Mineralogical composition of terrestrial feldspathic rocks using reflectance spectroscopy data from HySpex hyperspectral cameras

Author(s):  
Marie Barthez ◽  
Jessica Flahaut ◽  
Gen Ito ◽  
Julio Hernandez-Palacios ◽  
Na Liu ◽  
...  

<p>New feldspar detections made by visible-near infrared (VNIR) spectroscopy last year on Mars [1], raise questions on the nature of the rocks involved and the magmatic processes responsible for their formation.</p><p>Following these new findings, a range of terrestrial feldspathic rocks, which are possible analogs to the feldspar-bearing Martian rocks, were analyzed using a VNIR point-spectrometer (ASD Fieldspec 4) in a laboratory [2]. A spectral library referencing the average reflectance spectrum of uncrushed terrestrial feldspathic rocks, including granites, granodiorites, phenocryst basalts, dacites, anorthosites, was assembled. One of the conclusions from this work was that a more detailed, grain-by-grain spectral analysis is needed.</p><p>In this study we used a new instrument that made it possible to determine the grain-by-grain mineralogical composition of these same terrestrial analog rocks. VNIR spectra were acquired with the HySpex hyperspectral cameras VNIR-1800 and SWIR-384 that acquire high-resolution data in the visible near-infrared and short-wave infrared wavelength ranges. The cameras image the scene line by line using the pushbroom scanning technique. Using interchangeable lenses, cameras were used to acquire spectroscopy data at a distance of 30cm and at 8cm from the sample. In the VNIR, this results in a pixel size of about 53 µm and 24µm at sample-sensor distance of 30cm and 8cm, respectively, while in the SWIR, the pixel size is 250 µm and 55µm at a distance of at 30cm and 8cm, respectively. The hyperspectral cubes are analyzed with the ENVI software to classify the image pixels according to their spectral signature. Thus, the different minerals present in the rock, which are often on a millimeter scale, are grouped into different classes. The statistics give the average spectrum of each class, and therefore each mineral group.</p><p>This study, complementary to that of <em>Barthez et al. </em>(2020), makes it possible to associate, for each studied rock sample, an average reflectance spectrum of the bulk rock to a precise mapping of the different minerals present in the rock. This study allows us to determine if the feldspar minerals are contributing to the observed rock spectrum, and to assess each mineral group’s contribution to the spectral signature of the whole rock. Detailed petrographic characterization of rocks are also being conducted to evaluate characterizations done with spectral data.</p><p> </p><p><strong>References</strong></p><p>[1] J.Flahaut et al. (2020). EGU Abstracts, EGU2020-13377</p><p>[2] M.Barthez et al. (2020). EPSC Abstracts, EPSC2020-606</p>

Micromachines ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 236
Author(s):  
Rui Lou ◽  
Guangying Li ◽  
Xu Wang ◽  
Wenfu Zhang ◽  
Yishan Wang ◽  
...  

Antireflection and superhydrophilicity performance are desirable for improving the properties of electronic devices. Here, we experimentally provide a strategy of femtosecond laser preparation to create micro-nanostructures on the graphite surface in an air environment. The modified graphite surface is covered with abundant micro-nano structures, and its average reflectance is measured to be 2.7% in the ultraviolet, visible and near-infrared regions (250 to 2250 nm). The wettability transformation of the surface from hydrophilicity to superhydrophilicity is realized. Besides, graphene oxide (GO) and graphene are proved to be formed on the sample surface. This micro-nanostructuring method, which demonstrates features of high efficiency, high controllability, and hazardous substances zero discharge, exhibits the application for functional surface.


ENTRAMADO ◽  
2019 ◽  
Vol 15 (2) ◽  
pp. 256-262
Author(s):  
Edier Fernando Ávila Vélez ◽  
Natalia Escobar Escobar ◽  
Carlos Francisco Morantes Choconta

Maize is currently the world’s second largest crop in terms of production, after wheat and rice. It is the first cereal as for grain yield per hectare and the second, after wheat, regarding total production. Maize has great economic importance worldwide, both as human and/or animal food, and as a source of a large number of industrial products. New digital technologies are allowing greater monitoring of farming production stages. This research developed the spectral signature of maize fields ground covers across different growth stages (2 months, 2.3 months and 4.3 months). Similarly, this research paper proposes the application of a methodology based on four phases: 1. Maize crop georeferencing, 2. Satellite images selection, 3. Radiometric calibration of images 4. Spectral signature development of maize crops. Spectral response or signature of maize crops at visible and near-infrared wavelengths was obtained, indicating significant changes in crops growth. The use of satellite imagery becomes an interesting tool that introduces an approach towards more accurate and controlled monitoring systems in agricultural production.


Author(s):  
Eri Tatsumi ◽  
Marcel Popescu ◽  
Humberto Campins ◽  
Julia de León ◽  
Juan Luis Rizos García ◽  
...  

