MODIS and VIIRS Calibration History and Future Outlook

Xiong, Xiaoxiong; Butler, James J.

doi:10.3390/rs12162523

Cited by 44 publications

(26 citation statements)

References 67 publications

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“…This is to simulate a case when the scattering optical thicknesses at 468 and 642 nm are known from the retrieval using observed imager/spectrometer observations. The 3% uncertainty is based on the calibration accuracy of a MODIS-like imager (Butler et al, 2003;Xiong and Butler 2020). We ignore the uncertainty associated with retrieving aerosol optical thickness.…”

Section: Desert Aerosolsmentioning

confidence: 99%

Effect of Spectral Variability of Aerosol Optical Properties on Direct Aerosol Radiative Effect

Kato¹,

Thorsen²,

Ham³

et al. 2022

Front. Remote Sens.

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Aerosol optical properties depend on wavelength as well as both mixing ratios and size distributions of components that make up a particular type of aerosol. This study examines impacts on direct aerosol radiative effect (DARE) for desert, clean maritime, and polluted maritime aerosol types over the ocean when their optical properties are determined by various combinations of observations made by active (i.e., lidar) and passive (e.g., shortwave spectrometer) satellite sensors. Spectral optical properties are perturbed by altering mixing ratios of components that define aerosol types with assumptions that components within an aerosol type are fixed and only one aerosol type is present in the atmosphere. When 532 nm depolarization ratio from the lidar is used to identify desert aerosol, the uncertainty in the mean DARE due to spectral optical property variabilities is 10%. When the 532 nm depolarization and lidar ratios are used to identify clean and polluted maritime aerosols, uncertainties in mean DARE are, respectively, 4 and 18%. When scattering optical thicknesses are also known to within ± 3% at four passive imager wavelengths (340 nm, 546 nm, 966 nm, and 1,657 nm), uncertainty in the polluted maritime DARE decreases to 8%. Uncertainties in the instantaneous top-of-atmosphere (TOA) reflected irradiances derived from observed broadband radiances and angular distribution models are also estimated. When TOA irradiances are derived solely from the nadir view, their uncertainties can be reduced if aerosol type can be identified and aerosol type dependence is considered in the radiance to irradiance conversion. This is especially so for aerosols with a large fraction of nonspherical particles, such as desert aerosols.

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Section: Desert Aerosolsmentioning

confidence: 99%

Effect of Spectral Variability of Aerosol Optical Properties on Direct Aerosol Radiative Effect

Kato¹,

Thorsen²,

Ham³

et al. 2022

Front. Remote Sens.

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“…Because both MODIS and ASTER data are freely available, readers can easily reproduce our results. The radiometric calibration uncertainty (sensor requirement) for MODIS thermal bands for surface temperature measurement (i.e., bands 31 and 32) is ± 0.5% in radiance [ 30 ]. That for ASTER is ± 1 K or better in brightness temperature, for the range of 270–340 K (i.e., ~ ± 0.3%) [ 31 ].…”

Section: Introductionmentioning

confidence: 99%

Thermal remote sensing over heterogeneous urban and suburban landscapes using sensor-driven super-resolution

2022

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Thermal remote sensing is an important tool for monitoring regional climate and environment, including urban heat islands. However, it suffers from a relatively lower spatial resolution compared to optical remote sensing. To improve the spatial resolution, various “data-driven” image processing techniques (pan-sharpening, kernel-driven methods, and machine learning) have been developed in the previous decades. Such empirical super-resolution methods create visually appealing thermal images; however, they may sacrifice radiometric consistency because they are not necessarily sensitive to specific sensor features. In this paper, we evaluated a “sensor-driven” super-resolution approach that explicitly considers the sensor blurring process, to ensure radiometric consistency with the original thermal image during high-resolution thermal image retrieval. The sensor-driven algorithm was applied to a cloud-free Moderate Resolution Imaging Spectroradiometer (MODIS) scene of heterogeneous urban and suburban landscape that included built-up areas, low mountains with a forest, a lake, croplands, and river channels. Validation against the reference high-resolution thermal image obtained by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) shows that the sensor-driven algorithm can downscale the MODIS image to 250-m resolution, while maintaining a high statistical consistency with the original MODIS and ASTER images. Part of our algorithm, such as radiometric offset correction based on the Mahalanobis distance, may be integrated with other existing approaches in the future.

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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 History and Future Outlook

Cited by 44 publications

References 67 publications

Effect of Spectral Variability of Aerosol Optical Properties on Direct Aerosol Radiative Effect

Effect of Spectral Variability of Aerosol Optical Properties on Direct Aerosol Radiative Effect

Thermal remote sensing over heterogeneous urban and suburban landscapes using sensor-driven super-resolution

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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