Evaluation of a Global Soil Moisture Product from Finer Spatial Resolution SAR Data and Ground Measurements at Irish Sites

Remote Sensing

Chiara Pratola³  Brian Barrett¹  Alexander Gruber²  Gerard Kiely⁴ 

[1] School of Geography & Archaeology, University College Cork, Cork, Ireland; E-Mail:;Department of Geodesy and Geoinformation, Vienna University of Technology, 1040 Vienna, Austria; E-Mail:;Coastal and Marine Research Centre, Environmental Research Institute, University College Cork, Naval Base, Haulbowline, Cobh, Co. Cork, Ireland; E-Mail:;Environmental Research Institute, Civil and Environmental Engineering Department, University College Cork, Cork, Ireland; E-Mail:

关键词: ESA Climate Change Initiative;    Essential Climate Variable;    soil moisture;    ENVISAT ASAR WS;    temporal variability;    spatial variability;   

DOI  :  10.3390/rs6098190

来源: mdpi

【 摘 要 】

In the framework of the European Space Agency Climate Change Initiative, a global, almost daily, soil moisture (SM) product is being developed from passive and active satellite microwave sensors, at a coarse spatial resolution. This study contributes to its validation by using finer spatial resolution ASAR Wide Swath and in situ soil moisture data taken over three sites in Ireland, from 2007 to 2009. This is the first time a comparison has been carried out between three sets of independent observations from different sensors at very different spatial resolutions for such a long time series. Furthermore, the SM spatial distribution has been investigated at the ASAR scale within each Essential Climate Variable (ECV) pixel, without adopting any particular model or using a densely distributed network of in situ stations. This approach facilitated an understanding of the extent to which geophysical factors, such as soil texture, terrain composition and altitude, affect the retrieved ECV SM product values in temperate grasslands. Temporal and spatial variability analysis provided high levels of correlation (p < 0.025) and low errors between the three datasets, leading to confidence in the new ECV SM global product, despite limitations in its ability to track the driest and wettest conditions.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland