Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W3, 413-417, 2015
https://doi.org/10.5194/isprsarchives-XL-3-W3-413-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
19 Aug 2015
SEMI-BLIND SOURCE SEPARATION FOR ESTIMATION OF CLAY CONTENT OVER SEMI-VEGETATED AREAS, FROM VNIR/SWIR HYPERSPECTRAL AIRBORNE DATA
W. Ouerghemmi1,2, C. Gomez1, S. Nacer2, and P. Lagacherie3 1IRD, UMR LISAH (INRA-IRD-SupAgro), F-34060 Montpellier, France
2LTSIRS, Laboratoire de Télédétection et Systèmes d’Information à Référence Spatiale, ENIT, Tunisia
3INRA, UMR LISAH (INRA-IRD-SupAgro), F-34060 Montpellier, France
Keywords: Hyperspectral remote sensing, Semi-Blind source separation, Non-Negative Matrix Factorization, partial least squares regression, clay content, semi-vegetated pixels Abstract. The applicability of Visible, Near-Infrared and Short Wave Infrared (VNIR/SWIR) hyperspectral imagery for soil property mapping decreases when surfaces are partially covered by vegetation. The objective of this research was to develop and evaluate a methodology based on the “double-extraction” technique, for clay content estimation over semi-vegetated surfaces using VNIR/SWIR hyperspectral airborne data. The “double-extraction” technique initially proposed by Ouerghemmi et al. (2011) consists of 1) an extraction of a soil reflectance spectrum ssoil from semi-vegetated spectra using a Blind Source Separation technique, and 2) an extraction of clay content from the soil reflectance spectrum ssoil, using a multivariate regression method. In this paper, the Source Separation approach is Semi-Blind thanks to the integration of field knowledge in Source Separation model. And the multivariate regression method is a partial least squares regression (PLSR) model. This study employed VNIR/SWIR HyMap airborne data acquired in a French Mediterranean region over an area of 24 km2.

Our results showed that our methodology based on the “double-extraction” technique is accurate for clay content estimation when applied to pixels under a specific Cellulose Absorption Index threshold. Finally the clay content can be estimated over around 70% of the semi-vegetated pixels of our study area, which may offer an extension of soil properties mapping, at the moment restricted to bare soils.

Conference paper (PDF, 819 KB)


Citation: Ouerghemmi, W., Gomez, C., Nacer, S., and Lagacherie, P.: SEMI-BLIND SOURCE SEPARATION FOR ESTIMATION OF CLAY CONTENT OVER SEMI-VEGETATED AREAS, FROM VNIR/SWIR HYPERSPECTRAL AIRBORNE DATA, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W3, 413-417, https://doi.org/10.5194/isprsarchives-XL-3-W3-413-2015, 2015.

BibTeX EndNote Reference Manager XML