To conduct with these land surface parameters inversion using microwave observations in the bare soil surface, it is needed to estimate soil moisture (SM), surface temperature (ST) and surface roughness changes with microwave observations. High-frequency passive microwave radiometer sensitivity of the roughness is very low, traditional ground truth can't provide an accurate large-scale roughness of pixel information, and active radar and scatterometer data for roughness of the high sensitivity, active and passive joint inversion of soil volumetric water content is the current hot research. The main objective of this research is to develop a suitable method instead of some traditional methods for the retrieval of SM and other parameters at large-scale, which is based on the synergistic use of AMSR-E and Quikscat/SeaWinds observations. Quikscat / SeaWinds can provide large-scale scatterometer data, first used in this study to establish AIEM simulation and backscattering coefficient of roughness between, and then estimate the roughness of the known information as auxiliary inversion surface AMSR-E temperature and soil volumetric water content. The retrieval results show that this proposed method is helpful to achieve a higher accuracy in the study region of Maqu.
['Ruofei Zhong', 'Jianxi Huang', 'Jiangxia Wei', 'Qin Li', 'Jiao Guo', 'Wei Su']
Large-Scale Microwave Remote Sensing of Retrieving Surface Multi-parameters Using Active and Passive Satellite Data: In the Tibetan Plateau Region of Maqu