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Gamba, P.
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Gamba, P.
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- PublicationOpen AccessHySenS data exploitation for urban land cover analysis(2006-02)
; ; ; ; ; ; ; ; ; ; ; ;Dell’Acqua, F.; Dipartimento di Elettronica, Facoltà di Ingegneria, Università degli Studi di Pavia, Italy ;Gamba, P.; Dipartimento di Elettronica, Facoltà di Ingegneria, Università degli Studi di Pavia, Italy ;Casella, V.; Dipartimento di Ingegneria Edile e del Territorio (DIET), Facoltà di Ingegneria, Università degli Studi di Pavia, Italy ;Zucca, F.; Dipartimento di Scienze della Terra, Facoltà di Scienze Matematiche Fisiche e Naturali, Università degli Studi di Pavia, Italy ;Benediktsson, J. A.; Department of Electrical and Computer Engineering, University of Iceland, Reyjkavik, Iceland ;Wilkinson, G.; General Faculty of Technology, Lincoln University, Lincoln, U.K. ;Galli, A.; Facoltà di Agraria, Università Politecnica delle Marche, Ancona, Italy ;Malinverni, E. S.; Facoltà di Ingegneria, Università Politecnica delle Marche, Ancona, Italy ;Jones, G.; Digital Imaging Research Centre, School of Computing and Information Systems, Kingston University, Surrey, U.K. ;Greenhill, D.; Digital Imaging Research Centre, School of Computing and Information Systems, Kingston University, Surrey, U.K. ;Ripke, L.; Digital Imaging Research Centre, School of Computing and Information Systems, Kingston University, Surrey, U.K.; ; ; ; ; ; ; ; ; ; This paper addresses the use of HySenS airborne hyperspectral data for environmental urban monitoring. It is known that hyperspectral data can help to characterize some of the relations between soil composition, vegetation characteristics, and natural/artificial materials in urbanized areas. During the project we collected DAIS and ROSIS data over the urban test area of Pavia, Northern Italy, though due to a late delivery of ROSIS data only DAIS data was used in this work. Here we show results referring to an accurate characterization and classification of land cover/use, using different supervised approaches, exploiting spectral as well as spatial information. We demonstrate the possibility to extract from the hyperspectral data information which is very useful for environmental characterization of urban areas.268 244