Geology and landslide susceptibility assessment using Geographic Information System (GIS) in Aring, Gua Musang Kelantan
Aring is located in Gua Musang District, Kelantan which are very prone to have a geological hazard such as floods. It is also very vulnerable to landslide in some areas of Aring which does contributes to life losses and properties damages such as house and vehicles. The study area is located in Arin...
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| Format: | Undergraduate Final Project Report |
| Language: | English |
| Published: |
2021
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| Online Access: | http://discol.umk.edu.my/id/eprint/13089/1/Nurul%20Najiha%20Yahaya.pdf http://discol.umk.edu.my/id/eprint/13089/ |
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| Summary: | Aring is located in Gua Musang District, Kelantan which are very prone to have a geological hazard such as floods. It is also very vulnerable to landslide in some areas of Aring which does contributes to life losses and properties damages such as house and vehicles. The study area is located in Aring 6 with the are covered of 5km2 along the latitute 4° 55’ 30.00’’N to 4° 58’ 0’’N and longitude 102° 22' 30.00’’E to 102° 25' 30.00’’E. This study aims to update a geological map of Aring 6 with scale of 1:25 000 and to generate a landslide susceptibility map. The factors that influenced the landslide in Aring, Gua Musang were also identified based on the parameters. The research does involves the study of geomorphology, stratigraphy, structural geology and historical geology of the study area. The method that will be using in this research study is by overlays all the data by using the weighted overlay method in ArcGis and also by generating the probability calculation with the area under the curve (AUC). The study area was composed by Aring Formation which were divided into four lithologies unites. The parameters that caused the potential landslides such as the lithology, drainage, slope and aspect were also classified and the landslides susceptibility map was produced in ArcGIS software by using probability method. Results showed that the susceptibility map was categorized into three classes which are low, medium and high classes that is prone to have landslides in the future. Heavy rainfall intensity was identified as the factors that triggered the landslide. As a conclusion, the ability to identify landslides will provide a better knowlegde and understanding to the society on the landslide mechanisms and will also provide a better prevention of the most likely failure area that have high prone landslide for the future management. |
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