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17 pages, 9469 KiB  
Article
Preflight Spectral Calibration of the Ozone Monitoring Suite-Nadir on FengYun 3F Satellite
by Qian Wang, Yongmei Wang, Na Xu, Jinghua Mao, Ling Sun, Entao Shi, Xiuqing Hu, Lin Chen, Zhongdong Yang, Fuqi Si, Jianguo Liu and Peng Zhang
Remote Sens. 2024, 16(9), 1538; https://doi.org/10.3390/rs16091538 - 26 Apr 2024
Cited by 1 | Viewed by 981
Abstract
The Ozone Monitoring Suite-Nadir (OMS-N) instrument is the first hyperspectral remote sensor in the ultraviolet band of China’s Fengyun series satellites. It can be used to detect several kinds of atmospheric constituents. This paper describes the prelaunch spectral calibration of the OMS-N onboard [...] Read more.
The Ozone Monitoring Suite-Nadir (OMS-N) instrument is the first hyperspectral remote sensor in the ultraviolet band of China’s Fengyun series satellites. It can be used to detect several kinds of atmospheric constituents. This paper describes the prelaunch spectral calibration of the OMS-N onboard FengYun 3F. Several critical spectral parameters including the spectral resolution, spectral dispersion, and the instrument spectral response function were determined through laser-based measurements. A secondary peak of the instrument spectral response function from the short wavelength side of the ultraviolet band was found, and the possible influence on data applications was analyzed using a reference solar model and radiative transfer model. The results indicate that the spectral resolution and spectral accuracy of OMS-N meet the mission requirements. However, the asymmetries in the instrument spectral response function in the ultraviolet band were found near nadir rows, which are expressed as the “asymmetric central peak” and “secondary peak”. The analysis results show that if the influences of the instrument spectral response function “asymmetric central peak” and “secondary peak” in the ultraviolet band are ignored, they will bring an error as large as 5% at the center of the absorption line. Full article
(This article belongs to the Section Atmospheric Remote Sensing)
Show Figures

