Emerged areas around open-system lakes developing marshes are sensitive environments to climate changes. Under a semi-arid climate the sediments oxidize and dehydrate developing red colors due to iron bearing minerals. Mineral climate-dependent mixtures are spatially traced using hyperspectral imagery. Iron oxide mixtures have been mapped along differentially dehydrated units in the past 2000 years using DAIS spectrometer data. Spectral behavior
interactions and masking from iron and carbonate mixtures suffering desiccation on the sands are described on the imagery and laboratory spectra. Four morphological sandy units can be distinguished, located at different height from the lake coast-line. These units
are related to terraces, eolian deposits and desiccated areas, and appear as both continuous and remnant sparse encased surfaces showing different stages of landscape development. Mineralogical variations on iron oxides and hydroxides developed when sediments are exposed to the atmosphere are easily recorded in the visible and thermal infrared wavelength range in the imagery. Quantitative evaluation of soil color and related mineralogy is attempted.
The most prominent artifact in line scanner images is a cross track brightness gradient, which is due to sensor optics, atmospheric and surface bidirectional effects. Those effects prevent a precise intra- and intercomparison of image scenes and affect spectral ratios. A method to improve the intra- and intercomparison of a set of images of the same surface type but from different times of the day by using a simultaneous correction of bidirectional effects is presented. It should be applied after sensor, atmospheric, and geometric correction, although all four effects interact with each other. But since the method is semi-empirical in nature it will also correct partly gradients from the other effects when applied solely. The method bases on the linear semi-empirical Ambrals model (Algorithm for MODIS Bidirectional Reflectance Anisotropy of the Land Surface, Lucht 2000). A ready-to-use software in IDL has been developed for line scanner images and is made available to the public for test. The adaptation to different sensor types is straightforward. As an example, images from the DAISEX'99 campaign in Barrax, taken with the wide FOV hyperspectral sensor HyMap from different flight directions and times of the day, are modeled and corrected. An intercomparison of the images and a validation is made.
A new method to correct hyperspectral line scanner image data in airborne remote sensing for bidirectional reflectance effects is presented. Those effects prevent a precise intra- and intercomparison of image scenes and affect spectral ratios. The method bases on the linear semiempirical Ambrals model (Algorithm for MODIS Bidirectional Reflectance Anisotropy of the Land Surface, Lucht 2000). The samples for the inversion of the model are retrieved from the column averages which are calculated either over all pixels or separately over the pixels of each class of a spectral classification. The preclassification is supposed to lower the standard deviation within each column means in order to account for the different angular dependence for each surface. The data from a single scene is sufficient to perform an inversion. The application of this method to different sensor types is straightforward. As an example, images from the DAISEX'99 campaign in Barrax, taken with the wide-FOV hyperspectral sensor HyMap from different flight directions and times of the day, are modeled and corrected.
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