Burned area mapping in Mediterranean environment using medium-resolution multi-spectral data and a neuro-fuzzy classifier

In this study, we assess the performance of a self-organising neuro-fuzzy classifier for burned area mapping using multi-spectral satellite data. The proposed neuro-fuzzy model incorporates a multi-layered structure consisting of two types of nodes. The first type is a generic fuzzy neuron classifier (FNCs), whereas the second is solely a decision fusion operator. The Group Method of Data Handling algorithm is used for structure learning providing the model with self-organising attributes and feature selection capabilities. The resulting novel structure consists not only of layers of FNCs but also of layers with only decision fusion due to the nature of the burned area mapping problem

MITRAKIS Nikolaos;  MALLINIS Giorgos;  KOUTSIAS Nikos;  THEOCHARIS J.B.; 

2013-02-28

Taylor & Francis

JRC76751

1947–9832,   

http://www.tandfonline.com/doi/abs/10.1080/19479832.2011.635604,    https://publications.jrc.ec.europa.eu/repository/handle/JRC76751,   

10.1080/19479832.2011.635604,