Due to the lack of observation data which match the pixels size of satellite remote sensing data, the inversion accuracy of satellite inversion products in Tibet plateau is lack of an effective verification. Hence, the in situ observations are required to support their calibration and validation. For this purpose, a multi-level and multi-scale soil moisture and temperature regular automatic monitoring network (MS-SMTRMN) was established on Qiangtang grassland of northern Tibet area to support multiple satellite remote sensing application, climate modeling or assimilation, and land surface process studies. In this paper, MS-SMTRMN aim at multi-satellite remote sensing application was detailed and the observation data with quality control were used to the verification for multiple satellite retrieval products (FY3, AMSR2 and SMOS). This study will contribute to the understanding of the quality of products and lays the foundation for the satellite data assimilation results in the TP area.
Atmospheric transmittance is not only an important physical parameter which affects radiation of ground, but also the main study object in remote sensing, atmosphere physics and radiation transfer. During the range of the solar spectrum, gaseous absorption is mainly related to water vapor, carbon dioxide, ozone, nitrous oxide, carbon monoxide, methane, and oxygen (H2O, CO2, O3, N2O, CO, CH4 and O2). The article studies on atmospheric transmittance based on random exponential band models. Then make use of Modtran to analyze and validate the results using the same atmospheric parameters of random exponential band models. So it will lay a foundation for regressing and fitting the polynomials to calculate atmospheric transmittance, and application on Daily BRDF/ Albedo Algorithm in future.
The anisotropic reflectance of vegetation canopy is mainly determined by its spectral and structural features, and can be described by Bidirectional Reflectance Distribution Function (BRDF). In this article, we select the winter wheat from the beginning of April to the beginning of May 2001 at Shunyi county, north of Beijing, as the research object, to study its BRDF changing rule with the changing time. In the process we compute the structural scattering index (SSI) by inverting the semiempirical linear kernel-driven BRDF model, and analyze its relation with the leaf area index (LAI) of winter wheat. The results show that there is a clear linear relationship between SSI and LAI of winter wheat. So SSI can well be used to reflect the seasonal BRDF changing rule of winter wheat.