Natural Disaster Detection Using Wavelet and Artificial Neural Network

Santoso, Albertus Joko and Dewi, Findra Kartika Sari and Sidhi, Thomas Adi Purnomo (2015) Natural Disaster Detection Using Wavelet and Artificial Neural Network. In: Science and Information Conference 2015. he Science and Information (SAI) Organization Limited, London, United Kingdom, pp. 761-764. ISBN 978-1-4799-8546-3

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Text (Albertus Joko Santoso, Findra Kartika Sari Dewi and Thomas Adi Purnomo Sidhi) 52. Natural Disaster Detection Using Wavelet and Artifical Neural Network.pdf Download (5MB) | Preview

Abstract

Indonesia, by the location of its geographic and geologic, it have more potential encounters for natural disasters. This nation is traversed by three tectonic plates, namely: IndoAustralian, the Eurasian and the Pacific plates. One of the tools employed to detect danger and send an early disaster warning is sensor device for ocean waves, but it has drawbacks related to the very limited time gap between information/warnings obtained and the real disaster event, which is only less than 30 minutes. Natural disaster early detection information system is essential to prevent potential danger. The system can make use of the pattern recognition of satellite imagery sequences that take place before and during the natural disaster. This study is conducted to determine the right wavelet to compress the satellite image sequences and to perform the pattern recognition process of a natural disaster employing an artificial neural network. This study makes use of satellite imagery sequences of tornadoes and hurricanes.

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