| 利用有效积温提高冬小麦估产精度的研究 |
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| 引用本文： | 陈艳玲,顾晓鹤,董燕生,胡圣武,张秋阳,赵 静.利用有效积温提高冬小麦估产精度的研究[J].麦类作物学报,2014,34(8):1130-1135. |
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| 作者姓名： | 陈艳玲 顾晓鹤 董燕生 胡圣武 张秋阳 赵 静 |
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| 作者单位： | （1.河南理工大学，河南焦作 454000； 2.国家农业信息化工程技术研究中心，北京 100097； 3.农业部农业信息技术重点实验室，北京 100097； 4.东北农业大学，黑龙江哈尔滨 150030； 5.辽宁工程技术大学，辽宁阜新 123000） |
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| 基金项目： | 国家公益性行业（农业）科研专项（201303109）;国家高分辨率对地观测重大专项（民用部分）（03 Y30B06 9001 13/15） |
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| 摘 要： | 为探索如何利用冬小麦生长过程中的积温信息来提高遥感估产的准确性,以2009-2010和2012-2013年2个冬小麦生长季的田间试验数据为基础,利用有效积温和植被指数(NDVI)构建冬小麦当季估产指数INSEY(In-season estimate of yield)和INSEY-CGDD(In-season estimate of yield-cumulative growing degree days),分别用NDVI、INSEY和INSEY-CGDD与实测产量建立估产模型,并比较分析3类估产模型的精度。结果表明,3个变量与实测产量均成指数关系,其中INSEY-CGDD模型的精度最高(R2=0.59),预测能力最优,其次是INSEY模型(R2=0.55);而NDVI模型的精度最低(R2=0.35),预测能力最差。因此,在冬小麦估产模型中引入有效积温调整参数,可有效提高遥感估产模型精度。
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| 关 键 词： | 冬小麦 有效积温 NDVI 当季估产指数 精度 |
Prediction of Winter Wheat Yield Based on Remote Sensing with Accumulated Temperature |
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| CHEN Yanling,GU Xiaohe,DONG Yansheng,HU Shengwu,ZHANG Qiuyang,ZHAO Jing.Prediction of Winter Wheat Yield Based on Remote Sensing with Accumulated Temperature[J].Journal of Triticeae Crops,2014,34(8):1130-1135. |
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| Authors: | CHEN Yanling GU Xiaohe DONG Yansheng HU Shengwu ZHANG Qiuyang ZHAO Jing |
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| Abstract: | Accumulated temperature is an important factor affecting crop growth and yield. This study aims to explore the use of accumulated temperature information to improve the accuracy of yield prediction. The field experiment data was collected in two winter wheat growing seasons during 2009-2010 and 2012-2013. The days of Growing Degree Days(GDD) that greater than zero and Cumulative Growing Degree Days(CGDD) and the NDVI were obtained and calculated by the measured ground spectral data and meteorological data. IN Season Estimate of Yield (INSEY) and IN Season Estimate of Yield Cumulative Growing Degree Days (INSEY CGDD) were introduced by GDD and CGDD divided by NDVI, respectively. Finally, NDVI, INSEY and INSEY CGDD were utilized to build the estimation model with measured yield, respectively, and then the accuracy of the three types of yield estimation models were compared with each other. The result showed that all three kinds of variables and the measured yield appeared exponential relationship. The accuracy of INSEY CGDD model was the highest (R=0.59). In other words, its ability of prediction was the optimal. The followed was the INSEY model (R=0.55). However, the lowest accuracy was NDVI (R=0.35). The studies showed that the accuracy of yield estimation model with remote sensing was improved effectively by the introduction of the effective temperature in winter wheat yield estimation model as an adjustment parameter. Simultaneously, a new strategy for a wide range of crop yield estimation was putted forward as well. |
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| Keywords: | Winter wheat NDVI Accumulated temperature IN-Season estimate of yield Accuracy |
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