Figure 1

Figure 1
<p>Observation schematic view of the FY-3F OMS-N instrument.</p>
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<p>Schematic diagram of OMS-N spectral calibration.</p>
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<p>Flowchart of the data processing procedure of OMS-N spectral calibration.</p>
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<p>Response from a set of 11 spectral pixels (different colors) in the VIS band. (<b>a</b>) Row 30; (<b>b</b>) row 115; (<b>c</b>) row 204.</p>
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<p>Response from a set of 11 spectral pixels (different colors) in the UV1 band. (<b>a</b>) Row 9; (<b>b</b>) row 29 (the nadir row); (<b>c</b>) row 52.</p>
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<p>The “asymmetric central peak” and “secondary peak” characterization of the ISRF for the nadir row in the UV1 band. (<b>a</b>) Wavelength centroid around 296.6 nm; (<b>b</b>) wavelength centroid around 282.3 nm; (<b>c</b>) wavelength centroid around 270.8 nm; (<b>d</b>) wavelength centroid around 254.9 nm.</p>
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<p>The ISRF difference in the VIS band between the center (column 285) and the others (columns 280–290). The different dots donate the ISRF differences in different columns. (<b>a</b>) Row 30; (<b>b</b>) row 115; (<b>c</b>) row 204.</p>
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<p>The ISRF difference in the UV1 band between the center (column 568) and the others (columns 563–573). The different dots donate the ISRF differences in different columns. (<b>a</b>) Row 9; (<b>b</b>) row 29; (<b>c</b>) row 52.</p>
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<p>Samples from 11 spectral pixels in the VIS band are combined to give a single set of data, with a higher resolution shown by the colored circles. (<b>a</b>) Row 30; (<b>b</b>) row 119; (<b>c</b>) row 204.</p>
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<p>Combined ISRF spectral sample data (blue circle) and the fitted ISRF (red line) at row 204, column 285 in the VIS band.</p>
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<p>Samples from 11 spectral pixels in the UV1 band are combined to give a single set of data, with a higher resolution shown by the colored circles. (<b>a</b>) Row 9; (<b>b</b>) row 29; (<b>c</b>) row 52.</p>
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<p>Combined ISRF spectral sample data (blue circle) and the fitted ISRF (red line) at row 29, column 568 in the UV1 band.</p>
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<p>The ISRF in the UV2 band for row 119, column 150.</p>
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<p>Polynomial fits residuals of the spectral dispersion coefficients of second order (blue), third order (red), fourth order (yellow), and fifth order (purple). (<b>a</b>) UV1 band; (<b>b</b>) UV2 band; (<b>c</b>) VIS band.</p>
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<p>Fifth-order polynomial fits (red line) for nadir row wavelength centroids derived from (blue dots) laser data as a function of the spectral pixel index. (<b>a</b>) UV1 band; (<b>b</b>) UV2 band; (<b>c</b>) VIS band.</p>
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<p>OMS-N response to the standard spectral lamp, and the red rectangle shows the selected standard spectral line. (<b>a</b>) UV band; (<b>b</b>) VIS band.</p>
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<p>Histogram of the response ratio distribution of the ISRF “secondary peak” for all affected pixels in the UV1 band.</p>
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<p>An example of the measured ISRF (blue lines) and the testing ISRF (red lines) in the UV1 band. (<b>a</b>) Short wavelength; (<b>b</b>) middle wavelength; (<b>c</b>) long wavelength.</p>
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<p>The simulated irradiance spectra from OMS-N measured the ISRF (red line) and the testing ISRF (light blue line) and their relative irradiance difference. (<b>a</b>) Simulated irradiance spectra; (<b>b</b>) relative irradiance difference between simulation from the measured ISRF and the testing ISRF.</p>
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<p>The simulated spectra at 250–300 nm on water surface and ice surfaces.</p>
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<p>The consistency of radiance difference (between the measured ISRF and the testing ISRF) on snow and water surfaces. (<b>a</b>) The radiance difference in the spectral domain; (<b>b</b>) the histogram of the relative radiance difference on snow and water surfaces.</p>
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28 pages, 8697 KiB  
Article
Efficient Privacy-Aware Forwarding for Enhanced Communication Privacy in Opportunistic Mobile Social Networks
by Azizah Assiri and Hassen Sallay
Future Internet 2024, 16(2), 48; https://doi.org/10.3390/fi16020048 - 31 Jan 2024
Viewed by 1652
Abstract
Opportunistic mobile social networks (OMSNs) have become increasingly popular in recent years due to the rise of social media and smartphones. However, message forwarding and sharing social information through intermediary nodes on OMSNs raises privacy concerns as personal data and activities become more [...] Read more.
Opportunistic mobile social networks (OMSNs) have become increasingly popular in recent years due to the rise of social media and smartphones. However, message forwarding and sharing social information through intermediary nodes on OMSNs raises privacy concerns as personal data and activities become more exposed. Therefore, maintaining privacy without limiting efficient social interaction is a challenging task. This paper addresses this specific problem of safeguarding user privacy during message forwarding by integrating a privacy layer on the state-of-the-art OMSN routing decision models that empowers users to control their message dissemination. Mainly, we present three user-centric privacy-aware forwarding modes guiding the selection of the next hop in the forwarding path based on social metrics such as common friends and exchanged messages between OMSN nodes. More specifically, we define different social relationship strengths approximating real-world scenarios (familiar, weak tie, stranger) and trust thresholds to give users choices on trust levels for different social contexts and guide the routing decisions. We evaluate the privacy enhancement and network performance through extensive simulations using ONE simulator for several routing schemes (Epidemic, Prophet, and Spray and Wait) and different movement models (random way, bus, and working day). We demonstrate that our modes can enhance privacy by up to 45% in various network scenarios, as measured by the reduction in the likelihood of unintended message propagation, while keeping the message-delivery process effective and efficient. Full article
(This article belongs to the Special Issue Information and Future Internet Security, Trust and Privacy II)
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Figure 1

