The ability of thermal and shortwave infrared spectroscopy to characterise composition and texture was evaluated using both particle size separated soil samples and natural soils. Particle size analysis and separation into clay, silt, and sand-sized soil fractions was undertaken to examine possible relationships between quartz and clay mineral spectral signatures and soil texture. Spectral indices, based on thermal infrared specular and volume scattering features, were found to discriminate clay mineral-rich soil from mostly coarser quartz-rich sandy soil and to a lesser extent from the silty quartz-rich soil. Further investigations were undertaken using spectra and information on 51 USDA and other soils within the ASTER spectral library to test the application of shortwave, mid- and thermal infrared spectral indices for the derivation of clay mineral, quartz, and organic carbon content. A nonlinear correlation between quartz content and a TIR spectral index based on the 8.62？μm was observed. Preliminary efforts at deriving a spectral index for the soil organic carbon content, based on 3.4–3.5？μm fundamental H–C stretching vibration bands, were also undertaken with limited results. 1. Introduction Mapping and analysing soils for their composition and textural characteristics typically involves extensive field work and laboratory techniques that are traditionally time consuming. However the measurement and determination of soil texture and composition is important for the mapping of areas vulnerable to soil erosion, driven by water and wind. Coarser-textured soils are more resistant to detachment and transport via raindrops, thus less affected to water-assisted erosion [1]. Soils with a silt content above 40% are considered highly erodible while clay particles can potentially combine with organic matter to form aggregates or clods which assist in their resistance to erosion [1]. Also, studies of the critical shear wind velocities required for transportation of different-sized soil particles indicate, those with diameters between 0.10 to 0.15？mm are the most vulnerable to wind erosion [1]. Another motivation to determine a soil’s texture and composition, including mineralogy, is with the aim to measure a soil’s ability to retain water or enable drainage. Clay minerals such as montmorillonite can exhibit swelling behaviour, absorbing and storing water, within their layered lattice structure [2]. Such finer textured clay rich soils can offer more water for plant growth than sandy soils. Sandy soils are more vulnerable to drought than clayey soils, storing
References
[1]
R. P. C. Morgan, Soil Erosion and Conservation, Blackwell, Malden, Mass, USA, 3rd edition, 2005.
[2]
R. E. White, Principles and Practice of Soil Science—The Soil as a Natural Resource, Blackwell, Malden, Ma, USA, 4th edition, 2006.
[3]
C. Kosmas, M. Kirkby, and N. Geeson, “Manual on: Key indicators of desertification and mapping environmentally sensitive areas to desertification,” EUR 18882, European Commission, Energy, Environment and Sustainable Development, 1999.
[4]
Food and Agriculture Organisation of the United Nations, The State of Food Insecurity in the World, Rome, Italy, 2011.
[5]
E. Ben-Dor, S. Chabrillat, J. A. M. Demattê et al., “Using imaging spectroscopy to study soil properties,” Remote Sensing of Environment, vol. 113, no. 1, pp. S38–S55, 2009.
[6]
J. A. Hackwell, D. W. Warren, R. P. Bongiovi, S. J. Hansel, T. L. Hayhurst, and D. J. Mabry, “LWIR/MWIR imaging hyperspectral sensor for airborne and ground-based remote sensing,” in Imaging Spectrometry II, vol. 2819 of Proceedings of the SPIE, pp. 102–107, 1996.
[7]
S. Achal, J. E. McFee, T. Ivanco, and C. Anger, “A thermal infrared hyperspectral imager (TASI) for buried landmine detection,” in Detection and Remediation Technologies for Mines and Minelike Targets 7, vol. 6553 of Proceedings of SPIE, The International Society for Optical Engineering, April 2007.
[8]
J. W. Salisbury and D. M. D'Aria, “Infrared (8–14 μm) remote sensing of soil particle size,” Remote Sensing of Environment, vol. 42, no. 2, pp. 157–165, 1992.
[9]
J. W. Salisbury and D. M. D'Aria, “Emissivity of terrestrial materials in the 8–14？μm atmospheric window,” Remote Sensing of Environment, vol. 42, no. 2, pp. 83–106, 1992.
[10]
C. D. Elvidge, “Thermal infrared reflectance of dry plant materials: 2.5–20.0？μm,” Remote Sensing of Environment, vol. 26, no. 3, pp. 265–285, 1988.
[11]
J. W. Salisbury and D. M. D'Aria, “Emissivity of terrestrial materials in the 3–5 μm atmospheric window,” Remote Sensing of Environment, vol. 47, no. 3, pp. 345–361, 1994.
[12]
R. N. Clark, T. V. V. King, M. Klejwa, G. A. Swayze, and N. Vergo, “High spectral resolution reflectance spectroscopy of minerals,” Journal of Geophysical Research, vol. 95, no. 8, pp. 12653–12680, 1990.
[13]
R. H. Merry and L. J. Janik, “Mid infrared spectroscopy for rapid and cheap analysis of soils,” in Proceedings of the 10th Australia Agronomy Conference, January 2001.
[14]
R. A. Viscarra Rossel, D. J. J. Walvoort, A. B. McBratney, L. J. Janik, and J. O. Skjemstad, “Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties,” Geoderma, vol. 131, no. 1-2, pp. 59–75, 2006.
[15]
J. W. Salisbury, A. Wald, and D. M. D'Aria, “Thermal-infrared remote sensing and Kirchhoff's law—1. Laboratory measurements,” Journal of Geophysical Research, vol. 99, no. 6, pp. 11897–11911, 1994.
[16]
W. C. Snyder, Z. Wan, Y. Zhang, and Y. Z. Feng, “Thermal infrared (3–14 μm) of bidirectional reflectance measurements of sands and soils,” Remote Sensing of Environment, vol. 60, no. 1, pp. 101–109, 1997.
