Surface soil clay content mapping at large scales using multispectral (VNIR–SWIR) ASTER data

ABSTRACT

The potential of Visible Near-Infrared and Short-Wave Infrared (VNIR–SWIR, 400 nm–2500 nm) hyperspectral imagery for use in multivariate approaches and geostatistical techniques for mapping topsoil properties has been previously demonstrated. However, the use of VNIR–SWIR hyperspectral imagery remains costly, which limits the spatial scales over which it can be applied. This paper aims to evaluate the potential for substituting the more accessible Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) VNIR–SWIR multispectral data for hyperspectral imagery in mapping surface soil clay contents. This study used ASTER multispectral data (nine bands in the VNIR–SWIR spectral domain) acquired over the Cap-Bon region in Tunisia (2000 km²) and 262 surface soil samples collected within the ASTER scene that were subjected to laboratory analysis of the clay fraction (soil particles less than 2 µm). The approach followed two steps: i) estimation of surface soil clay contents for bare soil areas using a Multiple Linear Regression (MLR) model built from the 9 ASTER VNIR–SWIR bands and ii) spatial interpolation (co-kriging) of the soil sampling of measured points and the ASTER-estimates over the whole study area. The MLR model for estimating clay contents using ASTER multispectral data performed correctly ($R_{\mathrm{v}\mathrm{a}\mathrm{l}}^2$ = 0.60). In addition, this performance is only slightly lower than that obtained using hyperspectral imagery (specifically, an Airborne Imaging Spectrometer for Applications (AISA-DUAL) dual hyperspectral sensor) in a previous study. Moreover, the co-kriging process appeared to yield encouraging results for capturing the large range of variability of clay content values, although it was not able to represent the short scale variability ($R_{\mathrm{C}\mathrm{V}}^2$ = 0.43). Finally, the ASTER multispectral data, despite being underused in the mapping of soil properties, may open up new ways to perform more extensive mapping of surface soil properties in semi-arid contexts characterized by extensive bare and dry soil surfaces.

Acknowledgments

This research was supported by the French National Research Agency (ANR) through the ALMIRA project (ANR-12-TMED-0003), MISTRAL 2011 project Sicmed-Lebna “Biophysical and socio-economical analysis of water management within the Tunisian Cap-Bon Peninsula: the Lebna study area” and the Water Researches and Technologies Center of Borj-Cedria Technopark (CERTE, Tunisia). The authors are indebted to Yves Blanca (IRD-UMR LISAH Montpellier), Zakia Jenhaoui (IRD UMR LISAH Tunis) for the soil sampling in 2009 and 2010 over the Lebna catchment and to Hedi Hamrouni (DG/ACTA Sol, Tunis) for his significant support to this soil sampling campaign.

Disclosure statement

No potential conflict of interest was reported by the authors.