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...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/1/150 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841549008662691840 |
|---|---|
| author | Alberto González-Díez Ignacio Díaz-Martínez Pablo Cruz-Hernández Antonio Barreda-Argüeso Matthew Doughty |
| author_facet | Alberto González-Díez Ignacio Díaz-Martínez Pablo Cruz-Hernández Antonio Barreda-Argüeso Matthew Doughty |
| author_sort | Alberto González-Díez |
| collection | DOAJ |
| 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. |
| format | Article |
| id | doaj-art-975d1335d36f43ad8d0d9f2b374f9c08 |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-975d1335d36f43ad8d0d9f2b374f9c082025-01-10T13:20:24ZengMDPI AGRemote Sensing2072-42922025-01-0117115010.3390/rs17010150The 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 EvaluationsAlberto González-Díez0Ignacio Díaz-Martínez1Pablo Cruz-Hernández2Antonio Barreda-Argüeso3Matthew Doughty4Departamento de Ciencias de la Tierra y Física de la Materia Condensada, Universidad de Cantabria, Avda. Los Castros, s/n, 39005 Santander, SpainDepartamento de Ciencias de la Tierra y Física de la Materia Condensada, Universidad de Cantabria, Avda. Los Castros, s/n, 39005 Santander, SpainDepartamento de Ciencias de la Tierra y Física de la Materia Condensada, Universidad de Cantabria, Avda. Los Castros, s/n, 39005 Santander, SpainDepartamento de Ciencias de la Tierra y Física de la Materia Condensada, Universidad de Cantabria, Avda. Los Castros, s/n, 39005 Santander, SpainDepartamento de Ciencias de la Tierra y Física de la Materia Condensada, Universidad de Cantabria, Avda. Los Castros, s/n, 39005 Santander, SpainIn 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.https://www.mdpi.com/2072-4292/17/1/150fast Fourier transform filteringDTMground truthsFGRMsDSMglobal accuracy |
| spellingShingle | Alberto González-Díez Ignacio Díaz-Martínez Pablo Cruz-Hernández Antonio Barreda-Argüeso Matthew Doughty 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 Remote Sensing fast Fourier transform filtering DTM ground truths FGRMs DSM global accuracy |
| 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 |
| 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_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_sort | 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 |
| topic | fast Fourier transform filtering DTM ground truths FGRMs DSM global accuracy |
| url | https://www.mdpi.com/2072-4292/17/1/150 |
| work_keys_str_mv | AT albertogonzalezdiez theapplicationoffastfouriertransformfilteringtohighspatialresolutiondigitalterrainmodelsderivedfromlidarsensorsfortheobjectivemappingofsurfacefeaturesanddigitalterrainmodelevaluations AT ignaciodiazmartinez theapplicationoffastfouriertransformfilteringtohighspatialresolutiondigitalterrainmodelsderivedfromlidarsensorsfortheobjectivemappingofsurfacefeaturesanddigitalterrainmodelevaluations AT pablocruzhernandez theapplicationoffastfouriertransformfilteringtohighspatialresolutiondigitalterrainmodelsderivedfromlidarsensorsfortheobjectivemappingofsurfacefeaturesanddigitalterrainmodelevaluations AT antoniobarredaargueso theapplicationoffastfouriertransformfilteringtohighspatialresolutiondigitalterrainmodelsderivedfromlidarsensorsfortheobjectivemappingofsurfacefeaturesanddigitalterrainmodelevaluations AT matthewdoughty theapplicationoffastfouriertransformfilteringtohighspatialresolutiondigitalterrainmodelsderivedfromlidarsensorsfortheobjectivemappingofsurfacefeaturesanddigitalterrainmodelevaluations AT albertogonzalezdiez applicationoffastfouriertransformfilteringtohighspatialresolutiondigitalterrainmodelsderivedfromlidarsensorsfortheobjectivemappingofsurfacefeaturesanddigitalterrainmodelevaluations AT ignaciodiazmartinez applicationoffastfouriertransformfilteringtohighspatialresolutiondigitalterrainmodelsderivedfromlidarsensorsfortheobjectivemappingofsurfacefeaturesanddigitalterrainmodelevaluations AT pablocruzhernandez applicationoffastfouriertransformfilteringtohighspatialresolutiondigitalterrainmodelsderivedfromlidarsensorsfortheobjectivemappingofsurfacefeaturesanddigitalterrainmodelevaluations AT antoniobarredaargueso applicationoffastfouriertransformfilteringtohighspatialresolutiondigitalterrainmodelsderivedfromlidarsensorsfortheobjectivemappingofsurfacefeaturesanddigitalterrainmodelevaluations AT matthewdoughty applicationoffastfouriertransformfilteringtohighspatialresolutiondigitalterrainmodelsderivedfromlidarsensorsfortheobjectivemappingofsurfacefeaturesanddigitalterrainmodelevaluations |