Journal
JOURNAL OF COASTAL RESEARCH
Volume -, Issue -, Pages 197-204Publisher
COASTAL EDUCATION & RESEARCH FOUNDATION
DOI: 10.2112/SI90-024.1
Keywords
Artificial neural network; support vector machine; Brazil dam collapse; Brumadinho flood
Funding
- Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [2019R1A6A1A03033167]
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Floods are considered to be among the most devastating disasters and can threaten human life and environmental ecosystems. On January 25, 2019, the Brumadinho dam wall collapsed and waste material from the Corrego do Feijao mine flooded the area beneath the dam. At least hundreds of people were killed, animal habitats were swamped, and the flood invaded the river and agricultural fields. Brazilian authorities are examining how this destructive flood might threaten the water quality of the contaminated river. It is important to determine the flood distribution to prevent additional contamination by dangerous material from the flood. In this study, remote sensing was effectively used to map and calculate the dimensions of the flood. Pre- and post-flood images from Landsat-8 and Sentinel-2 were employed to devise a pixel-based classification using two artificial intelligence techniques: artificial neural network (ANN) and support vector machine (SVM). The flood area was successfully determined using the two classifiers. The resulting post-flood damage map should be beneficial for mitigating damage from a future flood event.
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