Acousto-optic infrared imaging spectrometer for close-up sensing of planetary surfaces

2018 ◽  
Author(s):  
Denis Belyaev ◽  
Konstantin Yushkov ◽  
Sergey Anikin ◽  
Yury Dobrolenskiy ◽  
Aleksander Laskin ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Planetary Surfaces ◽  
Imaging Spectrometer

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.

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>

Optical Design of Spaceborne Shortwave Infrared Imaging Spectrometer with Wide Field of View

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
Keyword(s):  
Infrared Imaging ◽  
Optical Design ◽  
Field Of View ◽  
Wide Field ◽  
Imaging Spectrometer ◽  
Wide Field Of View ◽  
Shortwave Infrared

Optical design of compact infrared imaging spectrometer

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
Keyword(s):  
Infrared Imaging ◽  
Optical Design ◽  
Imaging Spectrometer

scholarly journals Continuing the MODIS Dark Target Aerosol Time Series with VIIRS

2020 ◽  
Vol 12 (2) ◽  
pp. 308 ◽  
Author(s):  
Virginia Sawyer ◽  
Robert C. Levy ◽  
Shana Mattoo ◽  
Geoff Cureton ◽  
Yingxi Shi ◽  
...  
Keyword(s):  
Near Infrared ◽  
Infrared Imaging ◽  
Retrieval Algorithm ◽  
Spatial And Temporal Variability ◽  
Imaging Spectrometer ◽  
Standard Data ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Infrared Wavelengths ◽  
Good Agreement

For reflected sunlight observed from space at visible and near-infrared wavelengths, particles suspended in Earth’s atmosphere provide contrast with vegetation or dark water at the surface. This is the physical motivation for the Dark Target (DT) aerosol retrieval algorithm developed for the Moderate Resolution Imaging Spectrometer (MODIS). To extend the data record of aerosol optical depth (AOD) beyond the expected 20-year lifespan of the MODIS sensors, DT must be adapted for other sensors. A version of the DT AOD retrieval for the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-National Polar-Orbiting Partnership (SNPP) is now mature enough to be released as a standard data product, and includes some upgraded features from the MODIS version. Differences between MODIS Aqua and VIIRS SNPP lead to some inevitable disagreement between their respective AOD measurements, but the offset between the VIIRS SNPP and MODIS Aqua records is smaller than the offset between those of MODIS Aqua and MODIS Terra. The VIIRS SNPP retrieval shows good agreement with ground-based measurements. For most purposes, DT for VIIRS SNPP is consistent enough and in close enough agreement with MODIS to continue the record of satellite AOD. The reasons for the offset from MODIS Aqua, and its spatial and temporal variability, are investigated in this study.

scholarly journals Photometric Normalization of Chang’e-4 Visible and Near-Infrared Imaging Spectrometer Datasets: A Combined Study of In-Situ and Laboratory Spectral Measurements

2020 ◽  
Vol 12 (19) ◽  
pp. 3211
Author(s):  
Xiaobin Qi ◽  
Zongcheng Ling ◽  
Jiang Zhang ◽  
Jian Chen ◽  
Haijun Cao ◽  
...  
Keyword(s):  
Near Infrared ◽  
Infrared Imaging ◽  
Landing Site ◽  
Near Infrared Imaging ◽  
Imaging Spectrometer ◽  
Quantitative Mineralogy ◽  
Infrared Spectral ◽  
Phase Functions ◽  
Phase Angles

Until 29 May 2020, the Visible and Near-Infrared Imaging Spectrometer (VNIS) onboard the Yutu-2 Rover of the Chang’e-4 (CE-4) has acquired 96 high-resolution surface in-situ imaging spectra. These spectra were acquired under different illumination conditions, thus photometric normalization should be conducted to correct the introduced albedo differences before deriving the quantitative mineralogy for accurate geologic interpretations. In this study, a Lommel–Seeliger (LS) model and Hapke radiative transfer (Hapke) model were used and empirical phase functions of the LS model were derived. The values of these derived phase functions exhibit declining trends with the increase in phase angles and the opposition effect and phase reddening effect were observed. Then, we discovered from in-situ and laboratory measurements that the shadows caused by surface roughness have significant impacts on reflectance spectra and proper corrections were introduced. The validations of different phase functions showed that the maximum discrepancy at 1500 nm of spectra corrected by the LS model was less (~3.7%) than that by the Hapke model (~7.4%). This is the first time that empirical phase functions have been derived for a wavelength from 450 to 2395 nm using in-situ visible and near-infrared spectral datasets. Generally, photometrically normalized spectra exhibit smaller spectral slopes, lower FeO contents and larger optical maturity parameter (OMAT) than spectra without correction. In addition, the band centers of the 1 and 2 μm absorption features of spectra after photometric normalization exhibit a more concentrated distribution, indicating the compositional homogeneity of soils at the CE-4 landing site.

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