基于多生育期MODIS-NDVI的区域冬小麦遥感估产研究

发布时间：2018-09-19 09:51

【摘要】：以河南省开封市为研究区,采用2005—2013年种植区域冬小麦生育期内16 d合成的250 m空间分辨率的归一化植被指数(NDVI)之和,与冬小麦产量数据进行相关分析,筛选得到最佳遥感估产时相,建立单变量回归模型;同时,基于冬小麦生长的各个关键时期NDVI构建多元回归模型,再通过主成分分析方法对多元回归模型参数进行改进,得到新的估产模型;最后使用开封市2014年的产量数据对估产模型进行验证,旨在构建具有较高精度的估产模型,从而更好地指导小麦生产。结果显示,3种估产模型的估产误差均控制在10.55%内,根据3个模型得到研究区内冬小麦最佳产量预测时段为3月下旬,即拔节期;3个模型中,主成分回归估产模型的产量拟合精度最高,达93.12%,具有一定的实用价值。
[Abstract]:Taking Kaifeng City, Henan Province as the research area, the sum of normalized vegetation index (NDVI) of 250m spatial resolution during the growing period of winter wheat from 2005 to 2013 was used to analyze the correlation between the normalized vegetation index (NDVI) and winter wheat yield data. At the same time, the multivariate regression model was constructed based on NDVI in every key period of winter wheat growth, and the parameters of multivariate regression model were improved by principal component analysis. A new yield estimation model was obtained. Finally, the yield estimation model was validated by using the yield data of Kaifeng city in 2014, in order to construct a yield estimation model with high accuracy, and then to guide wheat production better. The results showed that the estimation error of the three models was controlled within 10.55%. According to the three models, the best prediction period of winter wheat yield in the study area was in late March, that is, jointing stage. The yield fitting accuracy of principal component regression model is the highest, 93.12, which has certain practical value.
【作者单位】：河南省农业科学院农业经济与信息研究所;郑州澍青医学高等专科学校;河南省农业遥感监测中心;
【基金】：河南省科技攻关重点项目(172102110090) 河南省农业科学院自主创新项目(2017ZC60)
【分类号】：S127;S512.11

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