Abstract
This paper presents a new approach to flood mapping using satellite synthetic-aperture radar (SAR) images that is based on intelligent tech- break niques. 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.
Keywords
Cite this article
@article{cai-18144,
author = {Sergii Skakun},
title = {A Neural Network Approach to Flood Mapping Using Satellite Imagery},
journal = {Computing and Informatics},
volume = {29},
number = {6},
pages = {1013--1024},
year = {2010},
issn = {1335-9150},
url = {https://cai.type.sk/content/2010/6/a-neural-network-approach-to-flood-mapping-using-satellite-imagery/}
}
TY - JOUR AU - Sergii Skakun TI - A Neural Network Approach to Flood Mapping Using Satellite Imagery JO - Computing and Informatics VL - 29 IS - 6 SP - 1013 EP - 1024 PY - 2010 SN - 1335-9150 UR - https://cai.type.sk/content/2010/6/a-neural-network-approach-to-flood-mapping-using-satellite-imagery/ KW - Flood mapping KW - neural networks KW - self-organising Kohonen maps KW - synthetic aperture radar ER -
Skakun, S. (2010). A Neural Network Approach to Flood Mapping Using Satellite Imagery. Computing and Informatics, 29(6), 1013–1024. https://cai.type.sk/content/2010/6/a-neural-network-approach-to-flood-mapping-using-satellite-imagery/