Abstract:A good knowledge of the quality of the satellite soil moisture products is of great importance for their application and improvement. This paper examines the performance of eight satellite-based soil moisture products, including the Soil Moisture Active Passive (SMAP) passive Level 3 (L3), the Soil Moisture and Ocean Salinity (SMOS) Centre Aval de Traitement des Données SMOS (CATDS) L3, the Japan Aerospace Exploration Agency (JAXA) Advanced Microwave Scanning Radiometer 2 (AMSR2) L3, the Land Parameter Retrieval Model (LPRM) AMSR2 L3, the European Space Agency (ESA) Climate Change Initiative (CCI) L3, the Chinese Fengyun-3B (FY3B) L2 soil moisture products at a coarse resolution of~0.25 • , and the newly released SMAP enhanced passive L3 and JAXA AMSR2 L3 soil moisture products at a medium resolution of~0.1 • . The ground soil moisture used for validation were collected from two well-calibrated and dense networks, including the Little Washita Watershed (LWW) network in the United States and the REMEDHUS network in Spain, each with different land cover. The results show that the SMAP passive soil moisture product outperformed the other products in the LWW network region, with an unbiased root mean square (ubRMSE) of 0.027 m 3 m −3 , whereas the FY3B soil moisture performed the best in the REMEDHUS network region, with an ubRMSE of 0.025 m 3 m −3 . The JAXA product performed much better at 0.25 • than at 0.1 • , but at both resolutions it underestimated soil moisture most of the time (bias < −0.05 m 3 m −3 ). The SMAP-enhanced passive soil moisture product captured the temporal variation of ground measurements well, with a correlation coefficient larger than 0.8, and was generally superior to the JAXA product. The LPRM showed much larger amplitude and temporal variation than the ground soil moisture, with a wet bias larger than 0.09 m 3 m −3 . The underestimation of surface temperature may have contributed to the general dry bias found in the SMAP (−0.018 m 3 m −3 for LWW and 0.016 m 3 m −3 for REMEDHUS) and SMOS (−0.004 m 3 m −3 for LWW and −0.012 m 3 m −3 for REMEDHUS) soil moisture products. The ESA CCI product showed satisfactory performance with acceptable error metrics (ubRMSE < 0.045 m 3 m −3 ), revealing the effectiveness of merging active and passive soil moisture products. The good performance of SMAP and FY3B demonstrates the

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The Soil Moisture Active Passive (SMAP) mission, which is the newest L-band satellite that is specifically designed for soil moisture monitoring, was launched on January 31, 2015. A beta quality version of the SMAP radiometer soil moisture product was recently released to the public. It is crucial to evaluate the reliability of this product before it can be routinely used in hydrometeorological studies at a global scale. In this paper, we carried out a preliminary evaluation of the SMAP radiometer soil moisture product against in situ measurements collected from three networks that cover different climatic and land surface conditions, including two dense networks established in the U.S. and Finland, and one sparse network set up in Romania. Results show that the SMAP soil moisture product is in good agreement with the in situ measurements, although it exhibits dry or wet bias at different network regions. It well reproduces the temporal evolution and anomalies of the observed soil moisture with a favorable correlation greater than 0.7. The overall ubRMSE (unbiased root mean square error) of SMAP product is 0.036 m 3 ·m −3 , well within the mission requirement of 0.04 m 3 ·m −3 . The error sources of SMAP soil moisture product may be associated with the parameterization of vegetation and surface roughness but still needs to be tested and confirmed in more extent. Considering that the algorithms are still under refinement, it can be reasonably expected that hydrometeorological applications will benefit from the SMAP radiometer soil moisture product.

Abstract-This paper presents a novel synthetic aperture radar (SAR) image simulation approach to target recognition, which consists of two frameworks, referred to as the satellite SAR images simulation and the target recognition and identification. The images simulation makes use of the sensor and target geo-location relative to the Earth, movement of SAR sensor, SAR system parameters, radiometric and geometric characteristics of the target, and target radar cross section (RCS), orbital parameters estimation, SAR echo signal generation and image focusing to build SAR image database. A hybrid algorithm that combines the physical optics, physical diffraction theory, and shooting and bouncing rays was used to compute the RCS of complex radar targets. Such database is vital for aided target recognition and identification system Followed by reformulating the projection kernel in an optimization equation form, the target's reflectivity field can be accurately estimated. Accordingly, the target's features can be effectively enhanced and extracted, and the dominant scattering centers are well separated. Experimental results demonstrate that the simulated database developed in this paper is well suited for target recognition. Performance is extensively tested and evaluated from real images by Radarsat-2 and TerraSAR-X. Effectiveness and efficiency of the proposed method are further confirmed.

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Abstract-In this paper, we study the bistatic reflection and transmission properties of random rough surface with large slope and large height. Method of Moment (MOM) is used to solve the surface integral equations for 2D rough surface scattering problem. The modeled rough surfaces are similar to random rectangular grating, so that there are large slopes on the surface. The motivation of the study is to analyze scattering by sastrugi surface in Polar Regions. The ridges on the sastrugi surface have heights of about 20 cm. In microwave remote sensing of land at 5 GHz, 10 GHz, 19 GHz and 37 GHz, these heights are larger than wavelength. Next, we consider the scattering problem of the sastrugi rough surface over multilayered snow. The bistatic reflection and transmission coefficients from MOM solutions are used as the boundary conditions for multilayered radiative transfer equations. The radiative transfer equations are solved and the reflectivities are calculated. Numerical results are illustrated as a function of roughness and multi-layered parameters. We demonstrate that rough surface of sastugi, when interactions with layered media, causes increase in reflectivity and the decrease in emissivity. The increase of reflectivity can be attributed to the fact that rough surface with large slope facilitates large angle transmission. The large angle transmission results in increase of subsurface reflection and the possibility of total internal reflection in layered media below the rough surface.

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