Estimating soil sand content using thermal infrared spectra in arid lands

Sand content is a textural property of soils closely related to soil quality. A fast determination of sand content at large scales is paramount importance for monitoring soil degradation to improve agricultural practices. The main objective of this study is to evaluate the ability of the thermal infrared region (TIR) to estimate sand content of soils. Thermal infrared spectra obtained in the field from a Fourier Transform Spectrometer are used to develop a partial least square regression model (PLSR) that translates thermal emittance to soil texture properties. Our results show that the 9.435-9.473 μm wavelength regions hold a great promise for prediction of sand content. Coefficient of determination R2 is 0.87 and standard error (SE) is 2.79. We also show that second derivative of thermal spectral profiles is very useful to detect kaolinite in sand dominated soils. The results of this study provide further insights for developing future thermal sensors aimed at predicting soil quality as indicated by the sand content and other textural properties.