Soil contamination classification based on ground penetrating radar data using support vector machine / Mohamad Adib Abdullah

Many of natural sources had been polluted such as water, air, sound and soil(mineral). This research is for making the classification of soil contamination with uncontaminated soil for sand and laterite type of soil. The contamination will be use is formed by hydrocarbon compound which was diesel. T...

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Main Author:	Abdullah, Mohamad Adib
Format:	Thesis
Language:	English
Published:	2021
Subjects:	Remote Sensing
Online Access:	https://ir.uitm.edu.my/id/eprint/42327/1/42327.pdf
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id	my-uitm-ir.42327
record_format	uketd_dc
spelling	my-uitm-ir.423272021-02-25T04:48:52Z Soil contamination classification based on ground penetrating radar data using support vector machine / Mohamad Adib Abdullah 2021-02-23 Abdullah, Mohamad Adib Remote Sensing Soils. Soil science. Including soil surveys, soil chemistry, soil structure, soil-plant relationships Many of natural sources had been polluted such as water, air, sound and soil(mineral). This research is for making the classification of soil contamination with uncontaminated soil for sand and laterite type of soil. The contamination will be use is formed by hydrocarbon compound which was diesel. This research will be conducted at test bed of GPR scanning in UiTM Perlis. After the data of contaminated and uncontaminated soil are collected, the raw data need to process using Reflexw. The preprocessing of data radar gram consists of move start time, dynamic correction, and hyperbola fitting. GPR data interpretation can be use for classify the buried feature by using machine learning. In this research the classification method that will be using Support Vector Machine (SVM) classifier. The open source provided SVM function is Waikato Environment for Knowledge Analysis (Weka). The SVM classification provided a good quality of classification. All of three soil type classification produce correct instances classified above than 95%. This classification also had been compared with logistic regression classification. The root mean square of these classification provided good result all of them were below 0.05. 2021-02 Thesis https://ir.uitm.edu.my/id/eprint/42327/ https://ir.uitm.edu.my/id/eprint/42327/1/42327.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	Remote Sensing Remote Sensing
spellingShingle	Remote Sensing Remote Sensing Abdullah, Mohamad Adib Soil contamination classification based on ground penetrating radar data using support vector machine / Mohamad Adib Abdullah
description	Many of natural sources had been polluted such as water, air, sound and soil(mineral). This research is for making the classification of soil contamination with uncontaminated soil for sand and laterite type of soil. The contamination will be use is formed by hydrocarbon compound which was diesel. This research will be conducted at test bed of GPR scanning in UiTM Perlis. After the data of contaminated and uncontaminated soil are collected, the raw data need to process using Reflexw. The preprocessing of data radar gram consists of move start time, dynamic correction, and hyperbola fitting. GPR data interpretation can be use for classify the buried feature by using machine learning. In this research the classification method that will be using Support Vector Machine (SVM) classifier. The open source provided SVM function is Waikato Environment for Knowledge Analysis (Weka). The SVM classification provided a good quality of classification. All of three soil type classification produce correct instances classified above than 95%. This classification also had been compared with logistic regression classification. The root mean square of these classification provided good result all of them were below 0.05.
format	Thesis
qualification_level	Bachelor degree
author	Abdullah, Mohamad Adib
author_facet	Abdullah, Mohamad Adib
author_sort	Abdullah, Mohamad Adib
title	Soil contamination classification based on ground penetrating radar data using support vector machine / Mohamad Adib Abdullah
title_short	Soil contamination classification based on ground penetrating radar data using support vector machine / Mohamad Adib Abdullah
title_full	Soil contamination classification based on ground penetrating radar data using support vector machine / Mohamad Adib Abdullah
title_fullStr	Soil contamination classification based on ground penetrating radar data using support vector machine / Mohamad Adib Abdullah
title_full_unstemmed	Soil contamination classification based on ground penetrating radar data using support vector machine / Mohamad Adib Abdullah
title_sort	soil contamination classification based on ground penetrating radar data using support vector machine / mohamad adib abdullah
granting_institution	Universiti Teknologi Mara Perlis
granting_department	Faculty of Architecture, Planning and Surveying
publishDate	2021
url	https://ir.uitm.edu.my/id/eprint/42327/1/42327.pdf
_version_	1783734665888137216

Soil contamination classification based on ground penetrating radar data using support vector machine / Mohamad Adib Abdullah

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