VIIRS on-orbit calibration and performance update

Xiong, Xiaoxiong; Butler, James J.; Chiang, K.; Efremova, Boryana; Fulbright, Jon P.; Lei, Ning; McIntire, Jeff; Wang, Zhipeng

doi:10.1109/igarss.2014.6946694

Cited by 6 publications

(2 citation statements)

References 5 publications

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“…We used Defense Meteorological Satellite Program (DMSP)/ Operational Linescan System (OLS) stable light (STL) data to depict the influences of human activities and socioeconomic factors (https://www.ngdc.noaa.gov/eog/dmsp/) with from the period 1992 to 2013 (Xiong et al, 2016;Li et al, 2019c). To ensure continuity in the lighting data, we used the NPP/VIIRS cloud mask (VCM) dataset (https://www.ngdc.noaa.gov/eog/viirs/) for the period between 2014 and 2020 (Lee et al, 2014;Zheng et al, 2020).…”

Section: Remote Sensing Datamentioning

confidence: 99%

Spatial−temporal variation of ecological environment quality and driving factors from 2000 to 2020 in Wuliangsu Lake Basin, Northern China

Li,

Chai,

et al. 2023

Front. Ecol. Evol.

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Due to global climate change and the intensification of human activities, the ecological function of Wuliangsu Lake Basin has been seriously degraded. Obtaining accurate spatial–temporal dynamics of regional ecological environment quality is essential for the evaluation of ecological management and restoration effects. This study assessed the trend changes and drivers of the Remote Sensing Ecological Index (RSEI) in the Wuliangsu Lake Basin from 2000−2020. Firstly, the trend analysis method and hurst index were used to analyze the temporal and spatial variation of RSEI. Then the main factors of RSEI variation were analyzed using meteorological data, integrated nighttime lighting data, and population density data. Overall, the RSEI shows an increasing trend from the west to the east with a rate of 0.0034 year−1 over the last 21 years. The area change of RSEI was 54.22%, 63.80% and 52.43% for 2000−2006, 2007−2013 and 2014−2020, respectively, which indicates that most areas have a stable ecological environment. However, the overall Future Improvement Trend (FIT) area of RSEI is 42.21%, mainly in Dengkou area, Urad Qianqi and central area. This indicates that the RSEI remains stable locally and shows an overall improving trend. The results of the correlation analysis showed that the areas influenced by meteorological and human factors were highly coincident, mainly in Dengkou and northern Linhe areas and Urad Qianqi. Considering the lagging effect of ecological engineering, the sustainable development status of RSEI in the western and eastern regions will maintain an improving trend in the future. Our study confirms the complex relationship between RSEI and meteorological and human activities, which is crucial for the scientific management of watershed ecosystems under the influence of anthropogenic factors.

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Section: Remote Sensing Datamentioning

confidence: 99%

Spatial−temporal variation of ecological environment quality and driving factors from 2000 to 2020 in Wuliangsu Lake Basin, Northern China

Li,

Chai,

et al. 2023

Front. Ecol. Evol.

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“…The EOS/MODIS uses a solar diffuser to realize the highest accuracy in-orbit calibration in the field of spectral imaging. However, the measurement accuracy is only 2% [23][24][25][26][27][28][29]. The on-satellite radiometric scale cannot be unified due to the random attenuation of the calibration system, such as the diffuser, the standard lamp, etc.…”

Section: Introductionmentioning

confidence: 99%

Instrument Development: Chinese Radiometric Benchmark of Reflected Solar Band Based on Space Cryogenic Absolute Radiometer

Lin

et al. 2020

Remote Sensing

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Low uncertainty and long-term stability remote data are urgently needed for researching climate and meteorology variability and trends. Meeting these requirements is difficult with in-orbit calibration accuracy due to the lack of radiometric satellite benchmark. The radiometric benchmark on the reflected solar band has been under development since 2015 to overcome the on-board traceability problem of hyperspectral remote sensing satellites. This paper introduces the development progress of the Chinese radiometric benchmark of the reflected solar band based on the Space Cryogenic Absolute Radiometer (SCAR). The goal of the SCAR is to calibrate the Earth–Moon Imaging Spectrometer (EMIS) on-satellite using the benchmark transfer chain (BTC) and to transfer the traceable radiometric scale to other remote sensors via cross-calibration. The SCAR, which is an electrical substitution absolute radiometer and works at 20 K, is used to realize highly accurate radiometry with an uncertainty level that is lower than 0.03%. The EMIS, which is used to measure the spectrum radiance on the reflected solar band, is designed to optimize the signal-to-noise ratio and polarization. The radiometric scale of the SCAR is converted and transferred to the EMIS by the BTC to improve the measurement accuracy and long-term stability. The payload of the radiometric benchmark on the reflected solar band has been under development since 2018. The investigation results provide the theoretical and experimental basis for the development of the reflected solar band benchmark payload. It is important to improve the measurement accuracy and long-term stability of space remote sensing and provide key data for climate change and earth radiation studies.

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Assessment of SNPP VIIRS VIS/NIR Radiometric Calibration Stability Using Aqua MODIS and Invariant Surface Targets

Xiong

Cao

et al. 2016

IEEE Trans. Geosci. Remote Sensing

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VIIRS on-orbit calibration and performance update

Cited by 6 publications

References 5 publications

Spatial−temporal variation of ecological environment quality and driving factors from 2000 to 2020 in Wuliangsu Lake Basin, Northern China

Spatial−temporal variation of ecological environment quality and driving factors from 2000 to 2020 in Wuliangsu Lake Basin, Northern China

Instrument Development: Chinese Radiometric Benchmark of Reflected Solar Band Based on Space Cryogenic Absolute Radiometer

Assessment of SNPP VIIRS VIS/NIR Radiometric Calibration Stability Using Aqua MODIS and Invariant Surface Targets

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