Applicability of the Thermal Infrared Spectral Region for the Prediction of Soil Properties Across Semi-Arid Agricultural Landscapes

Remote Sensing

Andreas Eisele¹  Ian Lau³  Robert Hewson⁴  Dan Carter²  Buddy Wheaton²  Cindy Ong³  Thomas John Cudahy³  Sabine Chabrillat¹ 

[1] Helmholtz Centre Potsdam, GFZ German Research Centre For Geosciences, Telegrafenberg, D-14473 Potsdam, Germany; E-Mails:;Department of Agriculture and Food of Western Australia (DAFWA), 3 Baron-Hay Court, South Perth, WA 6151, Australia; E-Mails:;Exploration & Mining, ARRC, CSIRO, 26 Dick Perry Avenue, Kensington, WA 6151, Australia; E-Mails:;School of Mathematical and Geospatial Sciences, RMIT University, GPO Box 2476, Melbourne, VIC 3001, Australia; E-Mail:

关键词: thermal infrared;    TIR;    emission IR spectroscopy;    soils;    texture;    organic carbon;   

DOI  :  10.3390/rs4113265

来源: mdpi

【 摘 要 】

In this study we tested the feasibility of the thermal infrared (TIR) wavelength region (within the atmospheric window between 8 and 11.5 μm) together with the traditional solar reflective wavelengths for quantifying soil properties for coarse-textured soils from the Australian wheat belt region. These soils have very narrow ranges of texture and organic carbon contents. Soil surface spectral signatures were acquired in the laboratory, using a directional emissivity spectrometer (μFTIR) in the TIR, as well as a bidirectional reflectance spectrometer (ASD FieldSpec) for the solar reflective wavelengths (0.4–2.5 μm). Soil properties were predicted using multivariate analysis techniques (partial least square regression). The spectra were resampled to operational imaging spectroscopy sensor characteristics (HyMAP and TASI-600). To assess the relevance of specific wavelength regions in the prediction, the drivers of the PLS models were interpreted with respect to the spectral characteristics of the soils’ chemical and physical composition. The study revealed the potential of the TIR (for clay: R² = 0.93, RMSEP = 0.66% and for sand: R² = 0.93, RMSEP = 0.82%) and its combination with the solar reflective region (for organic carbon: R² = 0.95, RMSEP = 0.04%) for retrieving soil properties in typical soils of semi-arid regions. The models’ drivers confirmed the opto-physical base of most of the soils’ constituents (clay minerals, silicates, iron oxides), and emphasizes the TIR’s advantage for soils with compositions dominated by quartz and kaolinite.

【 授权许可】

CC BY   
© 2012 by the authors, licensee MDPI, Basel, Switzerland.