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     Research Journal of Applied Sciences, Engineering and Technology


Review of Visualization Techniques for Landslide and Flood Disaster Data

Salman Yussof, Noor Bahirah Husin, Zailani Ibrahim, Marina Md Din, Azimah Abdul Ghapar, Norashidah Md Din and Fairuz Abdullah
College of Information Technologi, Universiti Tenaga Nasional, Jalan Ikram-Uniten, Malaysia
Research Journal of Applied Sciences, Engineering and Technology  2015  9:700-705
http://dx.doi.org/10.19026/rjaset.9.2614  |  © The Author(s) 2015
Received: August ‎13, ‎2014  |  Accepted: September ‎23, ‎2014  |  Published: March 25, 2015

Abstract

The aim of this study is to review the data visualization techniques that have been used for landslide and flood research. Landslide and flood are two of the natural disasters that commonly occur in Malaysia. Due to the large amount of damage that both landslide and flood can cause, it is important for researchers to predict where and when these two disasters will occur and the extent of damage that can happen. Data visualization techniques have been used by researchers in both areas to facilitate them in making a better prediction. However, data visualization techniques are used differently in the two areas. In landslide research, the visualizations techniques are used to visualize monitored landslide data. In flood research, the visualization techniques are used to visualize the predicted impact of flood, where they are used as a component in a flood simulation system. In both cases, data visualization technique has not been used to its full potential and this opens up a door for further research opportunities with regard to using data visualization to improve our prediction on landslide and flood occurrence.

Keywords:

Flood, landslide, natural disaster, visualization techniques,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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