文献类型： 外文期刊
作者： Gu, Xiaohe 1 ; Shu, Meiyan 1 ; Yang, Guijun 1 ; Song, Xiaoyu 1 ; Xu, Xingang 1 ;
作者机构： 1.Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
关键词： spatial variance; winter wheat; growth; CHRIS; LAI
期刊名称：2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019)
ISSN： 2153-6996
年卷期： 2019 年
页码：
收录情况： SCI
摘要： Monitoring spatial variance of crop growth is very important for precise fertilization and water management to reduce the difference of grain quality. The study obtained the CHRIS hyperspectral image in the jointing stage of winter wheat. Then the Beer-Lambert law was used to develop the inversion model of leaf area index (LAI) of winter wheat in the study area. Taken the winter wheat parcels as primary units, the CVs of LAI in each parcel were used to evaluate the spatial variance of winter wheat growth at parcel scale. Results showed that the parameters of LAI among all winter wheat parcels were obviously variable. The CVs of LAI fluctuated from 10% to 40%. There were 13 parcels of mid-variance, while 191 parcels of lower-variance. These indicated that the winter wheat growth in the study area was relatively homogeneous. The spatial resolution and spectral resolution of CHRIS image were suitable for evaluating the spatial variance of crop growth in parcel scale.
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