reflectance spectra
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2022 ◽  
Vol 14 (2) ◽  
pp. 405
Author(s):  
Kay Wohlfarth ◽  
Christian Wöhler

Telescopic observations of Mercury consistently report systematic variations of the normalized spectral slope of visible-to-near-infrared reflectance spectra. This effect was previously assumed to be a photometric property of the regolith, but it is not yet fully understood. After the MESSENGER mission, detailed global spectral maps of Mercury are available that better constrain Mercury’s photometry. So far, wavelength-dependent seeing has not been considered in the context of telescopic observations of Mercury. This study investigates the effect of wavelength-dependent seeing on systematic variations of Mercury’s normalized spectral reflectance slope. Therefore, we simulate the disk of Mercury for an idealized scenario, as seen by four different telescopic campaigns using the Hapke and the Kaasalainen–Shkuratov photometric model, the MDIS global mosaic, and a simple wavelength-dependent seeing model. The simulation results are compared with the observations of previous telescopic studies. We find that wavelength-dependent seeing affects the normalized spectral slope in several ways. The normalized slopes are enhanced near the limb, decrease toward the rim of the seeing disk, and even become negative. The decrease of the normalized spectral slope is consistent with previous observations. However, previous studies have associated the spectral slope variations with photometric effects that correlate with the emission angle. Our study suggests that wavelength-dependent seeing may cause these systematic variations. The combined reflectance and seeing model can also account for slope variations between different measurement campaigns. We report no qualitative differences between results based on the Hapke model or the Kaasalainen–Shkuratov model.


Vestnik MGTU ◽  
2021 ◽  
Vol 24 (4) ◽  
pp. 450-460
Author(s):  
V. Yu. Novikov ◽  
K. S. Rysakova ◽  
A. V. Baryshnikov

It is well known that fish belonging to the Salmonidae family differ in their nutritional value. Anatomical and morphological features of different salmon species have a certain similarity; therefore, representatives of this family are most often falsified. Assortment falsification of products from fish of this family is usually carried out by replacing more valuable species with cheaper ones with a reduced nutritional value. Most often, counterfeiting of Atlantic salmon (salmon) by Far Eastern ones (chum salmon, pink salmon, chinook salmon, coho salmon) is found. Near infrared spectroscopy (NIR) is now increasingly used for identification and authentication of closely related organisms, in some cases being a rapid method replacing genetic analysis. We have obtained diffusion reflectance spectra of NIR radiation for three species of fish from the Northern Basin belonging to the salmon family. The best classification by fish species has been obtained by analyzing the NIR spectra of pre-dried fat-free muscle tissue samples. In case of wet samples, the observed differences are less significant, up to insignificant differences in individual values from neighboring clusters. The possibility of using the method of linear discriminant analysis of the NIR reflection spectra of muscle proteins for the species identification of fish has been shown.


Coatings ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 37
Author(s):  
Marek Gąsiorowski ◽  
Piotr Szymak ◽  
Leszek Bychto ◽  
Aleksy Patryn

This article undertakes the subject matter of applying artificial neural networks to analyze optical reflectance spectra of objects exhibiting a change of optical properties in the domain of time. A compact Digital Light Projection NIRscan Nano Evaluation Module spectrometer was used to record spectra. Due to the miniature spectrometer’s size and its simplicity of measurement, it can be used to conduct tests outside of a laboratory. A series of plant-derived objects were used as test subjects with rapidly changing optical properties in the presented research cycle. The application of artificial neural networks made it possible to determine the aging time of plants with a relatively low mean squared error, reaching 0.56 h for the Levenberg–Marquardt backpropagation training method. The results of the other ten training methods for artificial neural networks have been included in the paper.


2021 ◽  
Author(s):  
Kateryna Zolotukhina ◽  
Iryna Soltys

2021 ◽  
Vol 137 (1) ◽  
Author(s):  
Jacopo Melada ◽  
Letizia Bonizzoni ◽  
Marco Gargano ◽  
Emanuela Grifoni ◽  
Nicola Ludwig

2021 ◽  
Author(s):  
L. Mandon ◽  
P. Beck ◽  
C. Quantin‐Nataf ◽  
E. Dehouck ◽  
P. Thollot ◽  
...  
Keyword(s):  

2021 ◽  
Author(s):  
Xiao Zhang ◽  
Liangyun Liu ◽  
Tingting Zhao ◽  
Yuan Gao ◽  
Xidong Chen ◽  
...  

Abstract. Accurately mapping impervious surface dynamics has great scientific significance and application value for urban sustainable development research, anthropogenic carbon emission assessment and global ecological environment modeling. In this study, a novel and accurate global 30 m impervious surface dynamic dataset (GISD30) for 1985 to 2020 was produced using the spectral generalization method and time-series Landsat imagery, on the Google Earth Engine cloud-computing platform. Firstly, the global training samples and corresponding reflectance spectra were automatically derived from prior global 30 m land-cover products after employing the multitemporal compositing method and relative radiometric normalization. Then, spatiotemporal adaptive classification models, trained with the migrated reflectance spectra of impervious surfaces from 2020 and pervious surface samples in the same epoch for each 5° × 5° geographical tile, were applied to map the impervious surface in each period. Furthermore, a spatiotemporal consistency correction method was presented to minimize the effects of independent classification errors and improve the spatiotemporal consistency of impervious surface dynamics. Our global 30 m impervious surface dynamic model achieved an overall accuracy of 91.5 % and a kappa coefficient of 0.866 using 18,540 global time-series validation samples. Cross-comparisons with four existing global 30 m impervious surface products further indicated that our GISD30 dynamic product achieved the best performance in capturing the spatial distributions and spatiotemporal dynamics of impervious surfaces in various impervious landscapes. The statistical results indicated that the global impervious surface has doubled in the past 35 years, from 5.116 × 105 km2 in 1985 to 10.871 × 105 km2 in 2020, and Asia saw the largest increase in impervious surface area compared to other continents, with a total increase of 2.946 × 105 km2. Therefore, it was concluded that our global 30 m impervious surface dynamic dataset is an accurate and promising product, and could provide vital support in monitoring regional or global urbanization as well as in related applications. The global 30 m impervious surface dynamic dataset from 1985 to 2020 generated in this paper is free to access at http://doi.org/10.5281/zenodo.5220816 (Liu et al., 2021b).


2021 ◽  
Author(s):  
J.A. Veitch ◽  
L.A. Whitehead

The higher the colour fidelity of a light source, the lower its luminous efficacy of radiation because the light source spectrum must deviate from V(λ) to deliver the higher fidelity. Two experiments probed the trade-off between energy efficiency and colour quality. Experiment 1 required participants to simultaneously view pairs of light sources differing in colour fidelity, at either a higher (346 lx) or lower (277 lx) illuminance. Participants performed a timed reading task and judged the colour appearance of the pair. There were no effects of illuminance, but larger colour fidelity differences between the light sources in the pair correlated with lower appearance judgements. Experiment 2 simulated the effect of light sources on defined reflectance spectra. The results showed that improvements of colour fidelity above what is often considered satisfactory can yield more satisfying illumination while using the same amount of power.


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