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Special Issue "Remote Sensing Calibration and Validation in Sounding Atmosphere and Ionosphere"

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: 30 June 2023 | Viewed by 2097

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Special Issue Editors

Prof. Dr. Yajun Zhu

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Guest Editor

State Key Laboratory of Space Weather, University of Chinese Academy of Sciences, Beijing, China
Interests: remote sensing; data processing; airglow

Prof. Dr. Weihua Bai

E-Mail Website
Guest Editor

State Key Laboratory of Space Weather, University of Chinese Academy of Sciences, Beijing, China
Interests: GNSS remote sensing GNSS occultation; GNSS-R technique and application

Prof. Dr. Jiyao Xu
E-Mail Website
Guest Editor

State Key Laboratory of Space Weather, University of Chinese Academy of Sciences, Beijing, China
Interests: atmospheric remote sensing

Special Issue Information

Dear Colleagues,

A variety of remote sensing techniques have been adopted to detect the atmosphere and ionosphere for the purpose of studying the characteristics of dynamics and photochemistry in the region, such as radars, lidars, GNSS radio occultations, and airglow observation techniques, etc. Each remote sensing technique has its own unique advantages as well as shortcomings in deriving the atmospheric and ionospheric parameters. Therefore, the calibration and validation of the instruments based on these remote sensing techniques play essential roles in the research on the atmosphere and ionosphere.

This Special Issue aims to collect papers with new results of diverse aspects of remote sensing techniques in the sounding of the atmosphere and ionosphere, including the development of active and passive optical and radio instruments, GNSS radio occultation (GNSS-RO) and reflectometry (GNSS-R) techniques, calibration and validation, comparison and application of datasets, and new retrieval methods, etc.

Potential topics for this Special Issue include, but are not limited to:

GNSS RO atmospheric datasets calibration, validation, comparison and application
GNSS-R datasets calibration, validation, comparison and application
Development of new and advanced active and passive optical and radio instruments
Calibration, validation, comparison and application of datasets from active and passive optical and radio instruments
Study of retrieval methods

Prof. Dr. Yajun Zhu
Prof. Dr. Weihua Bai
Prof. Dr. Jiyao Xu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

GNSS-RO
GNSS-R
radar
lidar
airglow
data processing
calibration
validation

Published Papers (3 papers)

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Open AccessTechnical Note

Mitigation of Calibration Ringing in the Context of the MTG-S IRS Instrument

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Remote Sens. 2023, 15(11), 2873; https://doi.org/10.3390/rs15112873 - 31 May 2023

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Abstract

EUMETSAT is currently developing the on-ground processing chain of the infrared sounders (IRS) on-board the Meteosat third-generation sounding satellites (MTG-S). In this context, the authors investigated the impact of a particular type of radiometric error, called hereafter calibration ringing. It arises in Fourier transform spectrometers when the instrument’s radiometric transfer function (RTF) varies within the domain of the instrument’s spectral response function (SRF). The expected radiometric errors were simulated in the context of the MTG-S IRS instrument in the long-wave infrared (LWIR) band. Making use of a principal components (PCs) decomposition, a software correction, called RTF uniformisation, was designed and its performance was assessed in the context of MTG-S IRS. Full article

(This article belongs to the Special Issue Remote Sensing Calibration and Validation in Sounding Atmosphere and Ionosphere)

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Open AccessTechnical Note

An Efficient Calibration System of Optical Interferometer for Measuring Middle and Upper Atmospheric Wind

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Remote Sens. 2023, 15(7), 1898; https://doi.org/10.3390/rs15071898 - 31 Mar 2023

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Abstract

Detection of the Doppler shift of airglow radiation in the middle and upper atmosphere is one of the most important methods for remote sensing of the atmospheric wind field. Laboratory and routine field calibration of an optical interferometer for wind measurement is very important. We report a novel calibration system that simulates a frequency shift of airglow emission lines introduced by wind in the middle and upper atmosphere for calibrating passive optical interferometers. The generator avoids the shortcomings of traditional motor-driven Doppler-shift generators in terms of stability and security while improving accuracy and simplifying assemblies. A simulated wind speed can be determined simultaneously using the light-beat method. The wind error simulated by the generator mainly comes from the light source, which is about 0.63 m/s. An experimental demonstration was conducted using a calibrated Fabry–Perot interferometer and showed that the root mean square of the measurement uncertainty is 0.91 m/s. The novel calibration system was applied to calibrate an asymmetric spatial heterodyne spectrometer (ASHS)-type interferometer successfully. The results demonstrate the feasibility of the system. Full article

(This article belongs to the Special Issue Remote Sensing Calibration and Validation in Sounding Atmosphere and Ionosphere)

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Open AccessTechnical Note

Soil Moisture Retrieval from Multi-GNSS Reflectometry on FY-3E GNOS-II by Land Cover Classification

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Remote Sens. 2023, 15(4), 1097; https://doi.org/10.3390/rs15041097 - 17 Feb 2023

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Abstract

The reflected GNSS signals at the L-band is significantly advantageous in soil moisture monitoring as they are sensitive to the dielectric properties determined by the volumetric water content of topsoil, and they can penetrate vegetation, except in very dense forests. The Global Navigation satellite system Occultation Sounder (GNOS-II) with a reflectometry technique onboard the Fengyun-3E (FY-3E) satellite, launched on 5 July 2021, is the first mission that can receive reflected Global Navigation Satellite System (GNSS) signals from GPS, BeiDou and Galileo systems. This paper presents the soil moisture retrieval results from the FY-3E GNOS-II mission using 16 months of data. In this study, the reflectivity observations from different GNSS systems were firstly intercalibrated with some differences analyzed. Observations were also corrected by considering vegetation attenuation for 16 different land cover classifications. Finally, an empirical model was constructed for volumetric soil moisture (VSM) estimation, where the reflectivity of GNOS-II was linearly related to the SMAP reference soil moisture for each 36 km ease grid. The overall root-mean-square error of the retrieved soil moisture is 0.049 compared with the SMAP product, and 0.054 compared with the in situ data. The results of the three GNSS systems show similar levels of accuracy. This paper, for the first time, demonstrates the feasibility of global soil moisture retrieval using multiple GNSS signals. Full article

(This article belongs to the Special Issue Remote Sensing Calibration and Validation in Sounding Atmosphere and Ionosphere)

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Special Issue "Remote Sensing Calibration and Validation in Sounding Atmosphere and Ionosphere"

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