scholarly journals Visible And Infrared Linear Detector Arrays For The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

1987 ◽  
Author(s):  
Gary C. Bailey
2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Simon Plank ◽  
Francesco Marchese ◽  
Nicola Genzano ◽  
Michael Nolde ◽  
Sandro Martinis

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.


2001 ◽  
Vol 67 (11) ◽  
pp. 5267-5272 ◽  
Author(s):  
Thomas H. Painter ◽  
Brian Duval ◽  
William H. Thomas ◽  
Maria Mendez ◽  
Sara Heintzelman ◽  
...  

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.


2014 ◽  
Vol 8 (1-2) ◽  
pp. 60-70 ◽  
Author(s):  
Mathias Schwarz ◽  
Andreas Buehler ◽  
Vasilis Ntziachristos

2021 ◽  
Author(s):  
Robert Green ◽  
Michael Rast ◽  
Michael Schaepman ◽  
Andreas Hueni ◽  
Michael Eastwood

<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>


2011 ◽  
Vol 40 (5) ◽  
pp. 673-678
Author(s):  
薛庆生 XUE Qing-sheng ◽  
林冠宇 LIN Guang-yu ◽  
宋克非 SONG Ke-fei

2018 ◽  
Vol 47 (4) ◽  
pp. 418001 ◽  
Author(s):  
袁立银 Yuan Liyin ◽  
谢佳楠 Xie Jianan ◽  
侯 佳 Hou Jia ◽  
吕 刚 Lv Gang ◽  
何志平 He Zhiping

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