可用于干旱预测精度评价的结论。

关 键 词:遥感  干旱  预测  Kappa系数  精度评价  一致性评价  反论
收稿时间:2012/3/12 0:00:00
修稿时间:2012/11/26 0:00:00

Adjustment of Kappa coefficient and its application in precision and agreement evaluation of drought forecasting models
Tian Miao,Wang Pengxin,Yan Tailai and Liu Chunhong.Adjustment of Kappa coefficient and its application in precision and agreement evaluation of drought forecasting models[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(24):1-7.
Authors:Tian Miao  Wang Pengxin  Yan Tailai and Liu Chunhong
Institution:(College of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China)
Abstract:Traditional methods for evaluating drought forecasting accuracies cannot be used to evaluate drought forecast results of large areas based on satellite remote sensing data. This paper is mainly on the accuracy evaluation and agreement analysis of the drought forecasting results of the autoregressive models (AR) and the seasonal integrated autoregressive moving average models (SARIMA) using the Kappa coefficient. The drought forecasting results and the drought monitoring results of VTCI were categories into two classes that are drought and normal, and were used to build the transformation matrices to calculate the Kappa coefficients. Two apparent paradoxes have been identified for the Kappa statistic, and some related indices, positive consistency, negative consistency, and prevalence index, bias index, maximum and minimum values of Kappa and PABAK coefficients were calculated and analyzed for verifying the paradoxes and modifying the Kappa coefficients. Drought forecasting results in first, middle and last ten days of April, 2009 in the Guanzhong Plain of China were selected for the evaluation. The results show that the overall accuracy of the AR(1) models are better than the SARIMA models, while the ability of forecasting drought situation of the SARIMA models is better than that of the AR(1) models. The Kappa or adjusted Kappa coefficients combined with the positive consistency can be used to evaluate the drought forecasting accuracy.
Keywords:remote sensing  drought  forecasting  Kappa coefficient  precision evaluation  agreement evaluation  paradox
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《农业工程学报》浏览原始摘要信息
点击此处可从《农业工程学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号