Figure 1
<p>System model overview.</p>
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<p>Privacy modes’ flowcharts (<b>a</b>) for the trust threshold-based mode, (<b>b</b>) for stranger then familiar selection mode, and (<b>c</b>) for familiar then stranger selection mode.</p>
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<p>The result of trust threshold 30% and random way movement model.</p>
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<p>The result of trust threshold 30% and the bus movement model.</p>
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<p>The result of trust thresholds 30% and working day movement model.</p>
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<p>The results of thresholds 50% and random way model.</p>
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<p>The result of thresholds 50 and bus model.</p>
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<p>The result of thresholds 50 and working day.</p>
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<p>The result of thresholds 80% and the random way model.</p>
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<p>The result of thresholds 80 and bus model.</p>
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<p>The result of thresholds 80% and the working day model.</p>
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<p>The result of stranger mode with random way model.</p>
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<p>The result of stranger mode with bus model.</p>
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<p>The result of stranger mode with working day model.</p>
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<p>The result of familiar mode with the random way model.</p>
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<p>The result of familiar mode with bus model.</p>
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<p>The result of familiar mode with working day model.</p>
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<p>The result of the data collection process in the random way model.</p>
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<p>The result of the data collection process with the bus model.</p>
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<p>The result data collection process with the working day model.</p>
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13 pages, 4660 KiB  
Communication
Pre-Launch Multi-Energy Radiance Calibration of the OMS-N
by Jinghua Mao, Yongmei Wang, Entao Shi, Xiuqing Hu, Qian Wang and Jinduo Wang
Remote Sens. 2024, 16(1), 119; https://doi.org/10.3390/rs16010119 - 27 Dec 2023
Cited by 3 | Viewed by 893
Abstract
This paper presents the prelaunch radiometric calibration of the Ozone Monitor Suite-Nadir (OMS-N) instrument, a vital payload on the FY-3F satellite. FY-3F achieved a successful launch on 3 August 2023. The radiance calibration of the OMS-N instrument was achieved using an integrating sphere, [...] Read more.
This paper presents the prelaunch radiometric calibration of the Ozone Monitor Suite-Nadir (OMS-N) instrument, a vital payload on the FY-3F satellite. FY-3F achieved a successful launch on 3 August 2023. The radiance calibration of the OMS-N instrument was achieved using an integrating sphere, with known exit radiance ascertained through a transferring radiometer. The calibration model incorporates six energy levels. The Solar Simulator Standard System was employed to validate the calibration results, selecting specific rows to represent varying spatial dimensions. Considering the influence of xenon lamp characteristic peaks and transmission errors during the calibration process, the average deviation remained within 2.3% for the VIS channel, 3% for the UV1 channel, and 2.2% for the UV2 channel. Furthermore, the uncertainty of the radiometric calibration was analyzed. The results indicated an absolute uncertainty of 2.33% for both the UV1 and UV2 channels and 1.69% for the VIS channel. The relative uncertainty was 1.84% for both the UV1 and UV2 channels and 1.45% for the VIS channel. The obtained calibration coefficients are accurate and reliable and can be used for the inversion of product parameters, which is of great significance to the quantitative application of satellite data and the advancement of scientific research on quantitative remote sensing. Full article
(This article belongs to the Section Remote Sensing Communications)
Show Figures

Figure 1

Figure 1
<p>Functional schematic of the OMS-N.</p>
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<p>The distribution of the six energy levels of the labsphere. (<b>a</b>) Six energy levels of the xenon lamp source used for calibrating radiation in the UV1 and UV2 channels; (<b>b</b>) six energy levels of the tungsten lamp sources used for calibrating radiation in the VIS channels.</p>
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<p>The radiance calibration schematic of OMS-N.</p>
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<p>Signal map of the OMS-N CCD after splicing the three channels. A complete DN map spliced from multiple angles under one light source condition, with the horizontal and vertical coordinates representing the spatial and spectral dimensions of the CCD, respectively.</p>
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<p>Distribution of fitting coefficients for full pixel radiance calibration. OMS-N irradiance responsivity fitted using Equation (1). Using DN maps of different sources combined with the standard irradiance of the sources, Rn represents the fitting coefficients, with one coefficient for each of the different pixels. Final irradiance coefficients with the same distribution matrices as those of the detector pixels. (<b>a</b>–<b>c</b>) Coefficients fitted for the different channels.</p>
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<p>Residuals of the fit for one of the pixels of the different channels.</p>
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<p>Radiance distribution in the infra-stellar field of view, obtained through OMS-N calculations and radiometry.</p>
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<p>Comparative distribution of multi-field calibration errors.</p>
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<p>Variation of relative accuracy with wavelength.</p>
Full article ">Figure 9 Cont.
<p>Variation of relative accuracy with wavelength.</p>
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