Author: Bériaux Emilie Waldner François Collienne François Bogaert Patrick Defourny Pierre
Publisher: MDPI
E-ISSN: 2072-4292|7|12|16204-16225
ISSN: 2072-4292
Source: Remote Sensing, Vol.7, Iss.12, 2015-12, pp. : 16204-16225
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Abstract
In order to monitor crop growth along the season with synthetic aperture radar (SAR) images, radiative transfer models were developed to retrieve key biophysical parameters, such as the Leaf Area Index (LAI). The semi-empirical water cloud model (WCM) can be used to estimate LAI values from SAR data and surface soil moisture information. Nevertheless, instability problems can occur during the model calibration, which subsequently reduce its transferability in both time and space. To avoid these ill-posed cases, three calibration methodologies are benchmarked in the present study. The accuracy of the retrieved LAI values for each methodology was analyzed, as well as the sensitivity of the signal to LAI for different soil moisture values. The sensitivity of the cross-polarization was highlighted especially for high LAI. The VV polarization was found sensitive for LAI values inferior to 2 m