Diferencia entre revisiones de «KES2008-hyper»
Sin resumen de edición |
Sin resumen de edición |
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Línea 1: | Línea 1: | ||
Title: Hyperspectral imagery analysis for remote sensing: methods and applications | Title: Hyperspectral imagery analysis for remote sensing: methods and applications | ||
Description: Hyperspectral data analysis is a very active field due to the great | Description: Hyperspectral data analysis is a very active field due to the great improvenet in remote sensing and the exponentially grow of data flow from in-orbit instruments. The fields of applicability are extensive. Geoscience tools are demanded for disasters prevision, environmental analysis, security. The investigation of new tools capable of predict, monitor and assist in preparation of strategies to minimize the damage produced by natural and human-made disasters would contribute to a better quality of life and to the reduction of economical losses. The purpose of this invited session in KES 2008 is to present and discuss researches on methods for hyperspectral imagery analysis and theirs applications. | ||
Topics: | Topics: | ||
Hyperspectral data acquisition | Hyperspectral data acquisition | ||
Unmixing methods | Unmixing methods | ||
Spatial and spectral characterization | Spatial and spectral characterization | ||
Classification | Classification | ||
Analysis of hyperspectral data | Analysis of hyperspectral data | ||
Applications | Applications |
Revisión del 16:57 30 nov 2007
Title: Hyperspectral imagery analysis for remote sensing: methods and applications
Description: Hyperspectral data analysis is a very active field due to the great improvenet in remote sensing and the exponentially grow of data flow from in-orbit instruments. The fields of applicability are extensive. Geoscience tools are demanded for disasters prevision, environmental analysis, security. The investigation of new tools capable of predict, monitor and assist in preparation of strategies to minimize the damage produced by natural and human-made disasters would contribute to a better quality of life and to the reduction of economical losses. The purpose of this invited session in KES 2008 is to present and discuss researches on methods for hyperspectral imagery analysis and theirs applications.
Topics:
Hyperspectral data acquisition
Unmixing methods
Spatial and spectral characterization
Classification
Analysis of hyperspectral data
Applications