Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS
In mountainous and hilly areas such as Malaysia, rockfalls phenomena is a significant and ongoing threat to people and their properties in addition to infrastructure and transportation lines located within steep terrain. This is because such incidence can cause serious injuries and fatalities as...
Saved in:
Main Author: | Fanos, Ali Mutar |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2019
|
Subjects: | |
Online Access: | http://psasir.upm.edu.my/id/eprint/84166/1/FK%202019%20122%20-%20ir.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Rockfall hazard assessment based on airborne laser scanning data and GIS in tropical region
by: Fanos, Ali Mutar
Published: (2016) -
Multi remote sensing data in landslide detection and modelling
by: Jebur, Mustafa Naemah
Published: (2015) -
Landslide vulnerability and risk assessment for multihazard scenarios using airborne laser scanning data
by: Abdulwahid, Waleed Mohammed
Published: (2016) -
Optimized techniques for landslide detection and characteristics using LiDAR data
by: Mezaal, Mustafa Ridha
Published: (2018) -
Landslide Hazard Analysis Using Frequency Ratio Model
by: Jadda, Mehrnoosh
Published: (2009)