Chapter

Proximal Soil Sensing

Part of the series Progress in Soil Science pp 211-229

Date:

Mapping Soil Surface Mineralogy at Tick Hill, North-Western Queensland, Australia, Using Airborne Hyperspectral Imagery

  • T. CudahyAffiliated withCSIRO Exploration and Mining, Australian Resources Research Centre Email author 
  • , M. JonesAffiliated withCSIRO Exploration and Mining, Australian Resources Research Centre
  • , M. ThomasAffiliated withCSIRO Exploration and Mining, Australian Resources Research Centre
  • , P. CocksAffiliated withCSIRO Exploration and Mining, Australian Resources Research Centre
  • , F. AgustinAffiliated withGeological Survey of Queensland
  • , M. CaccettaAffiliated withGeoscience Australia
  • , R. HewsonAffiliated withHyVista Corporation
  • , M. VerrallAffiliated withCurtin University
  • , A. RodgerAffiliated withCurtin University

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Abstract

The use of airborne hyperspectral imagery for mapping soil surface mineralogy is examined for the semi-arid Tick Hill test site (20 km2) near Mount Isa in north-western Queensland. Mineral maps at 4.5 m pixel resolution include the abundances and physicochemistries (chemical composition and crystal disorder) of kaolin, illite–muscovite, and Al-smectite (both montmorillonite and beidellite), as well as iron oxide, hydrated silica (opal), and soil/rock water (bound and unbound). Validation of these hyperspectral mineral maps involved field sampling (34 sites) and laboratory analyses (spectral reflectance and X-ray diffraction). The field spectral data were processed for their mineral information content in the same way as the airborne HyMap data processing. The results showed significant spatial and statistical correlation. The mineral maps provide more detailed surface composition information compared with the published soil and geological maps and other geoscience data (airborne radiometrics and digital elevation model). However, there is no apparent correlation between the published soil types (i.e. Ferrosols, Vertosols, and Tenosols) and the hyperspectral mineral maps (e.g. iron oxide-rich areas are not mapped as Ferrosols and smectite-rich areas are not mapped as Vertosols). This lack of correlation is interpreted to be related to the current lack of spatially comprehensive mineralogy for existing regional soil mapping. If correct, then this new, quantitative mineral-mapping data have the potential to improve not just soil mapping but also soil and water catchment monitoring and modelling at local to regional scales. The challenges to achieving this outcome include gaining access to continental-scale hyperspectral data and models that link the surface mineralogy to subsurface soil characteristics/processes.

Keywords

Remote sensing Hyperspectral mineral mapping Airborne radiometrics Digital elevation model