A Structure-from-Motion Pipeline for Generating Digital Elevation Models for Surface-Runoff Analysis
Digital Elevation Models (DEMs) are used to derive information from the morphology of a land. The topographic attributes obtained from the DEM data allow the construction of watershed delineation useful for predicting the behavior of systems and for studying hydrological processes. Imagery acquired...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2019
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/9234
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/9234
- Palabra clave:
- Antennas
Cameras
Cost effectiveness
Digital instruments
Engineering research
Geomorphology
Morphology
Object recognition
Open source software
Open systems
Optical radar
Pipelines
Remote sensing
Rock mechanics
Runoff
Computer vision techniques
Digital elevation model
Ground control points
High spatial resolution
Rainfall-runoff modeling
Structure from motion
Surface runoff modeling
Watershed delineation
Surveying
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.title.none.fl_str_mv |
A Structure-from-Motion Pipeline for Generating Digital Elevation Models for Surface-Runoff Analysis |
title |
A Structure-from-Motion Pipeline for Generating Digital Elevation Models for Surface-Runoff Analysis |
spellingShingle |
A Structure-from-Motion Pipeline for Generating Digital Elevation Models for Surface-Runoff Analysis Antennas Cameras Cost effectiveness Digital instruments Engineering research Geomorphology Morphology Object recognition Open source software Open systems Optical radar Pipelines Remote sensing Rock mechanics Runoff Computer vision techniques Digital elevation model Ground control points High spatial resolution Rainfall-runoff modeling Structure from motion Surface runoff modeling Watershed delineation Surveying |
title_short |
A Structure-from-Motion Pipeline for Generating Digital Elevation Models for Surface-Runoff Analysis |
title_full |
A Structure-from-Motion Pipeline for Generating Digital Elevation Models for Surface-Runoff Analysis |
title_fullStr |
A Structure-from-Motion Pipeline for Generating Digital Elevation Models for Surface-Runoff Analysis |
title_full_unstemmed |
A Structure-from-Motion Pipeline for Generating Digital Elevation Models for Surface-Runoff Analysis |
title_sort |
A Structure-from-Motion Pipeline for Generating Digital Elevation Models for Surface-Runoff Analysis |
dc.contributor.editor.none.fl_str_mv |
Perez-Taborda J.A. Avila Bernal A.G. |
dc.subject.keywords.none.fl_str_mv |
Antennas Cameras Cost effectiveness Digital instruments Engineering research Geomorphology Morphology Object recognition Open source software Open systems Optical radar Pipelines Remote sensing Rock mechanics Runoff Computer vision techniques Digital elevation model Ground control points High spatial resolution Rainfall-runoff modeling Structure from motion Surface runoff modeling Watershed delineation Surveying |
topic |
Antennas Cameras Cost effectiveness Digital instruments Engineering research Geomorphology Morphology Object recognition Open source software Open systems Optical radar Pipelines Remote sensing Rock mechanics Runoff Computer vision techniques Digital elevation model Ground control points High spatial resolution Rainfall-runoff modeling Structure from motion Surface runoff modeling Watershed delineation Surveying |
description |
Digital Elevation Models (DEMs) are used to derive information from the morphology of a land. The topographic attributes obtained from the DEM data allow the construction of watershed delineation useful for predicting the behavior of systems and for studying hydrological processes. Imagery acquired from Unmanned Aerial Vehicles (UAVs) and 3D photogrammetry techniques offer cost-effective advantages over other remote sensing methods such as LIDAR or RADAR. In particular, a high spatial resolution for measuring the terrain microtopography. In this work, we propose a Structure from Motion (SfM) pipeline using UAVs for generating high-resolution, high-quality DEMs for developing a rainfall-runoff model to study flood areas. SfM is a computer vision technique that simultaneously estimates the 3D coordinates of a scene and the pose of a camera that moves around it. The result is a 3D point cloud which we process to obtain a georeference model from the GPS information of the camera and ground control points. The pipeline is based on open source software OpenSfM and OpenDroneMap. Encouraging experimental results on a test land show that the produced DEMs meet the metrological requirements for developing a surface-runoff model. © Published under licence by IOP Publishing Ltd. |
publishDate |
2019 |
dc.date.issued.none.fl_str_mv |
2019 |
dc.date.accessioned.none.fl_str_mv |
2020-03-26T16:41:24Z |
dc.date.available.none.fl_str_mv |
2020-03-26T16:41:24Z |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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http://purl.org/coar/resource_type/c_c94f |
dc.type.driver.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
dc.type.hasVersion.none.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.spa.none.fl_str_mv |
Conferencia |
status_str |
publishedVersion |
dc.identifier.citation.none.fl_str_mv |
Meza J., Marrugo A.G., Ospina G., Guerrero M. y Romero L.A. (2019) A Structure-from-Motion Pipeline for Generating Digital Elevation Models for Surface-Runoff Analysis. Journal of Physics: Conference Series; Vol. 1247, Núm. 1 |
dc.identifier.issn.none.fl_str_mv |
17426588 |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/9234 |
dc.identifier.doi.none.fl_str_mv |
10.1088/1742-6596/1247/1/012039 |
