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The purpose of this paper is the capacity of spectral reflectance, in the full optical domain 0.4 – 12 µm, to retrieve the Soil Moisture Content (SMC) of bare soils. For this, a new empirical soil model was performed from spectra lab measurements, and more precisely from soil's classification, to simulate spectral reflectance for a given SMC, and in inverse way to estimate SMC. In solar and thermal domain, simulated spectra are highly correlated with measured spectra, respectively with 98% and 85%. In inverse way, estimation of SMC from a spectral reflectance and a given soil classes, provides a RMSE of 3.2% in solar and 2.8% in thermal domain.

The purpose of this paper is to analyse the impact of surface soil moisture on spectral reflectance in the optical domain [0.4–15 μm]. This work is based on lab spectral reflectance measurements of many bare soils at different moisture contents. Firstly, a classification of bare soil samples is performed according to their spectral signatures: five classes are then defined. Secondly, the soil moisture content impact on spectral signatures is analysed. In the [0.4–15 μm] domain, measurements exhibit, for all the samples, a decreasing of the reflectance level with an increasing of moisture content. These measurements give information on absorption peaks related to soil mineral components like hydroxyl, carbonate, and quartz. Thus, analysis of our lab measurements indicates that soil moisture impact on spectral reflectance depends of studied spectral domain. These measurements may improve existing data bases, and will be used in a processing chain to estimate the soil moisture content (cases of bare soil and/or sparse vegetation) in the optical domain [0.4–12 μm] by using airborne hyperspectral imaging.