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000019606 041__ $$aeng
000019606 084__ $$2WoS$$aRemote Sensing
000019606 1001_ $$0P:(DE-HGF)0$$aBériaux, E.$$b0
000019606 245__ $$aEstimating surface-soil moisture for retrieving maize leaf-area index from SAR data
000019606 260__ $$c2011
000019606 300__ $$a136 - 150
000019606 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article
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000019606 440_0 $$025206$$aCanadian Journal of Remote Sensing$$v37$$y1
000019606 500__ $$3POF3_Assignment on 2016-02-29
000019606 500__ $$aThis research was funded through STEREO II grant SR/00/101 (GLOBAM project) of the Belgian Science Policy. The ERS and ENVISAT SAR data were provided by the European Space Agency under the Category 1 Project. The parcel delineations were made available by the Direction of Agriculture of the Walloon Region. The authors also thank Allard de Wit for recommending the SWAP model.
000019606 520__ $$aThe leaf-area index (LAI) is a key parameter for coupling earth-observation data with crop-growth models from the perspective of crop-yield forecasting. Remote sensing is of particular interest in estimating LAI over large areas. SAR data, thanks to their systematic acquisition, offer an ideal temporal resolution throughout the crop-growing season. Nevertheless, surface soil dielectric permittivity, which is strongly correlated with soil moisture, also affects the SAR signal. Thus, surface-soil permittivity or moisture has to be taken into account. This study tackles the issues related to soil influence on the SAR signal in monitoring maize crop growth. Different methods of assessing surface-soil moisture or permittivity are explored in order to retrieve LAI values from SAR data. The first method is based on a hydrological model-the soil, water, atmosphere, and plant (SWAP) model-with which the surface-soil moisture level can be estimated as a function of time. This method is tested with two kinds of meteorological data as inputs for the hydrological model: ground meteorological data and estimated meteorological data. The second method resorts to ground-penetrating radar, an alternative means of estimating surface-soil permittivity. This study demonstrates that both soil-moisture levels estimated by the SWAP model and soil permittivity measured by ground-penetrating radar can be successfully used for retrieving maize LAI values from SAR data using the water cloud model.
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000019606 7001_ $$0P:(DE-Juel1)VDB54976$$aLambot, S.$$b1$$uFZJ
000019606 7001_ $$0P:(DE-HGF)0$$aDefourny, P.$$b2
000019606 773__ $$0PERI:(DE-600)2191814-4$$gVol. 37, p. 136 - 150$$p136 - 150$$q37<136 - 150$$tCanadian Journal of Remote Sensing$$v37$$y2011
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000019606 9141_ $$y2011
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