Slope safety factor mapping using drone based multispectral sensor / Mohammad Husni Sulaiman

Slope stability analysis is performed to reduce the chances to become slope failure or landslide. Thus, slope stability analysis can be interpreted in context of safety factor where the degree of slope failure risk can be determined. The aim of this project is to calculate safety factor of slope. Th...

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Main Author:	Sulaiman, Mohammad Husni
Format:	Thesis
Language:	English
Published:	2022
Subjects:	Aerial geography Slopes (Physical geography)
Online Access:	https://ir.uitm.edu.my/id/eprint/65340/1/65340.pdf
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id	my-uitm-ir.65340
record_format	uketd_dc
spelling	my-uitm-ir.653402022-09-25T16:49:28Z Slope safety factor mapping using drone based multispectral sensor / Mohammad Husni Sulaiman 2022-08-12 Sulaiman, Mohammad Husni Aerial geography Slopes (Physical geography) Slope stability analysis is performed to reduce the chances to become slope failure or landslide. Thus, slope stability analysis can be interpreted in context of safety factor where the degree of slope failure risk can be determined. The aim of this project is to calculate safety factor of slope. There are two objectives of this research which are; the first one is to compute factor of safety using selected spectral band from drone image and the second one is to produce safety of factor map. There are three datasets has been used in this project which is RGB, NIR and Thermal image. The image was given from Dr. Wahid bin Rasib in format of single picture. Then the data was processed in Agisoft software to produce orthophoto image. Because of no coordinate for NIR and RGB dataset, georeferencing in GIS software was used to set up the projection for the images. Combination of RGB and NIR image by using raster calculator tools in ArcGis was done in to produce NDVI and SAVI. Moreover, thermal image was used to derive several parameters by using algorithm from Omar, (2010) and Rahardjo et al. (1995) The parameter are soil moisture, soil mechanics properties and gravimetric water content. All those parameters will be calculated using infinite slope stability model to produce slope factor of safety map. As result, the value of factor safety in the study area is between -1.73 to 1.27 with mean of 0.82 respectively. The indicator for factor of safety is if the value <1 the slope is stable, 1, slope is between stable and unstable and 1> slope is unstable. The map factor of safety shows that 95 percent area is stable 4 percent merely stable and 1 percent is unstable. Nevertheless, comparison between NDVI and SAVI parameter with factor of safety show that those two parameters also affect slope stability. 2022-08 Thesis https://ir.uitm.edu.my/id/eprint/65340/ https://ir.uitm.edu.my/id/eprint/65340/1/65340.pdf text en public degree Universiti Teknologi Mara Perlis Faculty of Architecture, Planning and Surveying
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Aerial geography Slopes (Physical geography)
spellingShingle	Aerial geography Slopes (Physical geography) Sulaiman, Mohammad Husni Slope safety factor mapping using drone based multispectral sensor / Mohammad Husni Sulaiman
description	Slope stability analysis is performed to reduce the chances to become slope failure or landslide. Thus, slope stability analysis can be interpreted in context of safety factor where the degree of slope failure risk can be determined. The aim of this project is to calculate safety factor of slope. There are two objectives of this research which are; the first one is to compute factor of safety using selected spectral band from drone image and the second one is to produce safety of factor map. There are three datasets has been used in this project which is RGB, NIR and Thermal image. The image was given from Dr. Wahid bin Rasib in format of single picture. Then the data was processed in Agisoft software to produce orthophoto image. Because of no coordinate for NIR and RGB dataset, georeferencing in GIS software was used to set up the projection for the images. Combination of RGB and NIR image by using raster calculator tools in ArcGis was done in to produce NDVI and SAVI. Moreover, thermal image was used to derive several parameters by using algorithm from Omar, (2010) and Rahardjo et al. (1995) The parameter are soil moisture, soil mechanics properties and gravimetric water content. All those parameters will be calculated using infinite slope stability model to produce slope factor of safety map. As result, the value of factor safety in the study area is between -1.73 to 1.27 with mean of 0.82 respectively. The indicator for factor of safety is if the value <1 the slope is stable, 1, slope is between stable and unstable and 1> slope is unstable. The map factor of safety shows that 95 percent area is stable 4 percent merely stable and 1 percent is unstable. Nevertheless, comparison between NDVI and SAVI parameter with factor of safety show that those two parameters also affect slope stability.
format	Thesis
qualification_level	Bachelor degree
author	Sulaiman, Mohammad Husni
author_facet	Sulaiman, Mohammad Husni
author_sort	Sulaiman, Mohammad Husni
title	Slope safety factor mapping using drone based multispectral sensor / Mohammad Husni Sulaiman
title_short	Slope safety factor mapping using drone based multispectral sensor / Mohammad Husni Sulaiman
title_full	Slope safety factor mapping using drone based multispectral sensor / Mohammad Husni Sulaiman
title_fullStr	Slope safety factor mapping using drone based multispectral sensor / Mohammad Husni Sulaiman
title_full_unstemmed	Slope safety factor mapping using drone based multispectral sensor / Mohammad Husni Sulaiman
title_sort	slope safety factor mapping using drone based multispectral sensor / mohammad husni sulaiman
granting_institution	Universiti Teknologi Mara Perlis
granting_department	Faculty of Architecture, Planning and Surveying
publishDate	2022
url	https://ir.uitm.edu.my/id/eprint/65340/1/65340.pdf
_version_	1783735548535373824

Slope safety factor mapping using drone based multispectral sensor / Mohammad Husni Sulaiman

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