Steep slope DEM model construction based on the unmanned aerial vehicle (UAV) images

The DEM construction of high and steep slope has great importance to slope disaster monitoring. The conventional method used to construct high and steep slope DEM model requires larger field surveying workload. First of all, the high and steep slope image was obtained through unmanned aerial vehicle...

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Main Authors: Xi, Wenfei, Li, Dongsheng
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2017
Online Access:http://journalarticle.ukm.my/11678/
http://journalarticle.ukm.my/11678/
http://journalarticle.ukm.my/11678/1/12%20SM46%2011.pdf
id ukm-11678
recordtype eprints
spelling ukm-116782018-05-28T00:40:02Z http://journalarticle.ukm.my/11678/ Steep slope DEM model construction based on the unmanned aerial vehicle (UAV) images Xi, Wenfei Li, Dongsheng The DEM construction of high and steep slope has great importance to slope disaster monitoring. The conventional method used to construct high and steep slope DEM model requires larger field surveying workload. First of all, the high and steep slope image was obtained through unmanned aerial vehicle (UAV) platform; Then the SIFT algorithm is used to extract the feature points which are going to be matched accurately by using RANSAC algorithm. Finally, stereo pair splicing method is used to generate orthogonal images and construct DEM model. After comparing the DEM model with actual slope measurement result collected by total station finding, it is shown that elevation error between the DEM model constructed by unmanned aerial vehicle (UAV) and actual measurement is minimal and its efficiency is proven. Penerbit Universiti Kebangsaan Malaysia 2017-11 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/11678/1/12%20SM46%2011.pdf Xi, Wenfei and Li, Dongsheng (2017) Steep slope DEM model construction based on the unmanned aerial vehicle (UAV) images. Sains Malaysiana, 46 (11). pp. 2119-2124. ISSN 0126-6039 http://www.ukm.my/jsm/english_journals/vol46num11_2017/contentsVol46num11_2017.htm
repository_type Digital Repository
institution_category Local University
institution Universiti Kebangasaan Malaysia
building UKM Institutional Repository
collection Online Access
language English
description The DEM construction of high and steep slope has great importance to slope disaster monitoring. The conventional method used to construct high and steep slope DEM model requires larger field surveying workload. First of all, the high and steep slope image was obtained through unmanned aerial vehicle (UAV) platform; Then the SIFT algorithm is used to extract the feature points which are going to be matched accurately by using RANSAC algorithm. Finally, stereo pair splicing method is used to generate orthogonal images and construct DEM model. After comparing the DEM model with actual slope measurement result collected by total station finding, it is shown that elevation error between the DEM model constructed by unmanned aerial vehicle (UAV) and actual measurement is minimal and its efficiency is proven.
format Article
author Xi, Wenfei
Li, Dongsheng
spellingShingle Xi, Wenfei
Li, Dongsheng
Steep slope DEM model construction based on the unmanned aerial vehicle (UAV) images
author_facet Xi, Wenfei
Li, Dongsheng
author_sort Xi, Wenfei
title Steep slope DEM model construction based on the unmanned aerial vehicle (UAV) images
title_short Steep slope DEM model construction based on the unmanned aerial vehicle (UAV) images
title_full Steep slope DEM model construction based on the unmanned aerial vehicle (UAV) images
title_fullStr Steep slope DEM model construction based on the unmanned aerial vehicle (UAV) images
title_full_unstemmed Steep slope DEM model construction based on the unmanned aerial vehicle (UAV) images
title_sort steep slope dem model construction based on the unmanned aerial vehicle (uav) images
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2017
url http://journalarticle.ukm.my/11678/
http://journalarticle.ukm.my/11678/
http://journalarticle.ukm.my/11678/1/12%20SM46%2011.pdf
first_indexed 2023-09-18T20:00:53Z
last_indexed 2023-09-18T20:00:53Z
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