Soil moisture retrieval from optical and thermal spaceborne remote sensing.

Soil moisture is the water held in the soil within reach of plant roots and is one of the most important land environmental variables in perspective with land surface climatology, hydrology, and ecology. The soil moisture content (SMC) generally refers to the water contained in the upper 1-2 m of soil, which can potentially evaporate into the atmosphere. Variations in SMC have strong impacts on changes in the surface energy balance, regional runoff, and vegetation productivity (crop yield potential). SMC conditions may also serve as a warning for flooding. In areas of active deforestation, SMC estimates help to predict run-off as well as soil erosion. Despite the importance of SMC, the main problem is that the gravimetric method (standard procedure of SMC determination), on which all other methods are ultimately calibrated, is essentially a point measurement. Local scale variations in soil properties, terrain, and vegetation cover make selection of representative field sites difficult if not impossible. Contrarily, remote sensing (RS) techniques may be compromising because of the spatial ability and the relatively low cost (Wagner et al., 1999). Zazueta and Xin (1994) classify well known general measurement techniques to determine soil moisture content: (i) gravimetric techniques, (ii) nuclear (neutron scattering, gamma attenuation, nuclear magnetic resonance), (iii) electromagnetic (resistive and capacitive sensors, time and frequency domain reflectometer), (iv) tensiometric, (v) hydrometric, (vi) remote sensing (passive and active microwave, thermal infrared) and (vii) optical techniques (polarized light, fibre optic sensors, near-infrared). A more basic field method (ix) is the ‘Feel and Appearance method’ using a soil moisture interpretation chart based on texture classification and squeezing of soil samples (Miles, 1998). We demonstrate that optical and thermal information from an existing operational spaceborne sensor (METEOSAT) can be used to determine SMC on 10-daily intervals without the need of excessive ancillary data or direct coupling with SVAT models. We present the methodology, the product validation on 2 EUROFLUX sites (Valentini et al., 2000) and a comparison with active microwave RS using the ERS Scatterometer (Wagner et al., 1999).