Global-Scale Evaluation of Roughness Effects on C-Band AMSR-E Observations

Remote Sensing

Shu Wang³  Jean-Pierre Wigneron⁵  Ling-Mei Jiang³  Marie Parrens⁵  Xiao-Yong Yu³  Amen Al-Yaari⁵  Qin-Yu Ye³  Roberto Fernandez-Moran⁵  Wei Ji⁴  Yann Kerr²  Nicolas Baghdadi¹ 

[1] State Key Laboratory of Remote Sensing Science, and School of Geography, Beijing Normal University, Beijing 100875, China;;Centre d’Etudes Spatiales de la BIOsphere (CESBIO), UMR 5126, (CNES, CNRS, IRD, UT3), Toulouse Cedex 31401, France; E-Mails:;State Key Laboratory of Remote Sensing Science, and School of Geography, Beijing Normal University, Beijing 100875, China; E-Mails:;Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China; E-Mail:;INRA, UMR 1391 ISPA, Villenave d’Ornon, INRA, Bordeaux Aquitaine 33140, France; E-Mails:

关键词: soil moisture;    soil surface roughness;    AMSR-E;   

DOI  :  10.3390/rs70505734

来源: mdpi

【 摘 要 】

Quantifying roughness effects on ground surface emissivity is an important step in obtaining high-quality soil moisture products from large-scale passive microwave sensors. In this study, we used a semi-empirical method to evaluate roughness effects (parameterized here by the Hr parameter) on a global scale from AMSR-E (Advanced Microwave Scanning Radiometer for EOS) observations. AMSR-E brightness temperatures at 6.9 GHz obtained from January 2009 to September 2011, together with estimations of soil moisture from the SMOS (Soil Moisture and Ocean Salinity) L3 products and of soil temperature from ECMWF’s (European Centre for Medium-range Weather Forecasting) were used as inputs in a retrieval process. In the first step, we retrieved a parameter (referred to as the a* parameter) accounting for the combined effects of roughness and vegetation. Then, global MODIS NDVI data were used to decouple the effects of vegetation from those of surface roughness. Finally, global maps of the Hr parameters were produced and discussed. Initial results showed that some spatial patterns in the Hr values could be associated with the main vegetation types (higher values of Hr were retrieved generally in forested regions, intermediate values were obtained over crops and grasslands, and lower values were obtained over shrubs and desert) and topography. For instance, over the USA, lower values of Hr were retrieved in relatively flat regions while relatively higher values were retrieved in hilly regions.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.