Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti

Types of pavement distress include potholes, cracks and rutting. The most dangerous and common form of road defect is the pothole. Effective data collection of pothole geometry information can assist in road maintenance project. It is necessary in estimating a logistic need which can help Authoritie...

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Main Author:	Abd Mukti, Shahrul Nizan
Format:	Thesis
Language:	English
Published:	2022
Subjects:	Pavements and paved roads Aircraft
Online Access:	https://ir.uitm.edu.my/id/eprint/76663/1/76663.pdf
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id	my-uitm-ir.76663
record_format	uketd_dc
spelling	my-uitm-ir.766632023-05-29T04:20:43Z Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti 2022 Abd Mukti, Shahrul Nizan Pavements and paved roads Aircraft Types of pavement distress include potholes, cracks and rutting. The most dangerous and common form of road defect is the pothole. Effective data collection of pothole geometry information can assist in road maintenance project. It is necessary in estimating a logistic need which can help Authorities in distribute their budget projection. Pavement damage involving spectral features has limitations with the RGB format. In the field of remote sensing, road distress in the form of spectral features has been characterised by Multispectral (MS) images that have coverage with broad wavelengths. This study extracted pothole area and volume information from fusion of Digital Elevation Model (DEM) and classified MS image. The study set four main objectives to achieve its aim: (1) To analyse RGB and multispectral sensor calibration, (2) To evaluate the optimal flight parameters for pothole modelling production using RGB imagery, (3) To investigate various classifier algorithms and band combinations for pothole region areas using multispectral imagery and (4) To validate geometric information from the extracted pothole. Three (3) chequerboards were used in camera calibration to find an optimal camera parameter. 50mm size of chequerboard pattern yielded the lowest pre-projection error while there’s no guaranteed in having better projection by increased the focal length of the camera. Meanwhile, nine (9) classifier algorithms and forty (40) band stack combinations were deployed to classify the pothole edge. The most significant classifier algorithms to distinguish a pothole defect is Maximum likelihood with 29 over 40 band combination win rate. The lowest error of pothole polygon classification is 0.016m² from classification of Mahalanobis distance algorithm with NIR + red edge + red or Green + red edge + red combination. For volume estimation purpose, a Digital Elevation Models (DEM) were generated from photogrammetric method with flight parameters of three (3) different camera focal length and ten (10) UAV altitude. The optimal flight parameters for accurate fill-in volume estimation is at 8 m and 10 m flight altitude, with the 3.61 mm and 8.8 mm of focal lengths, respectively. These results confirmed that the UAV is a very useful form of technology in road maintenance applications, at the same time, contributing in alternative method of pothole information extraction. The information gathered is useful for Authorities, concession expressway company and interest party for better road maintenance implementation. 2022 Thesis https://ir.uitm.edu.my/id/eprint/76663/ https://ir.uitm.edu.my/id/eprint/76663/1/76663.pdf text en public phd doctoral Universiti Teknologi MARA (UiTM) Faculty of Architecture, Planning and Surveying Tahar, Khairul Nizam
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Tahar, Khairul Nizam
topic	Pavements and paved roads Aircraft
spellingShingle	Pavements and paved roads Aircraft Abd Mukti, Shahrul Nizan Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
description	Types of pavement distress include potholes, cracks and rutting. The most dangerous and common form of road defect is the pothole. Effective data collection of pothole geometry information can assist in road maintenance project. It is necessary in estimating a logistic need which can help Authorities in distribute their budget projection. Pavement damage involving spectral features has limitations with the RGB format. In the field of remote sensing, road distress in the form of spectral features has been characterised by Multispectral (MS) images that have coverage with broad wavelengths. This study extracted pothole area and volume information from fusion of Digital Elevation Model (DEM) and classified MS image. The study set four main objectives to achieve its aim: (1) To analyse RGB and multispectral sensor calibration, (2) To evaluate the optimal flight parameters for pothole modelling production using RGB imagery, (3) To investigate various classifier algorithms and band combinations for pothole region areas using multispectral imagery and (4) To validate geometric information from the extracted pothole. Three (3) chequerboards were used in camera calibration to find an optimal camera parameter. 50mm size of chequerboard pattern yielded the lowest pre-projection error while there’s no guaranteed in having better projection by increased the focal length of the camera. Meanwhile, nine (9) classifier algorithms and forty (40) band stack combinations were deployed to classify the pothole edge. The most significant classifier algorithms to distinguish a pothole defect is Maximum likelihood with 29 over 40 band combination win rate. The lowest error of pothole polygon classification is 0.016m² from classification of Mahalanobis distance algorithm with NIR + red edge + red or Green + red edge + red combination. For volume estimation purpose, a Digital Elevation Models (DEM) were generated from photogrammetric method with flight parameters of three (3) different camera focal length and ten (10) UAV altitude. The optimal flight parameters for accurate fill-in volume estimation is at 8 m and 10 m flight altitude, with the 3.61 mm and 8.8 mm of focal lengths, respectively. These results confirmed that the UAV is a very useful form of technology in road maintenance applications, at the same time, contributing in alternative method of pothole information extraction. The information gathered is useful for Authorities, concession expressway company and interest party for better road maintenance implementation.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Abd Mukti, Shahrul Nizan
author_facet	Abd Mukti, Shahrul Nizan
author_sort	Abd Mukti, Shahrul Nizan
title	Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
title_short	Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
title_full	Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
title_fullStr	Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
title_full_unstemmed	Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
title_sort	photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / shahrul nizan abd mukti
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Architecture, Planning and Surveying
publishDate	2022
url	https://ir.uitm.edu.my/id/eprint/76663/1/76663.pdf
_version_	1783736116973666304

Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti

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