基于条件植被温度指数的干旱预测研究

基于遥感定量化干旱监测结果,进行了干旱预测的研究。将遥感获得的条件植被温度指数VTCI序列应用于陕西关中平原地区,并利用ARIMA模型对该地区的VTCI时间序列进行分析建模预测。提出由点到面的时空序列预测方法,先对该区域的36个气象站所在像素点建立适合的ARIMA模型,再对整个区域所有像素点的VTCI时间序列进行建模预测。进行1步和2步预测,显示预测结果较好,1步预测精度好于2步预测;对历史数据进行AR(1)模型的拟合,拟合误差大部分较小。结果显示AR(1)模型适合VTCI序列。

Drought Forecasting with Vegetation Temperature Condition Index

The drought forecasting models is developed using the time series of the quantitative drought monitoring results of vegetation temperature condition index(VTCI) in the Guanzhong Plain of Northwest China.The autoregressive integrated moving average(ARIMA) is used to simulate the VTCI series of each pixel and forecast their changes in the future.A new way of modeling the spatio-temporal series is presented by extending of the forecasting models of some pixels to the whole area.The AR(1) models are suitable for all VTCI series of the 36 pixels.Therefore,the AR(1) models are applied to each pixel of the whole area,and the forecast is done with 1-2 lead-times.Comparing the monitoring and forecasting results,the forecasting accuracies of the AR(1) models are better,and the accuracies of the 1 lead-time are less than those of the 2 lead-times.The VTCI series of pixels in the whole study area are fitted by the selected best models.Comparing the fitting data with the historical data,the results show that VTCI series are better fitted by AR(1) models.Most of the simulating errors are small.All these results demonstrate that AR(1) models are suitable for drought forecasting using the VTCI series.