scholarly journals Mapping Layers of Clay in a Vertical Geological Surface Using Hyperspectral Imagery: Variability in Parameters of SWIR Absorption Features under Different Conditions of Illumination

2014 ◽  
Vol 6 (9) ◽  
pp. 9104-9129 ◽  
Author(s):  
Richard Murphy ◽  
Sven Schneider ◽  
Sildomar Monteiro
Keyword(s):  
Hyperspectral Imagery ◽  
Absorption Features

Automated Cartographic Feature Attribution Using Panchromatic and Hyperspectral Imagery.

1999 ◽  
Author(s):  
David M. McKeown ◽  
McGlone Jr. ◽  
Ford J. C. ◽  
Cochran Stephen J. ◽  
Shufelt Steven D. ◽  
...  
Keyword(s):  
Hyperspectral Imagery

SPICEE: An Extension of SPICE for Sparse Endmember Estimation in Hyperspectral Imagery

2016 ◽  
Vol 13 (12) ◽  
pp. 1910-1914 ◽  
Author(s):  
Seniha Esen Yuksel ◽  
Sefa Kucuk ◽  
Paul D. Gader
Keyword(s):  
Hyperspectral Imagery

Detection of gaseous plumes in airborne hyperspectral imagery

2016 ◽  
Author(s):  
Eyal Agassi ◽  
Eitan Hirsch ◽  
Martin Chamberland ◽  
Marc-André Gagnon ◽  
Holger Eichstaedt
Keyword(s):  
Hyperspectral Imagery

scholarly journals SDSS-IV MaNGA: radial gradients in stellar population properties of early-type and late-type galaxies

2021 ◽  
Vol 502 (4) ◽  
pp. 5508-5527
Author(s):  
Taniya Parikh ◽  
Daniel Thomas ◽  
Claudia Maraston ◽  
Kyle B Westfall ◽  
Brett H Andrews ◽  
...  
Keyword(s):  
Stellar Population ◽  
Mass Range ◽  
Mass Relation ◽  
Individual Element ◽  
Late Type ◽  
Element Abundances ◽  
Entire Mass Range ◽  
Strong Gradient ◽  
Star Formation Histories ◽  
Absorption Features

ABSTRACT We derive ages, metallicities, and individual element abundances of early- and late-type galaxies (ETGs and LTGs) out to 1.5 Re. We study a large sample of 1900 galaxies spanning 8.6–11.3 log M/M⊙ in stellar mass, through key absorption features in stacked spectra from the SDSS-IV/MaNGA survey. We use mock galaxy spectra with extended star formation histories to validate our method for LTGs and use corrections to convert the derived ages into luminosity- and mass-weighted quantities. We find flat age and negative metallicity gradients for ETGs and negative age and negative metallicity gradients for LTGs. Age gradients in LTGs steepen with increasing galaxy mass, from −0.05 ± 0.11 log Gyr/Re for the lowest mass galaxies to −0.82 ± 0.08 log Gyr/Re for the highest mass ones. This strong gradient–mass relation has a slope of −0.70 ± 0.18. Comparing local age and metallicity gradients with the velocity dispersion σ within galaxies against the global relation with σ shows that internal processes regulate metallicity in ETGs but not age, and vice versa for LTGs. We further find that metallicity gradients with respect to local σ show a much stronger dependence on galaxy mass than radial metallicity gradients. Both galaxy types display flat [C/Fe] and [Mg/Fe], and negative [Na/Fe] gradients, whereas only LTGs display gradients in [Ca/Fe] and [Ti/Fe]. ETGs have increasingly steep [Na/Fe] gradients with local σ reaching 6.50 ± 0.78 dex/log km s−1 for the highest masses. [Na/Fe] ratios are correlated with metallicity for both galaxy types across the entire mass range in our sample, providing support for metallicity-dependent supernova yields.

scholarly journals Using UAV-Based Hyperspectral Imagery to Detect Winter Wheat Fusarium Head Blight

2021 ◽  
Vol 13 (15) ◽  
pp. 3024
Author(s):  
Huiqin Ma ◽  
Wenjiang Huang ◽  
Yingying Dong ◽  
Linyi Liu ◽  
Anting Guo
Keyword(s):  
Winter Wheat ◽  
Fusarium Head Blight ◽  
Hyperspectral Imagery ◽  
Spectral Feature ◽  
Support Vector ◽  
Detection Accuracy ◽  
Feature Combination ◽  
Field Scale ◽  
Head Blight ◽  
Detection Model

Fusarium head blight (FHB) is a major winter wheat disease in China. The accurate and timely detection of wheat FHB is vital to scientific field management. By combining three types of spectral features, namely, spectral bands (SBs), vegetation indices (VIs), and wavelet features (WFs), in this study, we explore the potential of using hyperspectral imagery obtained from an unmanned aerial vehicle (UAV), to detect wheat FHB. First, during the wheat filling period, two UAV-based hyperspectral images were acquired. SBs, VIs, and WFs that were sensitive to wheat FHB were extracted and optimized from the two images. Subsequently, a field-scale wheat FHB detection model was formulated, based on the optimal spectral feature combination of SBs, VIs, and WFs (SBs + VIs + WFs), using a support vector machine. Two commonly used data normalization algorithms were utilized before the construction of the model. The single WFs, and the spectral feature combination of optimal SBs and VIs (SBs + VIs), were respectively used to formulate models for comparison and testing. The results showed that the detection model based on the normalized SBs + VIs + WFs, using min–max normalization algorithm, achieved the highest R2 of 0.88 and the lowest RMSE of 2.68% among the three models. Our results suggest that UAV-based hyperspectral imaging technology is promising for the field-scale detection of wheat FHB. Combining traditional SBs and VIs with WFs can improve the detection accuracy of wheat FHB effectively.

scholarly journals Author Correction: Using hyperspectral imagery to investigate large-scale seagrass cover and genus distribution in a temperate coast

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kenneth Clarke ◽  
Andrew Hennessy ◽  
Andrew McGrath ◽  
Robert Daly ◽  
Sam Gaylard ◽  
...  
Keyword(s):  
Large Scale ◽  
Hyperspectral Imagery ◽  
Genus Distribution ◽  
Seagrass Cover

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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