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Accuracy assessment of cross section and long section generated from DTM derived using UAV image and gps observation / Nurul Husna Shansu Baharing

This study explores an innovative approach to enhancing road construction efficiency by integrating Unmanned Aerial Vehicles (UAVs) for generating Digital Terrain Models (DTMs). UAVs have become essential tools, offering real-time, high-resolution images and data from construction sites, thereby tra...

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Main Author: Shansu Baharing, Nurul Husna
Format: Student Project
Language:English
Published: 2024
Subjects:
Geomatics
Online Access:https://ir.uitm.edu.my/id/eprint/105124/1/105124.pdf
https://ir.uitm.edu.my/id/eprint/105124/
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spelling my.uitm.ir.1051242025-03-07T08:42:45Z https://ir.uitm.edu.my/id/eprint/105124/ Accuracy assessment of cross section and long section generated from DTM derived using UAV image and gps observation / Nurul Husna Shansu Baharing Shansu Baharing, Nurul Husna Geomatics This study explores an innovative approach to enhancing road construction efficiency by integrating Unmanned Aerial Vehicles (UAVs) for generating Digital Terrain Models (DTMs). UAVs have become essential tools, offering real-time, high-resolution images and data from construction sites, thereby transforming the planning and execution phases of road construction projects. Given the increasing demand for streamlined and data-driven methods in the construction industry, the deployment of UAVs is both timely and beneficial. Traditional GPS-based methods, although precise, are labor-intensive and encounter significant difficulties, particularly in confined and deep excavation sites where signal tracking is problematic. The aim of this study is to assess UAV data by creating DTM for planning and designing road by utilizing UAVs equipped with advanced sensors and cameras. The findings reveal that UAV methods provide more reliable and accurate results compared to GPS methods. UAV-derived DTMs achieved a Root Mean Square Error (RMSE) of 0.284 meters for long sections and 0.036 meters for cross sections, demonstrating high accuracy. The greater point density of UAV-derived DTMs allows for better capture of fine-scale terrain features, whereas GPS methods showed larger errors, raising concerns about their reliability. In comparison, GPS methods offered wider coverage but required further refinement to match the accuracy levels of UAV-derived data. This study highlights the superior reliability, efficiency, and detailed terrain representation of UAVs, indicating their potential to replace traditional GPS methods in road construction projects. 2024-07 Student Project NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/105124/1/105124.pdf Accuracy assessment of cross section and long section generated from DTM derived using UAV image and gps observation / Nurul Husna Shansu Baharing. (2024) [Student Project] (Submitted)
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Geomatics
spellingShingle Geomatics
Shansu Baharing, Nurul Husna
Accuracy assessment of cross section and long section generated from DTM derived using UAV image and gps observation / Nurul Husna Shansu Baharing
description This study explores an innovative approach to enhancing road construction efficiency by integrating Unmanned Aerial Vehicles (UAVs) for generating Digital Terrain Models (DTMs). UAVs have become essential tools, offering real-time, high-resolution images and data from construction sites, thereby transforming the planning and execution phases of road construction projects. Given the increasing demand for streamlined and data-driven methods in the construction industry, the deployment of UAVs is both timely and beneficial. Traditional GPS-based methods, although precise, are labor-intensive and encounter significant difficulties, particularly in confined and deep excavation sites where signal tracking is problematic. The aim of this study is to assess UAV data by creating DTM for planning and designing road by utilizing UAVs equipped with advanced sensors and cameras. The findings reveal that UAV methods provide more reliable and accurate results compared to GPS methods. UAV-derived DTMs achieved a Root Mean Square Error (RMSE) of 0.284 meters for long sections and 0.036 meters for cross sections, demonstrating high accuracy. The greater point density of UAV-derived DTMs allows for better capture of fine-scale terrain features, whereas GPS methods showed larger errors, raising concerns about their reliability. In comparison, GPS methods offered wider coverage but required further refinement to match the accuracy levels of UAV-derived data. This study highlights the superior reliability, efficiency, and detailed terrain representation of UAVs, indicating their potential to replace traditional GPS methods in road construction projects.
format Student Project
author Shansu Baharing, Nurul Husna
author_facet Shansu Baharing, Nurul Husna
author_sort Shansu Baharing, Nurul Husna
title Accuracy assessment of cross section and long section generated from DTM derived using UAV image and gps observation / Nurul Husna Shansu Baharing
title_short Accuracy assessment of cross section and long section generated from DTM derived using UAV image and gps observation / Nurul Husna Shansu Baharing
title_full Accuracy assessment of cross section and long section generated from DTM derived using UAV image and gps observation / Nurul Husna Shansu Baharing
title_fullStr Accuracy assessment of cross section and long section generated from DTM derived using UAV image and gps observation / Nurul Husna Shansu Baharing
title_full_unstemmed Accuracy assessment of cross section and long section generated from DTM derived using UAV image and gps observation / Nurul Husna Shansu Baharing
title_sort accuracy assessment of cross section and long section generated from dtm derived using uav image and gps observation / nurul husna shansu baharing
publishDate 2024
url https://ir.uitm.edu.my/id/eprint/105124/1/105124.pdf
https://ir.uitm.edu.my/id/eprint/105124/
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score 13.244413

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