Site-specific soil properties prediction using hyperspectral signatures of topsoil coverage and underground image by real-time soil spectrophotometer

S.K. Roy; S. Shibusawa; T. Okayama

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Site-specific soil properties prediction using hyperspectral signatures of topsoil coverage and underground image by real-time soil spectrophotometer

In: Precision Agriculture â05

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S.K. Roy

S.K. Roy
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S. Shibusawa

S. Shibusawa shibu@cc.tuat.ac.jp

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T. Okayama

T. Okayama
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Type:: Chapter

Pages:: 529â536

DOI:: https://doi.org/10.3920/978-90-8686-549-9_066

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This paper describes the variation of soil moisture and organic matter using underground image textural indices and hyperspectral signatures. The image textural indices were extracted from video image data by a real-time soil spectrophotometer and hyperspectral signatures were recorded on a portable field spectrophotometer and an AISA airborne sensor for one field cropped with wheat. A neural network was used to explain the variation of soil properties. The neural network consistently outperformed stepwise multiple linear regression and provided minimal prediction errors for spatially varying soil properties. The result showed that the combination of field spectral signatures and underground image texture could predict soil properties more accurately than a single index.

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Precision Agriculture â05

E-Book ISBN:: 9789086865499

Publisher:: Wageningen Academic

Print Publication Date:: 24 Oct 2005

Subjects
- Life Sciences
  - General
  - Agriculture & Environment

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Site-specific soil properties prediction using hyperspectral signatures of topsoil coverage and underground image by real-time soil spectrophotometer

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Precision Agriculture â05

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