期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2010
卷号：XXXVIII - Part 7B
页码：176-180
出版社：Copernicus Publications
摘要：Soil moisture retrieval from SAR images using semi-empirical or physically-based backscatter models requires surface roughness pa- rameters, generally obtained by means of in situ measurements. However, measured roughness parameters often result in inaccurate soil moisture contents. Furthermore, when these retrieved soil moisture contents need to be used in data assimilation schemes, it is important to also assess the retrieval uncertainty. In this paper, a regression-based method is developed that allows for the parameteriza- tion of roughness by means of a probability distribution. This distribution is further propagated through an inverse backscatter model in order to obtain probability distributions of soil moisture content. About 70% of the obtained distributions are skewed and non-normal and it is furthermore shown that their interquartile range differs with respect to soil moisture conditions. Comparison of soil moisture measurements with the retrieved median values results in a root mean square error of approximately 3.5 vol%
