The application of fast Fourier transform filtering to high spatial resolution digital terrain models derived from LiDAR sensors for the objective mapping of surface features and digital terrain model evaluations

In this paper, the application is investigated of fast Fourier transform filtering (FFT-FR) to high spatial resolution digital terrain models (HR-DTM) derived from LiDAR sensors, assessing its efficacy in identifying genuine relief elements, including both natural geological features and anthropogen...

Full description

Bibliographic Details
Authors: González Díez, Alberto|||0000-0002-0151-3081, Díaz Martínez, Ignacio|||0000-0001-5301-8384, Cruz Hernández, Pablo, Barreda Argüeso, José Antonio, Doughty, Matthew William
Format: article
Publication Date:2025
Country:España
Institution:Universidad de Cantabria (UC)
Repository:UCrea Repositorio Abierto de la Universidad de Cantabria
Language:English
OAI Identifier:oai:repositorio.unican.es:10902/35272
Online Access:https://hdl.handle.net/10902/35272
Access Level:Open access
Keyword:Fast Fourier transform filtering
DTM
Ground truths
FGRMs
DSM
Global accuracy
Kappa
id ES_2be754fa69c3ea6d105e7dda54b055a8
oai_identifier_str oai:repositorio.unican.es:10902/35272
network_acronym_str ES
network_name_str España
repository_id_str
spelling The application of fast Fourier transform filtering to high spatial resolution digital terrain models derived from LiDAR sensors for the objective mapping of surface features and digital terrain model evaluationsGonzález Díez, Alberto|||0000-0002-0151-3081Díaz Martínez, Ignacio|||0000-0001-5301-8384Cruz Hernández, PabloBarreda Argüeso, José AntonioDoughty, Matthew WilliamFast Fourier transform filteringDTMGround truthsFGRMsDSMGlobal accuracyKappaIn this paper, the application is investigated of fast Fourier transform filtering (FFT-FR) to high spatial resolution digital terrain models (HR-DTM) derived from LiDAR sensors, assessing its efficacy in identifying genuine relief elements, including both natural geological features and anthropogenic landforms. The suitability of the derived filtered geomorphic references (FGRs) is evaluated through spatial correlation with ground truths (GTs) extracted from the topographical and geological geodatabases of Santander Bay, Northern Spain. In this study, it is revealed that existing artefacts, derived from vegetation or human infrastructures, pose challenges in the units´ construction, and large physiographic units are better represented using low-pass filters, whereas detailed units are more accurately depicted with high-pass filters. The results indicate a propensity of high-frequency filters to detect anthropogenic elements within the DTM. The quality of GTs used for validation proves more critical than the geodatabase scale. Additionally, in this study, it is demonstrated that the footprint of buildings remains uneliminated, indicating that the model is a poorly refined digital surface model (DSM) rather than a true digital terrain model (DTM). Experiments validate the DTM?s capability to highlight contacts and constructions, with water detection showing high precision (≥60%) and varying precision for buildings. Large units are better captured with low filters, whilst high filters effectively detect anthropogenic elements and more detailed units. This facilitates the design of validation and correction procedures for DEMs derived from LiDAR point clouds, enhancing the potential for more accurate and objective Earth surface representation.This work was carried out as part of the Projects: 29.P114.64004 (UC); 29.P203.64004 (UC); RECORNISA (FLTQ-UC). Díaz-Martínez, I. is supported by the Ramón y Cajal fellowship (RYC-2022, Ministerio de Ciencia e Innovación, Spanish Government). We thank the reviewers and editors for their constructive criticisms and suggestions, which have helped us to improve the initial version of the manuscript.MDPIUniversidad de Cantabria20252025-01-01journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articlehttps://hdl.handle.net/10902/35272Remote Sensing, 2025, 17(1), 150reponame:UCrea Repositorio Abierto de la Universidad de Cantabriainstname:Universidad de Cantabria (UC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositorio.unican.es:10902/352722026-06-02T12:39:31Z
dc.title.none.fl_str_mv The application of fast Fourier transform filtering to high spatial resolution digital terrain models derived from LiDAR sensors for the objective mapping of surface features and digital terrain model evaluations
title The application of fast Fourier transform filtering to high spatial resolution digital terrain models derived from LiDAR sensors for the objective mapping of surface features and digital terrain model evaluations
