基于加权马尔可夫模型的条件植被温度指数预测研究

Drought forecasting based on the vegetation temperature condition index using weighted Markov model

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。

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.