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Automatic estimation of soil biochar quantity via hyperspectral imaging

chapter
posted on 2020-05-21, 00:00 authored by L Tong, J Zhou, Shahla Hosseini BaiShahla Hosseini Bai, Chengyuan XuChengyuan Xu, Y Qian, Y Gao, Z Xu
Biochar soil amendment is globally recognized as an emerging approach to mitigate CO2 emissions and increase crop yield. Because the durability and changes of biochar may affect its long term functions, it is important to quantify biochar in soil after application. In this chapter, an automatic soil biochar estimation method is proposed by analysis of hyperspectral images captured by cameras that cover both visible and infrared light wavelengths. The soil image is considered as a mixture of soil and biochar signals, and then hyperspectral unmixing methods are applied to estimate the biochar proportion at each pixel. The final percentage of biochar can be calculated by taking the mean of the proportion of hyperspectral pixels. Three different models of unmixing are described in this chapter. Their experimental results are evaluated by polynomial regression and root mean square errors against the ground truth data collected in the environmental labs. The results show that hyperspectral unmixing is a promising method to measure the percentage of biochar in the soil. © 2019 by IGI Global.

Funding

Other

History

Editor

Information Resources Management Association USA

Volume

3

Start Page

1608

End Page

1635

Number of Pages

28

ISBN-10

1522570330

ISBN-13

9781522570332

Publisher

IGI-Global

Place of Publication

Hershey, PA

Open Access

  • No

External Author Affiliations

Griffith University; Zhejiang University, China

Era Eligible

  • Yes