A Neural Network Approach to Flood Mapping Using Satellite Imagery
Sergii Skakun
Computing and Informatics, Tome 28 (2012) no. 1, / Harvested from Computing and Informatics
Text on Computing and Informatics
This paper presents a new approach to flood mapping using satellite synthetic-aperture radar (SAR) images that is based on intelligent techniques. In particular, we apply artificial neural networks, self-organizing Kohonen's maps (SOMs), for SAR image segmentation and classification. Our approach was used to process data from different satellite SAR instruments (ERS-2/SAR, ENVISAT/ASAR, RADARSAT-1) for different flood events: the Tisza river, Ukraine and Hungary, 2001; the Huaihe river, China, 2007; the Mekong river, Thailand and Laos, 2008; and the Koshi river, India and Nepal, 2008.
Publié le : 2012-01-26
Classification:  Flood mapping; neural networks; self-organising Kohonen maps; synthetic aperture radar 
@article{cai127,
     author = {Sergii Skakun},
     title = {A Neural Network Approach to Flood Mapping Using Satellite Imagery},
     journal = {Computing and Informatics},
     volume = {28},
     number = {1},
     year = {2012},
     language = {en},
     url = {http://dml.mathdoc.fr/item/cai127}
}

Sergii Skakun. A Neural Network Approach to Flood Mapping Using Satellite Imagery. Computing and Informatics, Tome 28 (2012) no. 1, . http://gdmltest.u-ga.fr/item/cai127/