scholarly journals Determination of in-situ salinized soil moisture content from visible-near infrared (VIS–NIR) spectroscopy by fractional order derivative and spectral variable selection algorithms

2018 ◽  
Vol 1 (1) ◽  
pp. 21-34
Author(s):  
Congcong Lao ◽  
Zhitao Zhang ◽  
Junying Chen ◽  
Haorui Chen ◽  
Zhihua Yao ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Near Infrared ◽  
Soil Moisture Content ◽  
Nir Spectroscopy ◽  
Spectral Variable ◽  
Selection Algorithms ◽  
Salinized Soil

scholarly journals A New Remote Sensing Dryness Index Based on the Near-Infrared and Red Spectral Space

2019 ◽  
Vol 11 (4) ◽  
pp. 456 ◽  
Author(s):  
Jieyun Zhang ◽  
Qingling Zhang ◽  
Anming Bao ◽  
Yujuan Wang
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Moisture Content ◽  
Near Infrared ◽  
Soil Moisture Content ◽  
Spectral Space ◽  
Landsat 8 ◽  
Strong Negative Correlation ◽  
Dryness Index

Soil moisture, as a crucial indicator of dryness, is an important research topic for dryness monitoring. In this study, we propose a new remote sensing dryness index for measuring soil moisture from spectral space. We first established a spectral space with remote sensing reflectance data at the near-infrared (NIR) and red (R) bands. Considering the distribution regularities of soil moisture in this space, we formulated the Ratio Dryness Monitoring Index (RDMI) as a new dryness monitoring indicator. We compared RDMI values with in situ soil moisture content data measured at 0–10 cm depth. Results showed that there was a strong negative correlation (R = −0.89) between the RDMI values and in situ soil moisture content. We further compared RDMI with existing remote sensing dryness indices, and the results demonstrated the advantages of the RDMI. We applied the RDMI to the Landsat-8 imagery to map dryness distribution around the Fukang area on the Northern slope of the Tianshan Mountains, and to the MODIS imagery to detect the spatial and temporal changes in dryness for the entire Xinjiang in 2013 and 2014. Overall, the RDMI index constructed, based on the NIR–Red spectral space, is simple to calculate, easy to understand, and can be applied to dryness monitoring at different scales.

scholarly journals Spectra selection methods: A novel optimization way for treating dynamic spectra and in-line near infrared modeling

2020 ◽  
Vol 13 (04) ◽  
pp. 2050015
Author(s):  
Haiyan Wang ◽  
Ronghua Liu ◽  
Lei Nie ◽  
Dongbo Xu ◽  
Wenping Yin ◽  
...  
Keyword(s):  
Moisture Content ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Selection Methods ◽  
Expansion Chamber ◽  
Distance Method ◽  
Modeling Process ◽  
Time Determination ◽  
Cosine Distance

Near infrared (NIR) spectroscopy is now widely used in fluidized bed granulation. However, there are still some demerits that should be overcome in practice. Valid spectra selection during modeling process is now a hard nut to crack. In this study, a novel NIR sensor and a cosine distance method were introduced to solve this problem in order to make the fluidized process into “visualization”. A NIR sensor was fixed on the side of the expansion chamber to acquire the NIR spectra. Then valid spectra were selected based on a cosine distance method to reduce the influence of dynamic disturbances. Finally, spectral pretreatment and wavelength selection methods were investigated to establish partial least squares (PLS) models to monitor the moisture content. The results showed that the root mean square error of prediction (RMSEP) was 0.124% for moisture content model, which was much lower than that without valid spectra selection treatment. All results demonstrated that with the help of valid spectra selection treatment, NIR sensor could be used for real-time determination of critical quality attributes (CQAs) more accurately. It makes the manufacturing easier to understand than the process parameter control.

scholarly journals Determination of Soil Moisture Content using Laboratory Experimental and Field Electrical Resistivity Values

2018 ◽  
Vol 995 ◽  
pp. 012074
Author(s):  
Z A M Hazreek ◽  
S Rosli ◽  
A Fauziah ◽  
D C Wijeyesekera ◽  
M I M Ashraf ◽  
...  
Keyword(s):  
Electrical Resistivity ◽  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content
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