数字农科院2.0

Estimating the winter wheat harvest index with canopy hyperspectral remote sensing data based on the dynamic fraction of post-anthesis phase biomass accumulation

文献类型： 外文期刊

作者： Zhang, Ningdan;Liu, Xingren;Ren, Jianqiang;Wu, Shangrong;Li, Fangjie

作者机构：

关键词： Winter wheat;dynamic harvest index;remote sensing;normalized difference spectral index;sensitive band

期刊名称： INTERNATIONAL JOURNAL OF REMOTE SENSING

ISSN： 0143-1161

年卷期： 2022 年 43 卷 6 期

页码：

收录情况： SCIE（2022版） ; EI（2022版）

摘要： Remote sensing-based crop harvest index (HI) information is of great significance for crop yield estimation, crop variety breeding and evaluation of crop cultivation effectiveness. The method for estimating HI using f ( G ) (fraction of post-anthesis phase biomass accumulation) has been widely used and shows good performance at the field scale, but the upscaled regional application of this method had not been achieved using remote sensing information. In this paper, a remote sensing method for estimating the dynamic harvest index (D-HI) based on the remote sensing-based dynamic f ( G ) (D-f ( G )) was proposed to solve this problem and was verified based on D-f ( G ) and D-HI measurements. This approach was based on accurate D-f ( G ) parameters estimated by using the NDSI constructed from hyperspectral sensitive band centres. The results showed that the D-f ( G ) estimation, the overall verification accuracy of the D-HI estimation at different growth stages and the accuracy of the D-HI estimation in a single growth stage were highly accurate. In the overall D-HI estimation verification, the normalized root square mean error (NRMSE) was between 10.83% and 14.45%, and the mean relative error (MRE) was between 9.62% and 13.99%. At maturity, the D-HI estimation accuracy based on band centre lambda (732 nm, 834 nm) was the highest, and the NRMSE and MRE were 9.62% and 9.27%, respectively. Based on these results, the proposed method is feasible and effective at accurately estimating the D-HI, thus providing a technical reference for the use of satellite remote sensing data to obtain regional crop HI information based on f ( G ).

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