Growing Cell Structures Neural Networks for Designing Spectral Indexes

Delgado Sanz, Maria Soledad and Gonzalo Martín, Consuelo and Martínez Izquierdo, María Estíbaliz and Arquero Hidalgo, Águeda (2010). Growing Cell Structures Neural Networks for Designing Spectral Indexes. "Journal of the Serbian Society for Computational Mechanics", v. 4 (n. 1); pp. 1-15. ISSN 1820-6530.

Description

Title: Growing Cell Structures Neural Networks for Designing Spectral Indexes
Author/s:
  • Delgado Sanz, Maria Soledad
  • Gonzalo Martín, Consuelo
  • Martínez Izquierdo, María Estíbaliz
  • Arquero Hidalgo, Águeda
Item Type: Article
Título de Revista/Publicación: Journal of the Serbian Society for Computational Mechanics
Date: January 2010
ISSN: 1820-6530
Volume: 4
Subjects:
Faculty: Facultad de Informática (UPM)
Department: Arquitectura y Tecnología de Sistemas Informáticos
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Remote sensing can be defined as the technique that facilitates the acquisition of land surface data without contact with the material object of observation. The development of tools for analyzing and processing multispectral images captured by sensors aboard satellites has provided the automation of tasks that could not be possible otherwise. The main problem related with this discipline is the large volume of data of 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 features associated to the types of land cover categories that exhibits a multispectral image. Formally, 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.

More information

Item ID: 9449
DC Identifier: http://oa.upm.es/9449/
OAI Identifier: oai:oa.upm.es:9449
Official URL: http://www.sscm.kg.ac.rs/jsscm/
Deposited by: Memoria Investigacion
Deposited on: 11 Mar 2013 13:06
Last Modified: 20 Apr 2016 17:51
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