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Landslide susceptibility modelling using GIS and Random Forest Machine Learning

Soo, Neng Wu (2020) Landslide susceptibility modelling using GIS and Random Forest Machine Learning. Universiti Teknologi PETRONAS. (Submitted)

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Abstract

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.

Item Type: Final Year Project
Academic Subject : Academic Department - Civil Engineering - Water and environment - Water
Subject: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Engineering > Civil
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 12 Sep 2021 22:14
Last Modified: 12 Sep 2021 22:14
URI: http://utpedia.utp.edu.my/id/eprint/20989

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