MODIS and VIIRS Calibration and Characterization in Support of Producing Long-Term High-Quality Data Products

Xiong, Xiaoxiong; Angal, Amit; Chang, Tiejun; Chiang, K.; Lei, Ning; Li, Yonghong; Sun, Junqiang; Twedt, Kevin A.; Wu, Aisheng

doi:10.3390/rs12193167

Cited by 47 publications

(30 citation statements)

References 72 publications

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“…Additionally, the calibration difference in the specific referenced sensor onboard different platforms also contributes to the uncertainty of EPIC calibration. The calibration differences between MODIS Aqua and Terra for RSB are within 1.5% (Xiong et al, 2020), but MODIS/ Aqua-based EPIC calibration coefficients at 780 nm is 2% lower than that derived from MODIS/Terra (Geogdzhayev et al, 2021). The calibration coefficients for VIIRS/S-NPP at RSB are lower than that of VIIRS/NOAA-20 by 3-7% (Xiong et al, 2020).…”

Section: Data Epic L1bmentioning

confidence: 75%

“…The calibration differences between MODIS Aqua and Terra for RSB are within 1.5% (Xiong et al, 2020), but MODIS/ Aqua-based EPIC calibration coefficients at 780 nm is 2% lower than that derived from MODIS/Terra (Geogdzhayev et al, 2021). The calibration coefficients for VIIRS/S-NPP at RSB are lower than that of VIIRS/NOAA-20 by 3-7% (Xiong et al, 2020). The MODIS-based EPIC calibration by Doelling et al (2019) agrees with Geogdzhayev and Marshak (2018) within 1.6% and Geogdzhayev et al (2021) within 2.6%.…”

Section: Data Epic L1bmentioning

confidence: 79%

“…The MODIS-based EPIC calibration by Doelling et al (2019) agrees with Geogdzhayev and Marshak (2018) within 1.6% and Geogdzhayev et al (2021) within 2.6%. Overall, the uncertainty of EPIC calibration using MODIS or VIIRS data as references can be up to 8.5% as we analyzed above, with 7% attributable to the satellite data used as reference (Sayer et al, 2017;Xiong et al, 2020) and at least 1.5% attributable to the calibration process itself.…”

Section: Data Epic L1bmentioning

confidence: 87%

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Hourly Mapping of the Layer Height of Thick Smoke Plumes Over the Western U.S. in 2020 Severe Fire Season

Wang

et al. 2021

Front. Remote Sens.

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A series of huge smoke plume events from the largest wildfire season recorded in California’s modern history has occurred in 2020. Here, a research algorithm was modified to retrieve the aerosol optical centroid height (AOCH) and aerosol optical depth (AOD) from Earth Polychromatic Imaging Camera (EPIC) measurements. The research focus is to gain insights of the algorithm’s feasibility in heavy smoke conditions to study the diurnal variation of AOCH; this is only made possible via EPIC due to its unique position at Lagrange-1 point and its equipment of O2 B-band at which the vegetated surface reflectance is low. Vicarious calibration is applied to the EPIC 443, 680 and 688 nm channels based on the Tropospheric Monitoring Instrument (TROPOMI) observation. This new calibration leads to a better agreement of AOCH values between EPIC retrievals and the counterparts derived from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol extinction vertical profile. The hourly variation of AOCH up to 0.45 km on September 7 is shown to have important implications for estimating hourly change of surface PM2.5, although more quantitative studies are needed in the future.

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Section: Data Epic L1bmentioning

confidence: 75%

Section: Data Epic L1bmentioning

confidence: 79%

Section: Data Epic L1bmentioning

confidence: 87%

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Hourly Mapping of the Layer Height of Thick Smoke Plumes Over the Western U.S. in 2020 Severe Fire Season

Wang

et al. 2021

Front. Remote Sens.

