Monitoring and Forecasting Winter Wheat Freeze Injury and Yield from Multi-Temporal Remotely Sensed Data

文献类型： 外文期刊

第一作者： Wang, Huifang

作者： Wang, Huifang;Huo, Zhiguo;Zhou, Guangsheng;Wu, Li;Wang, Huifang;Feng, Haikuan

作者机构：

关键词： Winter wheat;freeze injury levels;change detection;yield assessment

期刊名称：INTELLIGENT AUTOMATION AND SOFT COMPUTING （ 影响因子：1.647； 五年影响因子：1.469 ）

ISSN： 1079-8587

年卷期： 2016 年 22 卷 2 期

页码：

收录情况： SCI

摘要： Remote-sensing techniques provide crop growth information economically, rapidly, and objectively on a large scale. Remote sensing has been widely used to monitor crop growth and forecast yield. In this study, three Huanjing satellite ( HJ) charge-coupled device ( CCD) images of winter wheat at growth-wintering ( December 2, 2009; pre-freeze injury), regreening ( April 2, 2010; post-freeze injury), and jointing stages ( April 23, 2010) were acquired for the Gaocheng area in Hebei Province. According to the change characteristics of the normalized difference vegetation index ( NDVI) of field samplings of post-freeze injury, we built a multi-line-progress model between the NDVI difference (Delta NDVI) and field samplings, which correspond with field investigation data. The damage levels ( uninjured, mild, moderate, and serious) and the growth levels ( better, good, bad, and worse) were also specified in the model. As a result, the coefficient of determination ( R-2) of this model reached 0.6001; 20 sampling points were used to validate the model and R-2 reached 0.5255. This study demonstrates the feasibility of using early growth stage model to predict yield and provides a tentative prediction of the yield in the Hebei area using HJ-CCD images of China.

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