Digital terrain model application in terrain sensitivity assessment of mountainous forest in Cameron Highlands, Malaysia
Statistics has shown that Malaysia receives high frequency of landslide while Cameron Highlands (CH) is one of the landslide prone hotspots. Previous studies have been conducted on landslide assessment but most research focused on urbanised populated area and limited study was conducted in forested...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2020
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| Online Access: | http://psasir.upm.edu.my/id/eprint/99180/1/FPAS%202020%2021%20IR.pdf http://psasir.upm.edu.my/id/eprint/99180/ |
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| Summary: | Statistics has shown that Malaysia receives high frequency of landslide while Cameron Highlands (CH) is one of the landslide prone hotspots. Previous studies have been conducted on landslide assessment but most research focused on urbanised populated area and limited study was conducted in forested mountainous area of CH. Most of the Malaysian show insufficient knowledge and low awareness regard landslide issue even though landslide case is not rare in this country. Besides, Digital Terrain Model (DTM) developed by radiogrammetry technology tends to produce spatial data with high precision. However, application of DTM in terrain assessment of mountainous forest was said to be challenging due to its complex terrain structure. This study aimed to demonstrate method to map terrain morphological characteristics and establish a terrain sensitivity map in landslide prone area of CH. Moreover, this study also aimed to analyse the landslide density in forested and non forested area of CH and evaluate the accuracy of DTM application in terrain assessment of mountainous forest. DTM of CH was applied to generate the terrain parameters which are elevation, slope gradient, aspect, Length-slope Factor (LS Factor) and Topography Wetness Index (TWI). All parameters were integrated, and a terrain sensitivity map was simulated by using weighted overlay analysis. Field assessment was conducted to collect landslide coordinate as data for landslide density measurement and DTM accuracy assessment. Result shows that 35.28% of slopes which are scatterly distributed in CH are classified as high sensitive area with landslide density of 2.18unit/km. Ringlet Forest Reserve recorded the highest frequency of landslide occurrence in forested area with 9.09unit/km, and Kuala Terla area recorded 4.01unit/km in non-forested area. Map comparison with field verification suggested that the DTM based Terrain Sensitivity Map generated obtained accuracy of 79.25%. Results presented provide a significant contribution to the understanding of interactions between terrain characteristic and forest functions were critically discussed. Digital terrain analysis approach presented in this study offer alternative techniques for the assessment of micro topography in forested area, which opens up opportunity for researchers and forest practitioners to assess forest stability and structure from the perspective of terrain parameters. In addition, the difference of landslide density in forested and non-forested area emphasized the impact of forest exploitation which can raise public concern about the importance of forest conservation. Information and analytical methods discussed in this study will be beneficial for further site assessment to support sustainable land management planning, especially in the complex mountainous forest of CH. |
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