Reflectance spectroscopy provides an alternate method to classical physical and chemical laboratory soil analysis for estimation of a large range of key soil properties. Techniques including classical chemometrics approaches and specific absorption features studies have been developed for deriving estimates of soil characteristics from visible and near-infrared (VNIR, 400-1200 mm) and shortwave infrared (SWIR, 1200-2500 nm) reflectance measurements. This paper examines the performances of two distinct methods for clay and calcium carbonate (CaCO3) content estimation (two key soil properties for erosion prediction) by VNIR/SWIR spectroscopy: i) the Continuum Removal (CR) has been used to correlate spectral absorption bands centred at 2206 and 2341 nm with clay and CaCO3 concentrations and ii) the partial least-squares regression (PLSR) method with leave-one-out cross-validation, which is a classical chemometrics technique, has been used to predict clay and CaCO3 concentrations from VNIR/SWIR full spectra. We tried to respond to the question "should we use all bands in the 400-2500 nm range or should we focus our analysis on selected spectral absorption bands to determine soil properties from reflectance data?" In this paper, the CR and PLSR methods were applied to VNIR/SWIR laboratory and airborne HYMAP reflectance measurements collected over the La Peyne Valley area in southern France. This study shows that the performance of both techniques is dependent on the spectral feature for the soil property of interest and on the level data acquisition (lab or airborne) face to the instrument specifications. When airborne HYMAP reflectance measurements are used, the PLSR technique performs better than the CR approach. As well, when the soil property of interest has no well-identified spectral feature, which is the case of clay, the PLSR technique performs better than the CR approach. In this last situation, PLSR is able to find surrogate spectral features that retain satisfactory estimations of the studied soil properties. However, parts of these spectral features remain difficult to explain or relate to area-specific correlations between soil properties, which means that extrapolation to larger pedological contexts must be envisaged with care. In the near future, VNIR/SWIR airborne hyperspectral data processed by the PLSR technique will allow for accurate mapping of clay and CaCO3 contents, which will contribute significantly to the digital mapping of soil properties.
