The Impact of Soiling, Moisture Content, Abrasion and Ultraviolet Exposure on Near-Infrared Evaluation of In-Use Firefighter Protective Clothing

Near-infrared (NIR) reflective materials are being developed for mitigating building cooling needs. Their use contributes to broadening the range of colours, responding to the urban aesthetic demand without compromising the building performance. Despite the increase in NIR reflective pigments investigation, there is still a knowledge gap in their applicability, impact, and durability in multilayer finishing coatings of External Thermal Insulation Composite Systems (ETICS). Hence, the main goal of this work consists of evaluating the impact of incorporating NIR reflective pigments (NRP) in the solar reflectance of the surface layer of ETICS, without affecting the colour perception, as well as their influence on the colour durability and surface temperature. As such, colour, solar reflectance, and surface temperature were monitored for 2 years in dark-coloured specimens of ETICS, with and without NRP and a primer layer. It was confirmed that the main contribution of NRP is the increase of solar reflectance and, consequently, the decrease in surface temperature, especially for high exterior temperatures (around 30 ºC). Moreover, these pigments highly increase the NIR reflectance without affecting the visible colour. In addition, they contribute to maintaining the colour characteristics. The application of primer increased the surface temperature, especially for higher exterior temperatures. However, it contributes to a lower colour difference and solar reflectance variation, which is an important achievement for durability purposes.

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Application of long-wave near infrared hyperspectral imaging for determination of moisture content of single maize seed

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy ◽

10.1016/j.saa.2021.119666 ◽

2021 ◽

Vol 254 ◽

pp. 119666

Author(s):

Zheli Wang ◽

Shuxiang Fan ◽

Jingzhu Wu ◽

Chi Zhang ◽

Fengying Xu ◽

...

Keyword(s):

Moisture Content ◽

Hyperspectral Imaging ◽

Near Infrared ◽

Maize Seed ◽

Long Wave

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A GNSS-IR Method for Retrieving Soil Moisture Content from Integrated Multi-Satellite Data That Accounts for the Impact of Vegetation Moisture Content

Remote Sensing ◽

10.3390/rs13132442 ◽

2021 ◽

Vol 13 (13) ◽

pp. 2442

Author(s):

Jichao Lv ◽

Rui Zhang ◽

Jinsheng Tu ◽

Mingjie Liao ◽

Jiatai Pang ◽

...

Keyword(s):

Soil Moisture ◽

Moisture Content ◽

Satellite Data ◽

Vegetation Index ◽

Soil Moisture Content ◽

Support Vector ◽

Observation Data ◽

Multipath Effect ◽

Mars Model ◽

The Impact

There are two problems with using global navigation satellite system-interferometric reflectometry (GNSS-IR) to retrieve the soil moisture content (SMC) from single-satellite data: the difference between the reflection regions, and the difficulty in circumventing the impact of seasonal vegetation growth on reflected microwave signals. This study presents a multivariate adaptive regression spline (MARS) SMC retrieval model based on integrated multi-satellite data on the impact of the vegetation moisture content (VMC). The normalized microwave reflection index (NMRI) calculated with the multipath effect is mapped to the normalized difference vegetation index (NDVI) to estimate and eliminate the impact of VMC. A MARS model for retrieving the SMC from multi-satellite data is established based on the phase shift. To examine its reliability, the MARS model was compared with a multiple linear regression (MLR) model, a backpropagation neural network (BPNN) model, and a support vector regression (SVR) model in terms of the retrieval accuracy with time-series observation data collected at a typical station. The MARS model proposed in this study effectively retrieved the SMC, with a correlation coefficient (R2) of 0.916 and a root-mean-square error (RMSE) of 0.021 cm3/cm3. The elimination of the vegetation impact led to 3.7%, 13.9%, 11.7%, and 16.6% increases in R2 and 31.3%, 79.7%, 49.0%, and 90.5% decreases in the RMSE for the SMC retrieved by the MLR, BPNN, SVR, and MARS model, respectively. The results demonstrated the feasibility of correcting the vegetation changes based on the multipath effect and the reliability of the MARS model in retrieving the SMC.

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The Improvement on the Performance of DMD Hadamard Transform Near-Infrared Spectrometer by Double Filter Strategy and a New Hadamard Mask

Micromachines ◽

10.3390/mi10020149 ◽

2019 ◽

Vol 10 (2) ◽

pp. 149 ◽

Cited By ~ 1

Author(s):

Zifeng Lu ◽

Jinghang Zhang ◽

Hua Liu ◽

Jialin Xu ◽

Jinhuan Li

Keyword(s):

Near Infrared ◽

Signal To Noise Ratio ◽

Nonuniform Distribution ◽

Stray Light ◽

Spectral Energy ◽

Hadamard Transform ◽

Digital Micromirror Device ◽

Infrared Spectrometer ◽

Near Infrared Spectrometer ◽

The Impact

In the Hadamard transform (HT) near-infrared (NIR) spectrometer, there are defects that can create a nonuniform distribution of spectral energy, significantly influencing the absorbance of the whole spectrum, generating stray light, and making the signal-to-noise ratio (SNR) of the spectrum inconsistent. To address this issue and improve the performance of the digital micromirror device (DMD) Hadamard transform near-infrared spectrometer, a split waveband scan mode is proposed to mitigate the impact of the stray light, and a new Hadamard mask of variable-width stripes is put forward to improve the SNR of the spectrometer. The results of the simulations and experiments indicate that by the new scan mode and Hadamard mask, the influence of stray light is restrained and reduced. In addition, the SNR of the spectrometer also is increased.

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