spellingShingle The application of fast Fourier transform filtering to high spatial resolution digital terrain models derived from LiDAR sensors for the objective mapping of surface features and digital terrain model evaluations
González Díez, Alberto|||0000-0002-0151-3081
Fast Fourier transform filtering
DTM
Ground truths
FGRMs
DSM
Global accuracy
Kappa
title_short The application of fast Fourier transform filtering to high spatial resolution digital terrain models derived from LiDAR sensors for the objective mapping of surface features and digital terrain model evaluations
title_full The application of fast Fourier transform filtering to high spatial resolution digital terrain models derived from LiDAR sensors for the objective mapping of surface features and digital terrain model evaluations
title_fullStr The application of fast Fourier transform filtering to high spatial resolution digital terrain models derived from LiDAR sensors for the objective mapping of surface features and digital terrain model evaluations
title_full_unstemmed The application of fast Fourier transform filtering to high spatial resolution digital terrain models derived from LiDAR sensors for the objective mapping of surface features and digital terrain model evaluations
title_sort The application of fast Fourier transform filtering to high spatial resolution digital terrain models derived from LiDAR sensors for the objective mapping of surface features and digital terrain model evaluations
dc.creator.none.fl_str_mv González Díez, Alberto|||0000-0002-0151-3081
Díaz Martínez, Ignacio|||0000-0001-5301-8384
Cruz Hernández, Pablo
Barreda Argüeso, José Antonio
Doughty, Matthew William
author González Díez, Alberto|||0000-0002-0151-3081
author_facet González Díez, Alberto|||0000-0002-0151-3081
Díaz Martínez, Ignacio|||0000-0001-5301-8384
Cruz Hernández, Pablo
Barreda Argüeso, José Antonio
Doughty, Matthew William
author_role author
author2 Díaz Martínez, Ignacio|||0000-0001-5301-8384
Cruz Hernández, Pablo
Barreda Argüeso, José Antonio
Doughty, Matthew William
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidad de Cantabria
dc.subject.none.fl_str_mv Fast Fourier transform filtering
DTM
Ground truths
FGRMs
DSM
Global accuracy
Kappa
topic Fast Fourier transform filtering
DTM
Ground truths
FGRMs
DSM
Global accuracy
Kappa
description In this paper, the application is investigated of fast Fourier transform filtering (FFT-FR) to high spatial resolution digital terrain models (HR-DTM) derived from LiDAR sensors, assessing its efficacy in identifying genuine relief elements, including both natural geological features and anthropogenic landforms. The suitability of the derived filtered geomorphic references (FGRs) is evaluated through spatial correlation with ground truths (GTs) extracted from the topographical and geological geodatabases of Santander Bay, Northern Spain. In this study, it is revealed that existing artefacts, derived from vegetation or human infrastructures, pose challenges in the units´ construction, and large physiographic units are better represented using low-pass filters, whereas detailed units are more accurately depicted with high-pass filters. The results indicate a propensity of high-frequency filters to detect anthropogenic elements within the DTM. The quality of GTs used for validation proves more critical than the geodatabase scale. Additionally, in this study, it is demonstrated that the footprint of buildings remains uneliminated, indicating that the model is a poorly refined digital surface model (DSM) rather than a true digital terrain model (DTM). Experiments validate the DTM?s capability to highlight contacts and constructions, with water detection showing high precision (≥60%) and varying precision for buildings. Large units are better captured with low filters, whilst high filters effectively detect anthropogenic elements and more detailed units. This facilitates the design of validation and correction procedures for DEMs derived from LiDAR point clouds, enhancing the potential for more accurate and objective Earth surface representation.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10902/35272
url https://hdl.handle.net/10902/35272
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv Remote Sensing, 2025, 17(1), 150
reponame:UCrea Repositorio Abierto de la Universidad de Cantabria
instname:Universidad de Cantabria (UC)
instname_str Universidad de Cantabria (UC)
reponame_str UCrea Repositorio Abierto de la Universidad de Cantabria
collection UCrea Repositorio Abierto de la Universidad de Cantabria
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869405192783396864
score 15,812429

Similar Items