Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Assessment of DSM Based on Radiometric Transformation of UAV Data
Department of Geoinformation, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia (UTM), Johor Bahru 81310, Malaysia. Centre of GIS, University of the Punjab, Lahore 54590, Pakistan.
Department of Geoinformation, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia (UTM), Johor Bahru 81310, Malaysia.
Centre of GIS, University of the Punjab, Lahore 54590, Pakistan.
Punjab University College of Information Technology, University of the Punjab, Lahore 54590, Pakistan.
Show others and affiliations
2021 (English)In: Sensors, E-ISSN 1424-8220, Vol. 21, no 5, article id 1649Article in journal (Refereed) Published
Abstract [en]

Unmanned Aerial Vehicle (UAV) is one of the latest technologies for high spatial resolution 3D modeling of the Earth. The objectives of this study are to assess low-cost UAV data using image radiometric transformation techniques and investigate its effects on global and local accuracy of the Digital Surface Model (DSM). This research uses UAV Light Detection and Ranging (LIDAR) data from 80 meters and UAV Drone data from 300 and 500 meters flying height. RAW UAV images acquired from 500 meters flying height are radiometrically transformed in Matrix Laboratory (MATLAB). UAV images from 300 meters flying height are processed for the generation of 3D point cloud and DSM in Pix4D Mapper. UAV LIDAR data are used for the acquisition of Ground Control Points (GCP) and accuracy assessment of UAV Image data products. Accuracy of enhanced DSM with DSM generated from 300 meters flight height were analyzed for point cloud number, density and distribution. Root Mean Square Error (RMSE) value of Z is enhanced from ±2.15 meters to 0.11 meters. For local accuracy assessment of DSM, four different types of land covers are statistically compared with UAV LIDAR resulting in compatibility of enhancement technique with UAV LIDAR accuracy. 

Place, publisher, year, edition, pages
Switzerland: MDPI, 2021. Vol. 21, no 5, article id 1649
Keywords [en]
RAW image, UAV image transformation, UAV drone, point cloud, tie points, UAV LIDAR
National Category
Geotechnical Engineering
Research subject
Soil Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-83096DOI: 10.3390/s21051649ISI: 000628584300001PubMedID: 33673425Scopus ID: 2-s2.0-85101702125OAI: oai:DiVA.org:ltu-83096DiVA, id: diva2:1531871
Note

Validerad;2021;Nivå 2;2021-03-01 (johcin)

Available from: 2021-02-27 Created: 2021-02-27 Last updated: 2023-09-05Bibliographically approved

Open Access in DiVA

fulltext(5363 kB)389 downloads
File information
File name FULLTEXT01.pdfFile size 5363 kBChecksum SHA-512
6d78156b9c90f5374688c9238cf215db7c1506fe4ce84ddd903998ece15edaeb490736dea679a880151e433b9afbd1bb502a47043f10fb135874caf2271f00b2
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMedScopus

Authority records

Al-Ansari, Nadhir

Search in DiVA

By author/editor
Al-Ansari, Nadhir
By organisation
Mining and Geotechnical Engineering
In the same journal
Sensors
Geotechnical Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 398 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 115 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf