SYNERGISTIC USE OF HYPERSPECTRAL AND MULTISPECTRAL DATA FOR IDENTIFICATION AND MONITORING OF SALINITY IN MEDITERRANEAN ENVIRONMENTS

The main aim of the study is to apply hyperspectral and multispectral data in order to identify and monitor change in soil salinity for Mediterranean environments. This is expressed principally by changes in the nature and characteristics of the soil and vegetation in the semi-arid area of La Mancha Alta, Spain.

Spectral unmixing is used to represent the spatial variation in the proportions of basic elements (end-members), which describe types of land covers specific for the study area. End-members are identified and characterized using field spectroradiometry combined with airborne hyperspectral imagery from DAIS. A spectral library has been constructed and includes a detailed field study with laboratory data and X-ray diffraction analysis.

Characteristics of the end-members from hyperspectral imagery (DAIS 7915) are determined and implemented in multispectral imagery (Landsat ETM+ and TM). Spectral weighting coefficients are used to generalize spectra from the DAIS to the ETM+ wavebands, and a Point Spread Function (PSF) of the ETM+ provides a means of spatial generalization. A subset-based spectral unmixing using simulated ETM+ end-members is applied to the ETM+ and TM images.

The results show a spatial distribution of soil salinity and temporal change in the salinity extension over a period of fourteen years. The data generated are related to location, nature, extent and direction of the change of salinity. These results have a relevant interest in the monitoring of salinity in Mediterranean environments.