[17]
R. D. Hewson, G. R. Taylor, and L. B. Whitbourn, “Application of TIR imagery and spectroscopy for the extraction of soil textural information at fowlers gap, Western New South Wales, Australia,” in Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, pp. 723–726, July 2008.
[18]
J. A. Sobrino, J. C. Jiménez-Mu？oz, L. Balick, A. R. Gillespie, D. A. Sabol, and W. T. Gustafson, “Accuracy of ASTER Level-2 thermal-infrared standard products of an agricultural area in Spain,” Remote Sensing of Environment, vol. 106, no. 2, pp. 146–153, 2007.
[19]
G. Hulley and S. Hook, HyspIRI Level-2 Thermal Infrared (TIR) Land Surface Temperature and Emissivity Algorithm Theoretical Basis Document, JPL Publication 11-5, Jet Propulsion Laboratory, NASA, Pasadena, Calif, USA, 2011.
[20]
Z. L. Li, F. Becker, M. P. Stoll, and Z. Wan, “Evaluation of six methods for extracting relative emissivity spectra from thermal infrared images,” Remote Sensing of Environment, vol. 69, no. 3, pp. 197–214, 1999.
[21]
A. Mushkin, L. K. Balick, and A. R. Gillespie, “Extending surface temperature and emissivity retrieval to the mid-infrared (3–5 μm) using the Multispectral Thermal Imager (MTI),” Remote Sensing of Environment, vol. 98, no. 2-3, pp. 141–151, 2005.
[22]
L. Kirkland, K. Herr, E. Keim et al., “First use of an airborne thermal infrared hyperspectral scanner for compositional mapping,” Remote Sensing of Environment, vol. 80, no. 3, pp. 447–459, 2002.
[23]
T. J. Cudahy, M. Caccetta, A. Cornelius, et al., “Regolith geology and alteration mineral maps from new generation airborne and satellite remote sensing technologies; and Explanatory Notes for the Kalgoorlie-Kanowna, 1:100,000 scale map sheet, remote sensing mineral maps,” MERIWA Report 252, Perth, Australia, 2005.
[24]
T. Cudahy, M. Jones, M. Thomas et al., Mapping Soil Surface Mineralogy at Tick Hill, North-Western Queensland, Australia, Using Airborne Hyperspectral Imagery, Springer, 1st edition, 2010.
[25]
R. Hewson, T. Cudahy, A. Beech, M. Jones, and M. Thomas, “Mineral and textural investigations of soils using thermal infrared spectroscopy,” in Proceedings of the 19th World Congress of Soil Science, Brisbane, Australia, August 2010.
[26]
A. M. Baldridge, S. J. Hook, C. I. Grove, and G. Rivera, “The ASTER spectral library version 2.0,” Remote Sensing of Environment, vol. 113, no. 4, pp. 711–715, 2009.
[27]
J. A. Sobrino, C. Mattar, P. Pardo et al., “Soil emissivity and reflectance spectra measurements,” Applied Optics, vol. 48, no. 19, pp. 3664–3670, 2009.
[28]
R. D. Hewson and G. R. Taylor, “An investigation of the geological and geomorphological features of Fowlers Gap using thermal infrared, radar and airborne geophysical remote sensing techniques,” Rangeland Journal, vol. 22, no. 1, pp. 105–123, 2000.
[29]
N. J. McKenzie, K. J. Coughlan, and H. P. Cresswell, Soil Physical Measurement and Interpretation for Land Evaluation, CSIRO Publishing, Melbourne, Australia, 2002.
[30]
R. F. Isbell, The Australian Soil Classification, CSIRO, Melbourne, Australia, 1996.
[31]
P. Carlile, E. Bui, C. Moran, D. Simon, and B. Henderson, “Method used to generate soil attribute surfaces for the Australian Soil Resource Information System using soil maps and look-up table,” CSIRO Land and Water Technical Report 24/01, CSIRO, 2011.
[32]
S. J. Hook and A. B. Kahle, “The micro Fourier Transform Interferometer (μFTIR)—a new field spectrometer for acquisition of infrared data of natural surfaces,” Remote Sensing of Environment, vol. 56, no. 3, pp. 172–181, 1996.
[33]
A. Walkley and I. A. Black, “An examination of the Degtjareff method for determining organic carbon in soils: effect of variations in digestion conditions and of inorganic soil constituents,” Soil Science, vol. 63, pp. 251–263, 1934.
[34]
R. D. Hewson, L. B. Whitbourn, and G. R. Taylor, “Application of TIMS imagery and airborne CO2 laser spectroscopy for geological and geomorphological investigations in an arid environment, Western NSW, Australia,” in Proceedings of the 12th International Conference of Applied Geologic Remote Sensing, vol. 2, pp. 373–384, 1997.
[35]
J. W. Salisbury, D. M. D’Aria, and L. E. Brown, Infrared (2.08–14 μm) Spectra of Soils: A Preliminary Report, Department of Earth and Planetary Sciences, Johns Hopkins University, 1990.
[36]
J. W. Salisbury and J. W. Eastes, “The effect of particle size and porosity on spectral contrast in the mid-infrared,” Icarus, vol. 64, no. 3, pp. 586–588, 1985.
[37]
J. K. Crowley, D. W. Brickey, and L. C. Rowan, “Airborne imaging spectrometer data of the Ruby Mountains, Montana: mineral discrimination using relative absorption band-depth images,” Remote Sensing of Environment, vol. 29, no. 2, pp. 121–134, 1989.
[38]
F. Van Der Meer, “Spectral curve shape matching with a continuum removed CCSM algorithm,” International Journal of Remote Sensing, vol. 21, no. 16, pp. 3179–3185, 2000.
