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Effects of Waterlogging and Shading at Jointing and Grain-Filling Stages on Yield Components of Winter Wheat Read chapter Read first chapter

2016 | OriginalPaper | Chapter

The Study of Winter Wheat Biomass Estimation Model Based on Hyperspectral Remote Sensing

Authors : Xiaowei Teng, Yansheng Dong, Lumin Meng

Published in: Computer and Computing Technologies in Agriculture IX

Publisher: Springer International Publishing

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Abstract

Biomass plays an important role in crop growth and yield formation. The study of biomass has been expanded to remote sensing sphere, which provides more ways to the obtainment of crop biomass. To carry out the study of winter wheat biomass estimation model, the field experiments were conducted at Rougu test area and Wugong test area, Shanxi Province in the cropping season 2013–2014. The biomass estimation model was based on the Time-Integrated Value of NDVI (TINDVI) and Leaf Water Content Index (LWCI), which was used to predict the winter wheat biomass. And the model was validated with the ground measured biomass. The results showed that the determination coefficient (R2) and root mean square error (RMSE) between the measured and the estimated biomass were 0.7949 and 2.689 t/ha, respectively. The estimated biomass was exactly similar to the field measured biomass, therefore this model had a good application prospect.

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Metadata
Title
The Study of Winter Wheat Biomass Estimation Model Based on Hyperspectral Remote Sensing
Authors
Xiaowei Teng
Yansheng Dong
Lumin Meng
Copyright Year
2016
Book
Computer and Computing Technologies in Agriculture IX

Print ISBN: 978-3-319-48353-5

Electronic ISBN: 978-3-319-48354-2

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-48354-2_17

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