IJESD 2016 Vol.7(1): 41-45 ISSN: 2010-0264
DOI: 10.7763/IJESD.2016.V7.738
DOI: 10.7763/IJESD.2016.V7.738
Early Detection of Spots High Water Saturation for Landslide Prediction Using Thermal Imaging Analysis
Aufa Zin, Kamarul Hawari, and Norliana Khamisan
Abstract—Nowadays, landslide phenomenon has become a
serious problem in Malaysia. Landslide can cause human injury,
loss of life and economical problem. One of the factors is due to
the heavy rain. Hence, to overcome this problem, this study
investigates a new method to detect spots of high water
saturation which is integrated with a thermal camera system to
provide early detection of landslide. The thermal camera is
selected because it provides accurate predict where landslide
going to occur. Thermal camera can be used to detect spots of
high water saturation which is a key component that contributes
to landslide activity. The analysis is done using 10 images. It was
tested to see the accuracy of this technique. From the
observation, this technique is quite accurate but still has their
weakness and error.
Index Terms—Landslides, thermal camera, morphological techniques, color thresholding.
The authors are with the Electrical and Electronics Engineering Faculty, Universiti Malaysia Pahang, 26600 Pekan Pahang, Malaysia (e-mail: aufahuda@gmail.com).
Index Terms—Landslides, thermal camera, morphological techniques, color thresholding.
The authors are with the Electrical and Electronics Engineering Faculty, Universiti Malaysia Pahang, 26600 Pekan Pahang, Malaysia (e-mail: aufahuda@gmail.com).
Cite: Aufa Zin, Kamarul Hawari, and Norliana Khamisan, "Early Detection of Spots High Water Saturation for Landslide Prediction Using Thermal Imaging Analysis," International Journal of Environmental Science and Development vol. 7, no. 1, pp. 41-45, 2016.
General Information
- ISSN: 2010-0264 (Print); 2972-3698 (Online)
- Abbreviated Title: Int. J. Environ. Sci. Dev.
- Frequency: Bimonthly
- DOI: 10.18178/IJESD
- Editor-in-Chief: Prof. Richard Haynes
- Managing Editor: Ms. Cherry L. Chen
- Indexing: Scopus (CiteScore 2022: 1.4), Google Scholar, CNKI, ProQuest, EBSCO, etc.
- E-mail: ijesd@ejournal.net
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