Soil moisture products acquired from passive satellite missions have been widely applied in environmental processes. A primary challenge for the use of soil moisture products from passive sensors is their reliability. It is crucial to evaluate the reliability of those products before they can be routinely used at a global scale. In this paper, we evaluated the Soil Moisture Active/Passive (SMAP) and the Advanced Microwave Scanning Radiometer (AMSR2) radiometer soil moisture products against in situ measurements collected from American networks with four statistics, including the mean difference (MD), the root mean squared difference (RMSD), the unbiased root mean square error (ubRMSE) and the correlation coefficient (R). The evaluation results of SMAP and AMSR2 soil moisture products were compared. Moreover, the triple collocation (TC) error model was used to assess the error among AMSR2, SMAP and in situ data. The monthly average and daily AMSR2 and SMAP soil moisture data were analyzed. Different spatial series, temporal series and combined spatial-temporal analysis were carried out. The results reveal that SMAP soil moisture retrievals are generally better than AMSR2 soil moisture data. The remotely sensed retrievals show the best agreement with in situ measurements over the central Great Plains and cultivated crops throughout the year. In particular, SMAP soil moisture data shows a stable pattern for capturing the spatial distribution of surface soil moisture. Further studies are required for better understanding the SMAP soil moisture product.

Accurate soil moisture retrieval of a large area in high resolution is significant for plateau pasture. The object of this paper is to investigate the estimation of volumetric soil moisture in vegetated areas of plateau pasture using fully polarimetric C-band RADARSAT-2 SAR (Synthetic Aperture Radar) images. Based on the water cloud model, Chen model, and Dubois model, we proposed two developed algorithms for soil moisture retrieval and validated their performance using experimental data. We eliminated the effect of vegetation cover by using the water cloud model and minimized the effect of soil surface roughness by solving the Dubois equations. Two experimental campaigns were conducted in the Qinghai Lake watershed, northeastern Tibetan Plateau in September 2012 and May 2013, respectively, with simultaneous satellite overpass. Compared with the developed Chen model, the predicted soil moisture given by the developed Dubois model agreed better with field measurements in terms of accuracy and stability. The RMSE, R², and RPD value of the developed Dubois model were (5.4, 0.8, 1.6) and (3.05, 0.78, 1.74) for the two experiments, respectively. Validation results indicated that the developed Dubois model, needing a minimum of prior information, satisfied the requirement for soil moisture inversion in the study region.

Lop Nur, a playa lake located on the eastern margin of Tarim Basin in northwestern China, is famous for the “Ear” feature of its salt crust, which appears in remote-sensing images. In this study, partial least squares (PLS) regression was used to estimated Lop Nur playa salt-crust properties, including total salt, Ca²⁺, Mg²⁺, Na⁺, Si²⁺, and Fe²⁺ using laboratory hyperspectral data. PLS results for laboratory-measured spectra were compared with those for resampled laboratory spectra with the same spectral resolution as Hyperion using the coefficient of determination (R²) and the ratio of standard deviation of sample chemical concentration to root mean squared error (RPD). Based on R² and RPD, the results suggest that PLS can predict Ca²⁺ using Hyperion reflectance spectra. The Ca²⁺ distribution was compared to the “Ear area” shown in a Landsat Thematic Mapper (TM) 5 image. The mean value of reflectance from visible bands for a 14 km transversal profile to the “Ear area” rings was extracted with the TM 5 image. The reflectance was used to build a correlation with Ca²⁺ content estimated with PLS using Hyperion. Results show that the correlation between Ca²⁺ content and reflectance is in accordance with the evolution of the salt lake. Ca²⁺ content variation was consistent with salt deposition. Some areas show a negative correlation between Ca²⁺ content and reflectance, indicating that there could have been a small-scale temporary runoff event under an arid environmental background. Further work is needed to determine whether these areas of small-scale runoff are due to natural (climate events) or human factors (upstream channel changes).

Lop Nur is a famous dry lake in the arid region of China. It was an important section of the ancient “Silk Road”, famous in history as the prosperous communication channel between Eastern and Western cultures. At present, there is no surface water in Lop Nur Lake basin, and on SAR (Synthetic Aperture Radar) images, it looks like an “Ear”. The objective of this paper is to interpret the Lop Nur phenomenon from the perspective of scattering mechanisms. Based on field investigation and analysis of sample properties, a two-layer scattering structure is proposed with detailed explanations of scattering mechanisms. In view of the rough surface, the MIEM (Modified Integral Equation Model) was introduced to represent air-surface scattering in Lop Nur. Then, a two-layer scattering model was developed which can describe surface scattering contribution. Using polarimetric decomposition, validations were carried out, and the RMSE (root mean square error) values for the HH and VV polarizations were found to be 1.67 dB and 1.06 dB, respectively. Furthermore, according to model parametric analysis, surface roughness was identified as an apparent reason for the “Ear” feature. In addition, the polarimetric decomposition result also showed that the volume scattering part had rich texture information and could portray the “Ear” feature exactly compared with the other two parts. It is maintained that subsurface properties, mainly generating volume scattering, can determine the surface roughness under the certain climate conditions, according to geomorphological dynamics, which can help to develop an inversion technology for Lop Nur.

In this paper, a digital elevation model (DEM) was produced for Lop Nur playa produced with the data from TanDEM-X mission. The spatial resolution is 10 m. It covers an area of 38,000 km²for orthometric height from 785 m to 900 m above sea level, which is composed of 42 interferometric synthetic aperture radar (InSAR) scenes. A least-square adjustment approach was used to reduce the systematic errors in each DEM scene. The DEM produced was validated with data from other sensors including Ice, Cloud, and land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) and aerial Structure-from-Motion (SfM) DEM. The results show that global elevation root mean square error to GLAS is 0.57 m, and the relative height error to SfM DEM in complicated terrain is 3 m. The excellent height reliability of TanDEM InSAR DEM in Lop region was proved in this paper. A reliable high-resolution basic topographic dataset for researches of Lop Nur was provided.