Unmanned Aerial Vehicles for Three‑dimensional Mapping and Change Detection Analysis

Q3 Social Sciences
Adetola Olufunmilayo Gbopa, E. Ayodele, C. Okolie, A. O. Ajayi, Chima J. Iheaturu
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引用次数: 3

Abstract

Unmanned Aerial Vehicles (UAVs), commonly known as drones are increas‐ ingly being used for three ‐dimensional (3D) mapping of the environment. This study utilised UAV technology to produce a revised 3D map of the University of Lagos as well as land cover change detection analysis. A DJI Phantom 4 UAV was used to collect digital images at a flying height of 90 m, and 75% fore and 65% side overlaps. Ground control points (GCPs) for orthophoto rectifica‐ tion were coordinated with a Trimble R8 Global Navigation Satellite System. Pix4D Mapper was used to produce a digital terrain model and an orthophoto at a ground sampling distance of 4.36 cm. The change detection analysis, using the 2015 base map as reference, revealed a significant change in the land cover such as an increase of 16,306.7 m2 in buildings between 2015 and 2019. The root mean square error analysis performed using 7 GCPs showed a horizontal and vertical accuracy of 0.183 m and 0.157 m respectively. This suggests a high level of accuracy, which is adequate for 3D mapping and change detection analysis at a sustainable cost.
无人机三维测绘与变化检测分析
无人驾驶飞行器(uav),通常被称为无人机,越来越多地被用于环境的三维(3D)测绘。这项研究利用无人机技术制作了拉各斯大学的修订3D地图以及土地覆盖变化检测分析。一架大疆幻影4无人机(DJI Phantom 4 UAV)用于收集飞行高度为90米、75%正面和65%侧面重叠的数字图像。正射影像校正的地面控制点(gcp)与Trimble R8全球导航卫星系统协调。使用Pix4D Mapper在4.36 cm的地面采样距离上生成数字地形模型和正射影像。以2015年的底图为参考,变化检测分析显示,2015年至2019年期间,土地覆盖发生了显著变化,建筑面积增加了16306.7平方米。使用7种gcp进行均方根误差分析,水平和垂直精度分别为0.183 m和0.157 m。这表明了高水平的准确性,足以在可持续的成本下进行3D映射和变化检测分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Geomatics and Environmental Engineering
Geomatics and Environmental Engineering Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
2.30
自引率
0.00%
发文量
27
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