Automatically Create Digital Elevation Model from Photos Captured by a Low-Cost UAV-Based System

Conference Paper (2023)
Author(s)

Kiet Tuan Nguyen (Vietnam National University, Ho Chi Minh City University of Technology (HCMUT))

Thi Anh Thu Phan (Ho Chi Minh City University of Technology (HCMUT), Vietnam National University)

Linh Hong (TU Delft - Optical and Laser Remote Sensing)

Research Group
Optical and Laser Remote Sensing
Copyright
© 2023 Kiet Tuan Nguyen, Anh Thu Thi Phan, Linh Truong-Hong
DOI related publication
https://doi.org/10.1007/978-981-99-7434-4_176
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Kiet Tuan Nguyen, Anh Thu Thi Phan, Linh Truong-Hong
Research Group
Optical and Laser Remote Sensing
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. @en
Pages (from-to)
1633-1641
ISBN (print)
['9789819974337', '978-981-99-7436-8']
ISBN (electronic)
978-981-99-7434-4
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Unmanned aerial vehicles (UAVs) are commonly utilized as cost-effective devices for data collection by capturing photos of target objects. UAV images have been used for many applications, such as civil engineering, transportation, architecture, surveying, and mapping. Although commercial UAV image data processing software is suitable for generating orthoimages and dense point clouds of surfaces, it still requires extensive labor to prepare the appropriate point cloud to create a digital elevation model (DEM). This study proposes a method to automatically create DEM from a point cloud generated from UAV images. The proposed method composes of three main steps: (1) Candidate ground points, (2) Ground points extraction, and (3) Creation of a DEM model. The proposed method was tested on three datasets, covering a total area of approximately 45 hectares from 200 images captured by DJI Phantom 4 drone. As a result, the DEMs are successfully created with a spatial resolution of 1.0 m.

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