Abstract Using the multiband imager MapCam onboard the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer) spacecraft, we identified 77 instances of proposed exogenic materials distributed globally on the surface of the B-type asteroid (101955) Bennu. We identified materials as exogenic on the basis of an absorption near 1 µm that is indicative of anhydrous silicates. The exogenic materials are spatially resolved by the telescopic camera PolyCam. All such materials are brighter than their surroundings, and they are expressed in a variety of morphologies: homogeneous, breccia-like, inclusion-like, and others. Inclusion-like features are the most common. Visible spectrophotometry was obtained for 46 of the 77 locations from MapCam images. Principal component analysis indicates at least two trends: (i) mixing of Bennu's average spectrum with a strong 1-µm band absorption, possibly from pyroxene-rich material, and (ii) mixing with a weak 1-µm band absorption. The endmember with a strong 1-µm feature is consistent with Howardite-Eucrite-Diogenite (HED) meteorites, whereas the one showing a weak 1-µm feature may be consistent with HEDs, ordinary chondrites, or carbonaceous chondrites. The variation in the few available near-infrared reflectance spectra strongly suggests varying compositions among the exogenic materials. Thus, Bennu might record the remnants of multiple impacts with different compositions to its parent body, which could have happened in the very early history of the Solar System. Moreover, at least one of the exogenic objects is compositionally different from the exogenic materials found on the similar asteroid (162173) Ryugu, and they suggest different impact tracks.


2021 ◽  
Vol 29 (4) ◽  
Author(s):  
Nor Athirah Roslin ◽  
Nik Norasma Che’Ya ◽  
Nursyazyla Sulaiman ◽  
Lutfi Amir Nor Alahyadi ◽  
Mohd Razi Ismail

Weed infestation happens when there is intense competition between rice and weeds for light, nutrients and water. These conditions need to be monitored and controlled to lower the growth of weeds as they affected crops production. The characteristics of weeds and rice are challenging to differentiate macroscopically. However, information can be acquired using a spectral signature graph. Hence, this study emphasises using the spectral signature of weed species and rice in a rice field. The study aims to generate a spectral signature graph of weeds in rice fields and develop a mobile application for the spectral signature of weeds. Six weeds were identified in Ladang Merdeka using Fieldspec HandHeld 2 Spectroradiometer. All the spectral signatures were stored in a spectral database using Apps Master Builder, viewed using smartphones. The results from the spectral signature graph show that the jungle rice (Echinochloa spp.) has the highest near-infrared (NIR) reflectance. In contrast, the saromacca grass (Ischaemum rugosum) shows the lowest NIR reflectance. Then, the first derivative (FD) analysis was run to visualise the separation of each species, and the 710 nm to 750 nm region shows the highest separation. It shows that the weed species can be identified using spectral signature by FD analysis with accurate separation. The mobile application was developed to provide information about the weeds and control methods to the users. Users can access information regarding weeds and take action based on the recommendations of the mobile application.


2003 ◽  
Vol 211 ◽  
pp. 87-90
Author(s):  
M. Tamura ◽  
T. Naoi ◽  
Y. Oasa ◽  
Y. Nakajima ◽  
C. Nagashima ◽  
...  

We are currently conducting three kinds of IR surveys of star forming regions (SFRs) in order to seek for very low-mass young stellar populations. First is a deep JHKs-bands (simultaneous) survey with the SIRIUS camera on the IRSF 1.4m or the UH 2.2m telescopes. Second is a very deep JHKs survey with the CISCO IR camera on the Subaru 8.2m telescope. Third is a high resolution companion search around nearby YSOs with the CIAO adaptive optics coronagraph IR camera on the Subaru. In this contribution, we describe our SIRIUS camera and present preliminary results of the ongoing surveys with this new instrument.


Author(s):  
Eniel Rodríguez-Machado ◽  
Osmany Aday-Díaz ◽  
Luis Hernández-Santana ◽  
Jorge Luís Soca-Muñoz ◽  
Rubén Orozco-Morales

Precision agriculture, making use of the spatial and temporal variability of cultivable land, allows farmers to refine fertilization, control field irrigation, estimate planting productivity, and detect pests and disease in crops. To that end, this paper identifies the spectral reflectance signature of brown rust (Puccinia melanocephala) and orange rust (Puccinia kuehnii), which contaminate sugar cane leaves (Saccharum spp.). By means of spectrometry, the mean values and standard deviations of the spectral reflectance signature are obtained for five levels of contamination of the leaves in each type of rust, observing the greatest differences between healthy and diseased leaves in the red (R) and near infrared (NIR) bands. With the results obtained, a multispectral camera was used to obtain images of the leaves and calculate the Normalized Difference Vegetation Index (NDVI). The results identified the presence of both plagues by differentiating healthy from contaminated leaves through the index value with an average difference of 11.9% for brown rust and 9.9% for orange rust.


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