Landslide susceptibility modelling using GIS and Random Forest Machine Learning

• Main Author: Soo, Neng Wu
• Format: Final Year Project
• Language: English
• Published: Universiti Teknologi PETRONAS 2020
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://utpedia.utp.edu.my/20989/1/CV50_23383_2SET_wordthesis.pdf; http://utpedia.utp.edu.my/20989/

Landslide a disaster that often occurs due to human intervention and it requires more attention nowadays more than ever since people that have been impacted by the aftermath of such incidents significantly, especially to those who tends to live and work in country or a part of an area that are made up of mountains where the gradient of the slope is generally steeper. The aftermath of landslides caused wide ranges of adversary effects in the past and still do now. Property are destroyed or damaged, people who affected are injured or possibly death; even after the disaster, ruptured or blocked roadways due to landslides cut off connections that requires the road for the vehicles to pass. Several precautions can be made to deduce its negative effects on the society. In such occasion, the development of the LSM will be considered a vital step to tackle the problems as it provides required information and turns it into a plan on which area is the most vulnerable against landslide to occur.