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Remote Sens. 2017, 9(12), 1212; doi:10.3390/rs9121212

Moisture Content Measurement of Broadleaf Litters Using Near-Infrared Spectroscopy Technique

1
Department of Biosystems and Biomaterials Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea
2
Research Institute of Agriculture and Life Sciences, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea
3
Department of Forest Sciences, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea
*
Author to whom correspondence should be addressed.
Received: 18 October 2017 / Revised: 14 November 2017 / Accepted: 20 November 2017 / Published: 24 November 2017
(This article belongs to the Section Forest Remote Sensing)
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Abstract

Near-infrared spectroscopy (NIRS) was implemented to monitor the moisture content of broadleaf litters. Partial least-squares regression (PLSR) models, incorporating optimal wavelength selection techniques, have been proposed to better predict the litter moisture of forest floor. Three broadleaf litters were used to sample the reflection spectra corresponding the different degrees of litter moisture. The maximum normalization preprocessing technique was successfully applied to remove unwanted noise from the reflectance spectra of litters. Four variable selection methods were also employed to extract the optimal subset of measured spectra for establishing the best prediction model. The results showed that the PLSR model with the peak of beta coefficients method was the best predictor among all of the candidate models. The proposed NIRS procedure is thought to be a suitable technique for on-the-spot evaluation of litter moisture. View Full-Text
Keywords: near-infrared spectroscopy; multivariate analysis; partial least-squares regression; floor litter; optimal wavelength selection near-infrared spectroscopy; multivariate analysis; partial least-squares regression; floor litter; optimal wavelength selection
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Kim, G.; Hong, S.-J.; Lee, A.-Y.; Lee, Y.-E.; Im, S. Moisture Content Measurement of Broadleaf Litters Using Near-Infrared Spectroscopy Technique. Remote Sens. 2017, 9, 1212.

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