4.5 Article

Parametric exponentially correlated surface emission model for L-band passive microwave soil moisture retrieval

期刊

PHYSICS AND CHEMISTRY OF THE EARTH
卷 83-84, 期 -, 页码 65-74

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.pce.2015.04.001

关键词

Soil moisture; L-band; Roughness parameterization; Exponential correlation; SMOS; SMAP

资金

  1. National Natural Science Foundation of China [41301396]
  2. Strategic Priority Research Program for Space Sciences'' of the Chinese Academy of Sciences, National Key Basic Research Program of China [2015CB953701]
  3. CAS/SAFEA International Partnership Program for Creative Research Teams [KZZD-EW-TZ-09]
  4. Foundation for Fostering Talents in State Key Laboratory of Remote Sensing Science

向作者/读者索取更多资源

Surface soil moisture is an important parameter in hydrology and climate investigations. Current and future satellite missions with L-band passive microwave radiometers can provide valuable information for monitoring the global soil moisture. A factor that can play a significant role in the modeling and inversion of microwave emission from land surfaces is the surface roughness. In this study, an L-band parametric emission model for exponentially correlated surfaces was developed and implemented in a soil moisture retrieval algorithm. The approach was based on the parameterization of an effective roughness parameter of Hp in relation with the geometric roughness variables (root mean square height s and correlation length l) and incidence angle. The parameterization was developed based on a large set of simulations using an analytical approach incorporated in the advanced integral equation model (AIEM) over a wide range of geophysical properties. It was found that the effective roughness parameter decreases as surface roughness increases, but increases as incidence angle increases. In contrast to previous research, Hp was found to be expressed as a function of a defined slope parameter m = s(2)/l, and coefficients of the function could be well described by a quadratic equation. The parametric model was then tested with L-band satellite data in soil moisture retrieval algorithm over the Little Washita watershed, which resulted in an unbiased root mean square error of about 0.03 m(3)/m(3) and 0.04 m(3)/m(3) for ascending and descending orbits, respectively. (C) 2015 Elsevier Ltd. All rights reserved.

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