Moisture Content Measurement of Broadleaf Litters Using Near-Infrared Spectroscopy Technique
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 lit...
| Main Authors: | , , , , |
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| Format: | Article |
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MDPI AG
2017-11-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/9/12/1212 |
| _version_ | 1819294388987101184 |
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| author | Ghiseok Kim Suk-Ju Hong Ah-Yeong Lee Ye-Eun Lee Sangjun Im |
| author_facet | Ghiseok Kim Suk-Ju Hong Ah-Yeong Lee Ye-Eun Lee Sangjun Im |
| author_sort | Ghiseok Kim |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-24T04:25:32Z |
| format | Article |
| id | doaj.art-8fe49c778aa84cf7a32c562f2b3e3297 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-24T04:25:32Z |
| publishDate | 2017-11-01 |
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| series | Remote Sensing |
| spelling | doaj.art-8fe49c778aa84cf7a32c562f2b3e32972022-12-21T17:15:39ZengMDPI AGRemote Sensing2072-42922017-11-01912121210.3390/rs9121212rs9121212Moisture Content Measurement of Broadleaf Litters Using Near-Infrared Spectroscopy TechniqueGhiseok Kim0Suk-Ju Hong1Ah-Yeong Lee2Ye-Eun Lee3Sangjun Im4Department of Biosystems and Biomaterials Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, KoreaDepartment of Biosystems and Biomaterials Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, KoreaDepartment of Biosystems and Biomaterials Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, KoreaDepartment of Forest Sciences, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, KoreaResearch Institute of Agriculture and Life Sciences, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, KoreaNear-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.https://www.mdpi.com/2072-4292/9/12/1212near-infrared spectroscopymultivariate analysispartial least-squares regressionfloor litteroptimal wavelength selection |
| spellingShingle | Ghiseok Kim Suk-Ju Hong Ah-Yeong Lee Ye-Eun Lee Sangjun Im Moisture Content Measurement of Broadleaf Litters Using Near-Infrared Spectroscopy Technique Remote Sensing near-infrared spectroscopy multivariate analysis partial least-squares regression floor litter optimal wavelength selection |
| title | Moisture Content Measurement of Broadleaf Litters Using Near-Infrared Spectroscopy Technique |
| title_full | Moisture Content Measurement of Broadleaf Litters Using Near-Infrared Spectroscopy Technique |
| title_fullStr | Moisture Content Measurement of Broadleaf Litters Using Near-Infrared Spectroscopy Technique |
| title_full_unstemmed | Moisture Content Measurement of Broadleaf Litters Using Near-Infrared Spectroscopy Technique |
| title_short | Moisture Content Measurement of Broadleaf Litters Using Near-Infrared Spectroscopy Technique |
| title_sort | moisture content measurement of broadleaf litters using near infrared spectroscopy technique |
| topic | near-infrared spectroscopy multivariate analysis partial least-squares regression floor litter optimal wavelength selection |
| url | https://www.mdpi.com/2072-4292/9/12/1212 |
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