Study on infrared imaging spectrometer with large aperture static interferometer

2009 ◽  
Author(s):  
Lin Ma ◽  
Weijian Zheng ◽  
Junhong Su
Keyword(s):  
Infrared Imaging ◽  
Imaging Spectrometer ◽  
Large Aperture

Corrective method for spectral offset error caused by radial distortion in the large aperture static imaging spectrometer

2020 ◽  
Vol 13 (6) ◽  
pp. 1-8
Author(s):  
AN Ling-ping ◽  
◽  
WANG Shuang ◽  
ZHANG Geng ◽  
LI Juan ◽  
...  
Keyword(s):  
Imaging Spectrometer ◽  
Radial Distortion ◽  
Large Aperture ◽  
Corrective Method ◽  
Offset Error ◽  
Static Imaging

scholarly journals The short life of the volcanic island New Late’iki (Tonga) analyzed by multi-sensor remote sensing data

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Simon Plank ◽  
Francesco Marchese ◽  
Nicola Genzano ◽  
Michael Nolde ◽  
Sandro Martinis
Keyword(s):  
Infrared Imaging ◽  
Rapid Change ◽  
Monitoring Network ◽  
Remote Sensing Data ◽  
Volcanic Island ◽  
Imaging Spectrometer ◽  
Remote Areas ◽  
Moderate Resolution ◽  
Satellite Sensors ◽  
Resolution Imaging

AbstractSatellite-based Earth observation plays a key role for monitoring volcanoes, especially those which are located in remote areas and which very often are not observed by a terrestrial monitoring network. In our study we jointly analyzed data from thermal (Moderate Resolution Imaging Spectrometer MODIS and Visible Infrared Imaging Radiometer Suite VIIRS), optical (Operational Land Imager and Multispectral Instrument) and synthetic aperture radar (SAR) (Sentinel-1 and TerraSAR-X) satellite sensors to investigate the mid-October 2019 surtseyan eruption at Late’iki Volcano, located on the Tonga Volcanic Arc. During the eruption, the remains of an older volcanic island formed in 1995 collapsed and a new volcanic island, called New Late’iki was formed. After the 12 days long lasting eruption, we observed a rapid change of the island’s shape and size, and an erosion of this newly formed volcanic island, which was reclaimed by the ocean two months after the eruption ceased. This fast erosion of New Late’iki Island is in strong contrast to the over 25 years long survival of the volcanic island formed in 1995.

scholarly journals Detection and Quantification of Snow Algae with an Airborne Imaging Spectrometer

2001 ◽  
Vol 67 (11) ◽  
pp. 5267-5272 ◽  
Author(s):  
Thomas H. Painter ◽  
Brian Duval ◽  
William H. Thomas ◽  
Maria Mendez ◽  
Sara Heintzelman ◽  
...  
Keyword(s):  
Sierra Nevada ◽  
Wavelength Range ◽  
Spectral Reflectance ◽  
Infrared Imaging ◽  
Spectral Signature ◽  
Absorption Feature ◽  
Imaging Spectrometer ◽  
Algal Concentration ◽  
Airborne Imaging ◽  
Spectrometer Data

ABSTRACT We describe spectral reflectance measurements of snow containing the snow alga Chlamydomonas nivalis and a model to retrieve snow algal concentrations from airborne imaging spectrometer data. Because cells of C. nivalis absorb at specific wavelengths in regions indicative of carotenoids (astaxanthin esters, lutein, β-carotene) and chlorophylls a and b, the spectral signature of snow containing C. nivalis is distinct from that of snow without algae. The spectral reflectance of snow containing C. nivalis is separable from that of snow without algae due to carotenoid absorption in the wavelength range from 0.4 to 0.58 μm and chlorophyll a and babsorption in the wavelength range from 0.6 to 0.7 μm. The integral of the scaled chlorophyll a and b absorption feature (I 0.68) varies with algal concentration (Ca ). Using the relationshipCa = 81019.2 I 0.68+ 845.2, we inverted Airborne Visible Infrared Imaging Spectrometer reflectance data collected in the Tioga Pass region of the Sierra Nevada in California to determine algal concentration. For the 5.5-km2 region imaged, the mean algal concentration was 1,306 cells ml−1, the standard deviation was 1,740 cells ml−1, and the coefficient of variation was 1.33. The retrieved spatial distribution was consistent with observations made in the field. From the spatial estimates of algal concentration, we calculated a total imaged algal biomass of 16.55 kg for the 0.495-km2 snow-covered area, which gave an areal biomass concentration of 0.033 g/m2.

Optical simulation of large aperture spatial heterodyne imaging spectrometer

2016 ◽  
Vol 366 ◽  
pp. 136-141 ◽  
Author(s):  
Qisheng Cai ◽  
Bin Xiangli ◽  
Yu Fang
Keyword(s):  
Optical Simulation ◽  
Imaging Spectrometer ◽  
Large Aperture

Joint ESA and NASA Imaging Spectrometer Airborne Campaign to Support CHIME and SBG

2021 ◽  
Author(s):  
Robert Green ◽  
Michael Rast ◽  
Michael Schaepman ◽  
Andreas Hueni ◽  
Michael Eastwood
Keyword(s):  
Uncertainty Quantification ◽  
Hyperspectral Imaging ◽  
Infrared Imaging ◽  
State Of The Art ◽  
Atmospheric Correction ◽  
Imaging Spectrometer ◽  
Science Collaboration ◽  
Study Sites ◽  
University Of Zurich ◽  
The University

<p>In 2018 a joint ESA and NASA airborne campaign was orchestrated with the University of Zurich to advance cooperation and harmonization of algorithms and products from imaging spectrometer measurements.  This effort was intended to benefit the future candidate European Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) and NASA Surface Biology and Geology mission. For this campaign, the Airborne Visible/Infrared Imaging Spectrometer Next Generation was deployed from May to July 2018.  Twenty-four study sites were measured across Germany, Italy, and Switzerland.  All measurements were rapidly calibrated, atmospherically corrected, and made available to NASA and ESA investigators.  An expanded 2021 campaign is now planned with goals to: 1) further test and evaluate new state-of-the-art science algorithms: atmospheric correction, etc; 2)  grow international science collaboration in support of ESA CHIME and NASA SBG; 3) test/demonstrate calibration, validation, and uncertainty quantification approaches;  4) collect strategic cross-comparison under flights of space missions: DESIS, PRISMA, Sentinels, etc.  In this paper, we present an overview of the key results from the 2018 campaign and plans for the 2021 campaign.</p><p> </p>

Study of the Structure of Large Aperture Ultraviolet Fourier Transform Imaging Spectrometer

2014 ◽  
Vol 34 (3) ◽  
pp. 0330001
Author(s):  
刘洋 Liu Yang ◽  
廖宁放 Liao Ningfang ◽  
白廷柱 Bai Tingzhu ◽  
吕航 Lü Hang ◽  
廉玉生 Lian Yusheng
Keyword(s):  
Fourier Transform ◽  
Imaging Spectrometer ◽  
Large Aperture

Exposure Time Control of Large Aperture Static Imaging Spectrometer

2015 ◽  
Vol 44 (11) ◽  
pp. 1123004
Author(s):  
杨阳 YANG Yang ◽  
刘学斌 LIU Xue-bin
Keyword(s):  
Exposure Time ◽  
Imaging Spectrometer ◽  
Large Aperture ◽  
Time Control ◽  
Static Imaging
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