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Position: Home > Articles > Winter Wheat Yield Forecasting Based on Vegetation Temperature Condition Index Transactions of the Chinese Society for Agricultural Machinery 2014,45 (2) 239-245

基于条件植被温度指数的冬小麦产量预测

作  者：
田苗;王鹏新;张树誉;刘峻明;景毅刚;李俐
单  位：
陕西省气象局;中国农业大学信息与电气工程学院
关键词：
冬小麦;产量预测;改进层次分析法;加权条件植被温度指数;季节性ARIMA模型
摘  要：
条件植被温度指数(VTCI)综合了地表主要参数——植被指数(NDVI)和地表温度(LST),能够较为准确地对干旱进行监测,可为抗旱救灾、遥感作物估产等提供科学依据。在改进层次分析法的加权VTCI与冬小麦产量的相关性研究成果和VTCI的季节性ARIMA模型干旱预测研究成果基础上,对关中平原的冬小麦产量进行向前1旬、2旬和3旬的预测研究。研究结果表明,产量预测结果与产量监测结果吻合较好,预测精度随着预测步长的增大而降低,关中平原4个地级市平均产量预测结果的最大相对误差为3.27%,说明用该方法可以进行向前3旬的产量预测。
译  名：
Winter Wheat Yield Forecasting Based on Vegetation Temperature Condition Index
作  者：
Tian Miao;Wang Pengxin;Zhang Shuyu;Liu Junming;Jing Yigang;Li Li;College of Information and Electrical Engineering,China Agricultural University;Shaanxi Provincial Meteorological Bureau;
关键词：
Winter wheat Yield forecast Improved analytical hierarchy process Weighted vegetation temperature condition index Seasonal ARIMA models
摘  要：
Vegetation temperature condition index( VTCI) takes the effects of NDVI and LST into account,and is applicable to drought monitoring in the Guanzhong Plain,Shaanxi,China. VTCI provides a scientific basis for drought relief and crop yield estimation in the plain. Based on the research of correlation of the weighted VTCI and winter wheat yield,and SARIMA drought forecasting results,the winter wheat yield forecasting models were developed at intervals of 1 ten-day,2 ten-day and 3 ten-day before the harvest. The results showed that the yield forecasting results and yield monitoring results had a good agreement. The forecasting accuracy was reduced with the increase of the forecasting interval and the maximum relative error of the yield forecasting results of the 3 ten-day was 3. 27%,which indicated that the developed models could be used to forecast winter wheat yield at 30 days before the harvest.

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