Optimising configuration of a hyperspectral imager for on-line field measurement of wheat canopy

Date

2016-12-30

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier

Department

Type

Article

ISSN

1537-5110

Format

Free to read from

Citation

Whetton RL, Waine TW, Mouazen AM, Optimising configuration of a hyperspectral imager for on-line field measurement of wheat canopy, Biosystems Engineering, Volume 155, March 2017, Pages 84–95

Abstract

There is a lack of information on optimal measurement configuration of hyperspectral imagers for on-line measurement of a wheat canopy. This paper aims at identifying this configuration using a passive sensor (400–750 nm). The individual and interaction effects of camera height and angle, sensor integration time and light source distance and height on the spectra's signal-to-noise ratio (SNR) were evaluated under laboratory scanning conditions, from which an optimal configuration was defined and tested under on-line field measurement conditions. The influences of soil total nitrogen (TN) and moisture content (MC) measured with an on-line visible and near infrared (vis-NIR) spectroscopy sensor on SNR were also studied. Analysis of variance and principal component analysis (PCA) were applied to understand the effects of the laboratory considered factors and to identify the most influencing components on SNR.

Results showed that integration time and camera height and angle are highly influential factors affecting SNR. Among integration times of 10, 20 and 50 ms, the highest SNR was obtained with 1.2 m, 1.2 m and 10° values of light height, light distance and camera angle, respectively. The optimum integration time for on-line field measurement was 50 ms, obtained at an optimal camera height of 0.3 m. On-line measured soil TN and MC were found to have significant effects on the SNR with Kappa values of 0.56 and 0.75, respectively. In conclusion, an optimal configuration for a tractor mounted hyperspectral imager was established for the best quality of on-line spectra collected for wheat canopy.

Description

Software Description

Software Language

Github

Keywords

Hyperspectral imager, Signal-to-noise ratio, Wheat canopy, Hyperspectral imager; Signal-to-noise ratio; Wheat canopy; Principal component analysis, Soil properties

DOI

Rights

Attribution-NonCommercial 4.0 International

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