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“…As typical satellites in the world, Aqua/MODIS and NPP/VIIRS both have high calibration uncertainty. MODIS is an internationally recognized remote sensor for cross calibration that has high calibration accuracy, and its onboard calibration uncertainty is 2% [ 35 ]. The VIIRS calibration uncertainty is comparable to that of MODIS.…”

Section: Comparison and Analysismentioning

confidence: 99%

Vicarious Radiometric Calibration of Ocean Color Bands for FY-3D/MERSI-II at Lake Qinghai, China

Chen

Zheng

et al. 2020

Sensors

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To calibrate the low signal response of the ocean color (OC) bands and test the stability of the Fengyun-3D (FY-3D)/Medium Resolution Spectral Imager II (MERSI-II), an absolute radiometric calibration field test of FY-3D/MERSI-II at the Lake Qinghai Radiometric Calibration Site (RCS) was carried out in August 2018. The lake surface and atmospheric parameters were mainly measured by advanced observation instruments, and the MODerate spectral resolution atmospheric TRANsmittance algorithm and computer model (MODTRAN4.0) was used to simulate the multiple scattering radiance value at the altitude of the sensor. The results showed that the relative deviations between bands 9 and 12 are within 5.0%, while the relative deviations of bands 8, and 13 are 17.1%, and 12.0%, respectively. The precision of the calibration method was verified by calibrating the Aqua/Moderate-resolution Imaging Spectroradiometer (MODIS) and National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer (VIIRS), and the deviation of the calibration results was evaluated with the results of the Dunhuang RCS calibration and lunar calibration. The results showed that the relative deviations of NPP/VIIRS were within 7.0%, and the relative deviations of Aqua/MODIS were within 4.1% from 400 nm to 600 nm. The comparisons of three on-orbit calibration methods indicated that band 8 exhibited a large attenuation after launch and the calibration results had good consistency at the other bands except for band 13. The uncertainty value of the whole calibration system was approximately 6.3%, and the uncertainty brought by the field surface measurement reached 5.4%, which might be the main reason for the relatively large deviation of band 13. This study verifies the feasibility of the vicarious calibration method at the Lake Qinghai RCS and provides the basis and reference for the subsequent on-orbit calibration of FY-3D/MERSI-II.

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“…Although the spatial resolution is highly consistent with Landsat, the revisit time is reduced to 5 days. MODIS (Moderate Resolution Imaging Spectroradiometer) images which 1-day frequency can reflect the change of vegetation greenness in a highly dynamic riverbed, but their coarse spatial resolution provides a sub-optimal representation of the instantaneous distribution of vegetation greenness, especially in flat landscapes with complex riverbed networks [30][31][32][33]. The NDVI is widely used all over the world for characterizing vegetation greenness, vigour and biomass [34].…”

Section: Introductionmentioning

confidence: 99%

Using MODIS-NDVI Time Series to Quantify the Vegetation Responses to River Hydro-Geomorphology in the Wandering River Floodplain in an Arid Region

Ablat

Liu

et al. 2021

Water

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Vegetation, hydrology and geomorphology are three major elements of the floodplain ecosystem on Earth. Although the normalized difference vegetation index (NDVI) has been used extensively to characterize floodplain vegetation growth, vigour and biomass, methods for quantifying the various distinct responses of floodplain vegetation to hydro-geomorphological changes in different lateral belts in arid regions are still needed. In this study, the Linhe reach was divided into four lateral belts based on their hydro-geomorphological characteristics, and the Moderate Resolution Imaging Spectroradiometer (MODIS)-NDVI time series statistical indicators were used to characterise the distinct changing the patterns of vegetation growth in different belts. The response of floodplain vegetation to river hydro-geomorphology in each belt was analysed. The result showed that the average maximum NDVI value in the regular inundation area was 0.23 and higher than that in the other lateral belts. The correlation between the water persistence time and peak NDVI value in the regular water inundation area was significant (ρ = 0.84), indicating that in contrast to highly frequent or extremely rare water inundation, regular water inundation provides significant benefits to floodplains. Continuous or highly frequent inundation may cause decreased vegetation productivity. Overall, our results suggest that the vegetation greenness response to the river hydro-geomorphology is different from the river to the edge of the floodplain. Thus, a better understanding of the interactions between the floodplain vegetation and river hydro-morphology and river water resource management in arid-region floodplains.

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MODIS and VIIRS Calibration and Characterization in Support of Producing Long-Term High-Quality Data Products

Cited by 47 publications

References 72 publications

Hourly Mapping of the Layer Height of Thick Smoke Plumes Over the Western U.S. in 2020 Severe Fire Season

Hourly Mapping of the Layer Height of Thick Smoke Plumes Over the Western U.S. in 2020 Severe Fire Season

Vicarious Radiometric Calibration of Ocean Color Bands for FY-3D/MERSI-II at Lake Qinghai, China

Using MODIS-NDVI Time Series to Quantify the Vegetation Responses to River Hydro-Geomorphology in the Wandering River Floodplain in an Arid Region

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