The Soil Moisture and Ocean Salinity (SMOS) satellite has been providing global data for more than 11 years. The algorithm to retrieve surface soil moisture (SM) and vegetation optical depth (VOD) from Brightness Temperatures (TB) has constantly evolved as our understanding of the instrument and of the responses to various ecosystems increased. The evolution of the radiative transfer modelling used in the inversion process is in part based upon ground measurements done on experimental sites. We present the particular case of an L-band radiometer placed on top of a 800- meter-high cliff. This design allows us to study large and various scenes when compared to classical experiments where a radiometer is placed 10–20 m above a surface. With our set up, the footprints cover areas larger than 300 m in diameter, covering thus several land use types and the footprint can be directed towards different dominant land classes (forest, crops, urban etc…). This paper presents the whole set up consisting of in situ measurements (soil moisture and surface temperatures) and L-band radiometry acquired by the LEWIS instrument at high incidence angles. We perform SM/VOD retrievals from brightness temperatures using various configurations which are compared to the in situ observations. We test in particular a 2-VOD retrieval approach that consists in deriving one SM for the entire scene but two VOD, one for agricultural/low vegetation and a VOD for the forest parts, which improves the performance of the SM/VOD retrievals.

In the framework of the preparation of the Soil Moisture and Ocean Salinity (SMOS) mission, several field experiments are required so as to address specific modeling issues. The goal is to improve current models and to test retrieval algorithms. However, adequate ground instrumentation is scarce and not readily available "off the shelf'' In this context, a high-accuracy L-band radiometer was required for a specific long-term campaign for the preparation of the SMOS mission. For this purpose, a dual-polarized radiometer was designed and built to check algorithms for surface soil moisture retrieval from multiangular dual-polarized brightness temperatures. This radiometer has been tested in the field for 20 months and is operational since end of January 2003. The aim of this paper is to give details of the system architecture, calibration procedures, together with the performances obtained and some preliminary results.

The automatic classification of urban materials from airborne and spatial acquisitions remains difficult today because of two main reasons: the spatial resolution of the images and the need for pre-processing algorithms to extract ground surface intrinsic properties. This work examines the feasibility of using 8 spectral information distributed in the visible and the near-infrared spectral regions (0.4 - 1 µm), acquired at a 20 cm spatial resolution, for recognizing the urban materials. The motivation for this study is the development of very high spatial resolution sensors which has introduced a promising capability for the study of urban areas. In this study, an experiment campaign took place in Toulouse. The airborne measurements were carried out using 8 cameras associated with 8 narrow filters (30 nm). Ground spectral measurements of Toulouse's urban materials were performed within the configuration of the airborne acquisitions. These measurements allow us to determine and quantify three types of reflectance spatial variability. The results show that urban materials have low reflectances with no significant spectral features and are then difficult to discriminate. To determine which material classes could be discriminate over the 8 spectral bands of the airborne acquisitions, a statistical analysis was performed on the ground measurements. This analysis highlights that 5 material classes could be discriminated from good quality measurements.