Title:	Landscape discrimination in Brazil using hyperion data and self-organizing map approach.
Authors:	VICENTE, L. E. FRIEDEL, M. J. IWASHITA, F.
Affiliation:	LUIZ EDUARDO VICENTE, CNPM; MICHAEL J. FRIEDEL, UNITED STATES GEOLOGICAL SURVEY; FABIO IWASHITA, DESERT RESEARCH INSTITUTE.
Date Issued:	2011
Citation:	In: AGU FALL MEETING, 2011, San Francisco. Anais... San Francisco: AGU, 2011.
Description:	We demonstrate the efficacy of an unsupervised artificial neural network, called a self-organizing map (SOM), to facilitate modeling and classifying targets based on images from the EO1-Hyperion hyperspectral sensor. The proposed methodology is able to discriminate signals obtained from a spectral library indentifying landscape elements in Brazil, such as different types of soil, pastures and grasslands at a larger scale.
Thesagro:	Sensoriamento Remoto
Type of Material:	Resumo em anais e proceedings
Access:	openAccess
Appears in Collections:	Resumo em anais de congresso (CNPM)