Title of article :
A field experiment on microwave forest radiometry: L-band signal behaviour for varying conditions of surface wetness
Author/Authors :
Grant، نويسنده , , J.P. and Wigneron، نويسنده , , J.-P. and Van de Griend، نويسنده , , A.A. and Kruszewski، نويسنده , , A. and Sّbjوrg، نويسنده , , S. Schmidl and Skou، نويسنده , , N.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2007
Abstract :
From July–December 2004 the experimental campaign ‘Bray 2004’ was conducted in the coniferous forest of Les Landes near Bordeaux, France, using a multi-angle L-band (1.4 GHz) radiometer to measure from above the forest at horizontal polarization. At the same time, ground measurements were taken of soil and litter moisture content, while precipitation was also permanently monitored. This experiment was done in the context of the upcoming SMOS mission in order to improve our understanding of the behaviour of the L-band signal from forested areas for different wetness conditions and viewing angles. This is especially relevant for solving the problem of heterogeneity since a large fraction of SMOS pixels (∼ 30 × 30 km2) is partially covered by forest.
aper describes the objectives and the overall set-up of the Bray-2004 experiment and shows some first results. The greater part of the horizontally polarized L-band signal is found to be dominated by the influence of physical temperature. Variations in soil and/or litter moisture content are visible in the angular signal and in the above-canopy microwave emission, although the dynamic range of this last effect is very small. This, together with the fact that emissivity values are very high, is possibly due to the presence of a substantial litter layer. However, decoupling of soil and litter effects is difficult because of the strong correlation found between soil and litter moisture.
Keywords :
L-band , pine forest , Soil moisture , Litter moisture , Precipitation , Ground-canopy temperature , Passive microwaves
Journal title :
Remote Sensing of Environment
Journal title :
Remote Sensing of Environment