Research Article | OPEN ACCESS
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
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,
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.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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