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Soil moisture saturation index (SMSI) is an important indicator that demonstrates the status of the soil water content for drought monitoring. However, at present, most of the methods to calculate the SMSI from the in situ measurement data are inadequate or inaccurate. This paper proposed a simple method to determine the SMSI from the remotely sensed data. Combining the theory of thermal inertia and triangle method, the apparent thermal inertia and fractional vegetation cover can construct a triangular space. In this space, SMSI can be determined easily. Validation was performed with in situ measurements for 19 meteorological stations in the study area. Results indicated that the method can obtain the accurate soil water status that reflects the variation in soil moisture to some extent and is suitable for monitoring the regional surface soil moisture.

Land surface temperature and emissivity separation is a critical process for land surface temperature (LST) retrieval from hyperspectral thermal infrared data. This paper compared the iterative spectrally smooth temperature/emissivity separation (ISSTES) and the correlation based temperature/emissivity separation (CBTES) methods for land surface temperature and emissivities retrievals from simulated data under typical atmospheres and different land surface covers. The paper also compared both methods for retrieving low emissivities with simulated data. For typical land cover types, neglecting the instrumental noise, ISSTES is more accurate than CBTES with root mean square error (RMSE) of LSTs less than 0.0005K for the ISSTES and 0.1K for the CBTES. For low emissivity material, considering instrumental noise, both methods have large errors, but the CBTES performs much better.

The total atmospheric precipitable water vapor amount (TWV) is a key variable for the study of the Earth's climate. This paper develops an algorithm to estimate the TWV over clear skies from the Medium Resolution Spectral Imager (MERSI) data in the near-IR channels. The MODTRAN 4 code is used to simulate the top of the atmospheric radiances for the MERSI channels. The results show that the proposed algorithm is suitable to estimate TWV form the absorbing channel centered at 0.940 µm and the atmospheric window channels centered at 0.865 µm and centered at 1.030 µm by the radiances over the clear pixels, with relative differences in the range of 10%–15%.

To evaluate the radiometric characteristics of the thermal infrared channels of Visible and InfraRed Radiometer (VIRR) aboard Chinese second generation polar-orbiting meteorological satellite FengYun-3B (FY-3B), the inter-calibration of those thermal infrared channels with high spectral resolution data acquired by the Atmospheric InfraRed Sounder (AIRS) aboard Aqua is carried out in this paper. Four steps, i.e. subsetting, collocating, transforming and regressing, were used to calculate the inter-calibration coefficients. The collocation data were picked out with a series of thresholds: the absolute viewing zenith angle differences less than 10°, the absolute viewing azimuth angle differences less than 20°, and absolute time differences less than 40 minute. The results on June 1st, 2012 reveal that the VIRR/FY-3B measurements are highly linearly related to the convolved AIRS/Aqua measurements. However, calibration discrepancies exist between VIRR and AIRS channels. When brightness temperatures in VIRR channels change from 270 K to 300 K under a normal condition, the AIRS-VIRR temperature adjustment linearly varies from -0.79 K to -2.32K for VIRR channel 4, from 0.14 K to -1.42 K for VIRR channel 5, respectively.

Land surface temperature (LST) is a critical parameter for numerical weather forecasting, drought monitoring, water resources management and global climate change studies. Because of the supercooled temperature, the cirrus cloud can significantly reduce the LST retrieved from thermal infrared data. This paper focused on analyzing and reducing the influence of thin cirrus cloud on the accuracy of LST retrieved using the generalized split-window (GSW) algorithm. A correction method was proposed with the LST retrieval error expressed as linear functions of cirrus optical depth (COD). The slopes of the linear functions were further written as the combination of the difference and mean of two used channels emissivities and cirrus cloud top height (CTH). The results showed that the LST retrieval accuracy could be significantly improved with root mean square error (RMSE) of LST changing from 14.4 K before LST error correction to 1.8 K after LST error correction for COD equivalent to 0.3.

Soil moisture is a key variable that influences the redistribution of the radiant energy and the runoff generation and percolation of water in soil. Knowledge of soil moisture temporal-spatial variations is important in a wide range of studies. This study aims to investigate the temporal-spatial variations of soil moisture using microwave polarization difference index (MPDI). The AMSR-E/Aqua Daily Global Quarter-Degree Gridded Brightness Temperature at 10.65 GHz channel was used to calculate the MPDI. In addition, the AMSR-E/Aqua Daily L3 Surface Soil Moisture was used in this study. The temporal and spatial patterns between the MPDI and soil moisture were analyzed. The results indicate that the temporal and spatial patterns of the MPDI are consistent with those of soil moisture. The MPDI reflects the temporal and spatial variations of soil moisture.