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基于加权马尔可夫模型的条件植被温度指数预测研究
引用本文:韩萍,王鹏新,王家慧,孙威,朱德海. 基于加权马尔可夫模型的条件植被温度指数预测研究[J]. 干旱地区农业研究, 2008, 26(6): 196-200
作者姓名:韩萍  王鹏新  王家慧  孙威  朱德海
作者单位:中国农业大学理学院,北京,100094;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,教育部科学技术研究重点项目 
摘    要:条件植被温度指数(VTCI)是一种近实时的干旱监测指标。利用加权马尔可夫模型对陕西关中平原的条件植被温度指数(VTCI)时空变化序列进行了2步预测,并将预测结果与实际监测结果进行对比分析,结果表明,预测的干旱监测结果与实际的干旱监测结果空间分布特征基本一致,进一步的误差分析显示,2步预测的误差平均值分别为0.042和0.152。

关 键 词:干旱预测  条件植被温度指数  加权马尔可夫模型

Drought forecasting based on the vegetation temperature condition index using weighted Markov model
HAN Ping,WANG Pengxin,WANG Jiahui,SUN Wei,ZHU Dehai. Drought forecasting based on the vegetation temperature condition index using weighted Markov model[J]. Agricultural Research in the Arid Areas, 2008, 26(6): 196-200
Authors:HAN Ping  WANG Pengxin  WANG Jiahui  SUN Wei  ZHU Dehai
Abstract:The spatial and time series of vegetation temperature condition index (VTCI) for Guanzhong Plain and Weibei Tablelands are analyzed using weighted Markov model.The VTCI images of 2 lead-time prediction are got.Comparing the monitoring images with the forecasting images,we can find the similar characters showing similar drought distribution between the monitoring image and the forecasting image.The further difference detection in difference images shows that the average difference of 1-step prediction is 0.042,and the average difference of 2-step prediction is 0.152.
Keywords:vegetation temperature condition index  weighted Markov model  drought forecasting
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