Cargando…

Accuracy Analysis of a New Data Processing Method for Landslide Monitoring Based on Unmanned Aerial System Photogrammetry

One of the most commonly used surveying techniques for landslide monitoring is a photogrammetric survey using an Unmanned Aerial System (UAS), where landslide displacements can be determined by comparing dense point clouds, digital terrain models, and digital orthomosaic maps resulting from differen...

Descripción completa

Detalles Bibliográficos
Autores principales: Jakopec, Ivan, Marendić, Ante, Grgac, Igor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10054903/
https://www.ncbi.nlm.nih.gov/pubmed/36991810
http://dx.doi.org/10.3390/s23063097
_version_ 1785015783975288832
author Jakopec, Ivan
Marendić, Ante
Grgac, Igor
author_facet Jakopec, Ivan
Marendić, Ante
Grgac, Igor
author_sort Jakopec, Ivan
collection PubMed
description One of the most commonly used surveying techniques for landslide monitoring is a photogrammetric survey using an Unmanned Aerial System (UAS), where landslide displacements can be determined by comparing dense point clouds, digital terrain models, and digital orthomosaic maps resulting from different measurement epochs. A new data processing method for calculating landslide displacements based on UAS photogrammetric survey data is presented in this paper, whose main advantage is the fact that it does not require the production of the above-mentioned products, enabling faster and simpler displacement determination. The proposed method is based on matching features between the images from two different UAS photogrammetric surveys and calculating the displacements based only on the comparison of two reconstructed sparse point clouds. The accuracy of the method was analyzed on a test field with simulated displacements and on an active landslide in Croatia. Moreover, the results were compared with the results obtained with a commonly used method based on comparing manually tracked features on orthomosaics from different epochs. Analysis of the test field results using the presented method show the ability to determine displacements with a centimeter level accuracy in ideal conditions even with a flight height of 120 m, and on the Kostanjek landslide with a sub-decimeter level accuracy.
format Online
Article
Text
id pubmed-10054903
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-100549032023-03-30 Accuracy Analysis of a New Data Processing Method for Landslide Monitoring Based on Unmanned Aerial System Photogrammetry Jakopec, Ivan Marendić, Ante Grgac, Igor Sensors (Basel) Article One of the most commonly used surveying techniques for landslide monitoring is a photogrammetric survey using an Unmanned Aerial System (UAS), where landslide displacements can be determined by comparing dense point clouds, digital terrain models, and digital orthomosaic maps resulting from different measurement epochs. A new data processing method for calculating landslide displacements based on UAS photogrammetric survey data is presented in this paper, whose main advantage is the fact that it does not require the production of the above-mentioned products, enabling faster and simpler displacement determination. The proposed method is based on matching features between the images from two different UAS photogrammetric surveys and calculating the displacements based only on the comparison of two reconstructed sparse point clouds. The accuracy of the method was analyzed on a test field with simulated displacements and on an active landslide in Croatia. Moreover, the results were compared with the results obtained with a commonly used method based on comparing manually tracked features on orthomosaics from different epochs. Analysis of the test field results using the presented method show the ability to determine displacements with a centimeter level accuracy in ideal conditions even with a flight height of 120 m, and on the Kostanjek landslide with a sub-decimeter level accuracy. MDPI 2023-03-14 /pmc/articles/PMC10054903/ /pubmed/36991810 http://dx.doi.org/10.3390/s23063097 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Jakopec, Ivan
Marendić, Ante
Grgac, Igor
Accuracy Analysis of a New Data Processing Method for Landslide Monitoring Based on Unmanned Aerial System Photogrammetry
title Accuracy Analysis of a New Data Processing Method for Landslide Monitoring Based on Unmanned Aerial System Photogrammetry
title_full Accuracy Analysis of a New Data Processing Method for Landslide Monitoring Based on Unmanned Aerial System Photogrammetry
title_fullStr Accuracy Analysis of a New Data Processing Method for Landslide Monitoring Based on Unmanned Aerial System Photogrammetry
title_full_unstemmed Accuracy Analysis of a New Data Processing Method for Landslide Monitoring Based on Unmanned Aerial System Photogrammetry
title_short Accuracy Analysis of a New Data Processing Method for Landslide Monitoring Based on Unmanned Aerial System Photogrammetry
title_sort accuracy analysis of a new data processing method for landslide monitoring based on unmanned aerial system photogrammetry
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10054903/
https://www.ncbi.nlm.nih.gov/pubmed/36991810
http://dx.doi.org/10.3390/s23063097
work_keys_str_mv AT jakopecivan accuracyanalysisofanewdataprocessingmethodforlandslidemonitoringbasedonunmannedaerialsystemphotogrammetry
AT marendicante accuracyanalysisofanewdataprocessingmethodforlandslidemonitoringbasedonunmannedaerialsystemphotogrammetry
AT grgacigor accuracyanalysisofanewdataprocessingmethodforlandslidemonitoringbasedonunmannedaerialsystemphotogrammetry