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Descripción
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| Remote sensing can be defined as the technique that allows data acquisition of the land surface without contact with the material object of observation. The development of tools for analyzing and processing multispectral images captured by satellites has provided the automation of tasks that could not be possible otherwise. The main problem raises this discipline is the large volume of data with multidimensional nature that must be handled. The concept of spectral index emerged as an idea to reduce the number of dimensions to one and thus facilitate the study of different aspects related to the types of land cover categories that exhibits a multispectral image. A spectral index is defined as a combination of spectral bands whose function is to enhance the contribution of one type of land cover mitigating the rest of covers. In this work a no-supervised methodology to analyze and discover spectral indexes based on growing self-organizing neural network (GCS-Growing Cell Structures) is presented. | |
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Internacional
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Si |
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Nombre congreso
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2nd South-East European Conference on Computational Mechanics. SEECCM¿09 |
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Tipo de participación
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960 |
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Lugar del congreso
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Rodas. Grecia |
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Revisores
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Si |
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ISBN o ISSN
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978-960-254-683-3 |
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DOI
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Fecha inicio congreso
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22/06/2009 |
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Fecha fin congreso
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24/06/2009 |
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Desde la página
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92 |
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Hasta la página
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92 |
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Título de las actas
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2nd South-East European Conference on Computational Mechanics |