University of Extremadura

About: University of Extremadura is a education organization based out in Badajoz, Spain. It is known for research contribution in the topics: Population & Hyperspectral imaging. The organization has 7856 authors who have published 18299 publications receiving 396126 citations. The organization is also known as: Universidad de Extremadura.

Recent Developments in Endmember Extraction and Spectral Unmixing

Abstract: Spectral unmixing is an important task for remotely sensed hyperspectral data exploitation. The spectral signatures collected in natural environments are invariably a mixture of the pure signatures of the various materials found within the spatial extent of the ground instantaneous field view of the imaging instrument. Spectral unmixing aims at inferring such pure spectral signatures, called endmembers, and the material fractions, called fractional abundances, at each pixel of the scene. In this chapter, we provide an overview of existing techniques for spectral unmixing and endmember extraction, with particular attention paid to recent advances in the field such as the incorporation of spatial information into the endmember searching process, or the use of nonlinear mixture models for fractional abundance characterization. In order to substantiate the methods presented throughout the chapter, highly representative hyperspectral scenes obtained by different imaging spectrometers are used to provide a quantitative and comparative algorithm assessment. To address the computational requirements introduced by hyperspectral imaging algorithms, the chapter also includes a parallel processing example in which the performance of a spectral unmixing chain (made up of spatial–spectral endmember extraction followed by linear spectral unmixing) is accelerated by taking advantage of a low-cost commodity graphics co-processor (GPU). Combined, these parts are intended to provide a snapshot of recent developments in endmember extraction and spectral unmixing, and also to offer a thoughtful perspective on future potentials and emerging challenges in designing and implementing efficient hyperspectral imaging algorithms.

Validation of OMI‐TOMS and OMI‐DOAS total ozone column using five Brewer spectroradiometers at the Iberian peninsula

Abstract: [1] This article focuses on the comparison of the total ozone column data from the Ozone Monitoring Instrument (OMI) flying aboard the NASA EOS-Aura satellite platform with ground-based measurement recorded by Brewer spectroradiometers located at five Spanish remote sensing ground stations between January 2005 and December 2007 The satellite data are derived from two algorithms: OMI Total Ozone Mapping Spectrometer (OMI-TOMS) and OMI Differential Optical Absorption Spectroscopy (OMI-DOAS) The largest relative differences between these OMI total ozone column estimates reach 5% with a significant seasonal dependence The agreement between OMI ozone data and Brewer measurements is excellent Total ozone columns from OMI-TOMS are on average a mere 20% lower than Brewer data For OMI-DOAS data the bias is a mere 14% However, the relative difference between OMI-TOMS and Brewer measurements shows a notably lower seasonal dependence and variability than the differences between OMI-DOAS and ground-based data For both OMI ozone data products these relative differences show significant dependence on the satellite ground pixel solar zenith angle for cloud-free cases as well as for cloudy conditions However, the OMI ozone data products are shown to reveal opposite behavior with respect to the two antagonistic sky conditions No significant dependency of the ground-based to satellite-based differences with respect to the satellite cross-track position is seen for either OMI retrieval algorithm