Surface soil clay content mapping at large scales using multispectral (VNIR-SWIR) ASTER data - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Accéder directement au contenu
Article Dans Une Revue International Journal of Remote Sensing Année : 2019

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

Résumé

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 km(2)) 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 mu m). 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 ( = 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 ( = 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.
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Dates et versions

hal-02619303 , version 1 (25-05-2020)

Identifiants

Citer

Anis Gasmi, Cécile Gomez, Philippe Lagacherie, Hedi Zouari. Surface soil clay content mapping at large scales using multispectral (VNIR-SWIR) ASTER data. International Journal of Remote Sensing, 2019, 40 (4), pp.1506-1533. ⟨10.1080/01431161.2018.1528018⟩. ⟨hal-02619303⟩
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