Spectral and textural classification of multi-source imagery to identify soil degradation stages in semi-arid environments

Arid and semi-arid areas are specially susceptible to soil degradation processes such as erosion and salinization and the influence of land use. The identification of soil degradation stages form an important basis for sustainable land use and land conservation. The key aim in this work is to combine multispectral with radar data and to evaluate their effectiveness for delineating soil degradation stages in semi-arid environments. Radar images have the advantage of being very sensitive to textural differences along land surfaces. Principal component analysis is performed on two data sets using the six reflective bands of Landsat ETM+ including the mean texture band of ERS-2 SAR and using only the six ETM+ bands. To evaluate the usefulness of the textural information for delineating the soil degradation stages an automated classification is performed on both PC data sets. The methodology for identifying soil degradation stages is performed on test sites located within an area in the Central region of Spain. Ground truth verification is carried out to confirm the results obtained. Different soil degradation stages, according to the soil surface characteristics, are successfully identified in the study area. The ERS/ETM+ based classification has significantly improved the separation of rugged landscape features along the slopes from those in the plateau area.