High spectral resolution / low-temperature IR study of carbonates

2021 ◽  
Author(s):  
Simone De Angelis ◽  
Bernard Schmitt ◽  
Pierre Beck ◽  
Cristian Carli ◽  
Olivier Poch ◽  
...  
1959 ◽  
Vol 3 ◽  
pp. 41-47
Author(s):  
A. Taylor

AbstractThe camera was constructed to fill the need for a low-temperature instrument capable of yielding high spectral resolution and accurate lattice parameters. Specimen temperatures in the range -190 to 300°C are attainable.A special feature of the camera is the film holder which is split along the beam axis into two symmetrical halves and which can easily be removed from the base without disturbing the cooling system or the specimen. The specimenholderis mounted on a cross-slide to enable specimens of large radius to be rotated off-center with the beam at glancing incidence to their surface. Finally, diffraction patterns from large metallurgical samples may be obtained by removing one of the film holders and employing the apparatus as a “half camera.”Some applications of the camera to the thermal expansion of SiC and MnSe are described.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hua-Tian Tu ◽  
An-Qing Jiang ◽  
Jian-Ke Chen ◽  
Wei-Jie Lu ◽  
Kai-Yan Zang ◽  
...  

AbstractUnlike the single grating Czerny–Turner configuration spectrometers, a super-high spectral resolution optical spectrometer with zero coma aberration is first experimentally demonstrated by using a compound integrated diffraction grating module consisting of 44 high dispersion sub-gratings and a two-dimensional backside-illuminated charge-coupled device array photodetector. The demonstrated super-high resolution spectrometer gives 0.005 nm (5 pm) spectral resolution in ultra-violet range and 0.01 nm spectral resolution in the visible range, as well as a uniform efficiency of diffraction in a broad 200 nm to 1000 nm wavelength region. Our new zero-off-axis spectrometer configuration has the unique merit that enables it to be used for a wide range of spectral sensing and measurement applications.


2021 ◽  
Vol 13 (9) ◽  
pp. 1693
Author(s):  
Anushree Badola ◽  
Santosh K. Panda ◽  
Dar A. Roberts ◽  
Christine F. Waigl ◽  
Uma S. Bhatt ◽  
...  

Alaska has witnessed a significant increase in wildfire events in recent decades that have been linked to drier and warmer summers. Forest fuel maps play a vital role in wildfire management and risk assessment. Freely available multispectral datasets are widely used for land use and land cover mapping, but they have limited utility for fuel mapping due to their coarse spectral resolution. Hyperspectral datasets have a high spectral resolution, ideal for detailed fuel mapping, but they are limited and expensive to acquire. This study simulates hyperspectral data from Sentinel-2 multispectral data using the spectral response function of the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor, and normalized ground spectra of gravel, birch, and spruce. We used the Uniform Pattern Decomposition Method (UPDM) for spectral unmixing, which is a sensor-independent method, where each pixel is expressed as the linear sum of standard reference spectra. The simulated hyperspectral data have spectral characteristics of AVIRIS-NG and the reflectance properties of Sentinel-2 data. We validated the simulated spectra by visually and statistically comparing it with real AVIRIS-NG data. We observed a high correlation between the spectra of tree classes collected from AVIRIS-NG and simulated hyperspectral data. Upon performing species level classification, we achieved a classification accuracy of 89% for the simulated hyperspectral data, which is better than the accuracy of Sentinel-2 data (77.8%). We generated a fuel map from the simulated hyperspectral image using the Random Forest classifier. Our study demonstrated that low-cost and high-quality hyperspectral data can be generated from Sentinel-2 data using UPDM for improved land cover and vegetation mapping in the boreal forest.


2015 ◽  
Vol 53 (2) ◽  
pp. 869-882 ◽  
Author(s):  
Eva M. Ampe ◽  
Dries Raymaekers ◽  
Erin L. Hestir ◽  
Maarten Jansen ◽  
Els Knaeps ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document