dc.identifier.instname.none.fl_str_mv |
Universidad Tecnológica de Bolívar |
dc.identifier.reponame.none.fl_str_mv |
Repositorio UTB |
dc.identifier.orcid.none.fl_str_mv |
57204065355 24329839300 57211428345 57200615582 36142156300 |
identifier_str_mv |
Meza J., Marrugo A.G., Ospina G., Guerrero M. y Romero L.A. (2019) A Structure-from-Motion Pipeline for Generating Digital Elevation Models for Surface-Runoff Analysis. Journal of Physics: Conference Series; Vol. 1247, Núm. 1 17426588 10.1088/1742-6596/1247/1/012039 Universidad Tecnológica de Bolívar Repositorio UTB 57204065355 24329839300 57211428345 57200615582 36142156300 |
url |
https://hdl.handle.net/20.500.12585/9234 |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.relation.conferencedate.none.fl_str_mv |
22 October 2018 through 26 October 2018 |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.uri.none.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.rights.accessRights.none.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.cc.none.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ Atribución-NoComercial 4.0 Internacional http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.medium.none.fl_str_mv |
Recurso electrónico |
dc.format.mimetype.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Institute of Physics Publishing |
publisher.none.fl_str_mv |
Institute of Physics Publishing |
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institution |
Universidad Tecnológica de Bolívar |
dc.source.event.none.fl_str_mv |
6th National Conference on Engineering Physics, CNIF 2018 and the 1st International Conference on Applied Physics Engineering and Innovation, APEI 2018 |
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spelling |
Perez-Taborda J.A.Avila Bernal A.G.Meza J.Marrugo A.G.Ospina G.Guerrero M.Romero L.A.2020-03-26T16:41:24Z2020-03-26T16:41:24Z2019Meza J., Marrugo A.G., Ospina G., Guerrero M. y Romero L.A. (2019) A Structure-from-Motion Pipeline for Generating Digital Elevation Models for Surface-Runoff Analysis. Journal of Physics: Conference Series; Vol. 1247, Núm. 117426588https://hdl.handle.net/20.500.12585/923410.1088/1742-6596/1247/1/012039Universidad Tecnológica de BolívarRepositorio UTB5720406535524329839300572114283455720061558236142156300Digital Elevation Models (DEMs) are used to derive information from the morphology of a land. The topographic attributes obtained from the DEM data allow the construction of watershed delineation useful for predicting the behavior of systems and for studying hydrological processes. Imagery acquired from Unmanned Aerial Vehicles (UAVs) and 3D photogrammetry techniques offer cost-effective advantages over other remote sensing methods such as LIDAR or RADAR. In particular, a high spatial resolution for measuring the terrain microtopography. In this work, we propose a Structure from Motion (SfM) pipeline using UAVs for generating high-resolution, high-quality DEMs for developing a rainfall-runoff model to study flood areas. SfM is a computer vision technique that simultaneously estimates the 3D coordinates of a scene and the pose of a camera that moves around it. The result is a 3D point cloud which we process to obtain a georeference model from the GPS information of the camera and ground control points. The pipeline is based on open source software OpenSfM and OpenDroneMap. Encouraging experimental results on a test land show that the produced DEMs meet the metrological requirements for developing a surface-runoff model. © Published under licence by IOP Publishing Ltd.This work has been partly funded by Universidad Tecnológica de Bolívar project (FI2006T2001). The authors thank Direccion de Investigaciones Universidad Tecnologica de Bolivar for their support.Recurso electrónicoapplication/pdfengInstitute of Physics Publishinghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073914844&doi=10.1088%2f1742-6596%2f1247%2f1%2f012039&partnerID=40&md5=c602b10d3665e588f5ea3c184a840ba2Scopus2-s2.0-850739148446th National Conference on Engineering Physics, CNIF 2018 and the 1st International Conference on Applied Physics Engineering and Innovation, APEI 2018A Structure-from-Motion Pipeline for Generating Digital Elevation Models for Surface-Runoff Analysisinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionConferenciahttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_c94fAntennasCamerasCost effectivenessDigital instrumentsEngineering researchGeomorphologyMorphologyObject recognitionOpen source softwareOpen systemsOptical radarPipelinesRemote sensingRock mechanicsRunoffComputer vision techniquesDigital elevation modelGround control pointsHigh spatial resolutionRainfall-runoff modelingStructure from motionSurface runoff modelingWatershed delineationSurveying22 October 2018 through 26 October 2018Smith, M., Carrivick, J., Quincey, D., (2016) Progress in Physical Geography, 40 (2), pp. 247-275Marcus, W.A., Fonstad, M.A., (2008) Earth Surface Processes and Landforms, 33 (1), pp. 4-24Westoby, M., Brasington, J., Glasser, N., Hambrey, M., Reynolds, J., (2012) Geomorphology, 179, pp. 300-314Enciso, J., Jung, J., Chang, A., (2018) Journal of Applied Remote Sensing, 12 (1), pp. 1-9Nobajas, A., Waller, R.I., Robinson, Z.P., Sangonzalo, R., (2017) International Journal of Remote Sensing, 38 (8-10), pp. 2844-2860Goesele, M., Curless, B., Seitz, S.M., (2006) Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on, pp. 2402-2409. , (IEEE)Agisoft Photoscan Professional, , http://www.agisoft.com/downloads/installer/https://pix4d.com/, Pix4dMeza, J., Marrugo, A.G., Sierra, E., Guerrero, M., Meneses, J., Romero, L.A., (2018) Communications in Computer and Information Science, 885, pp. 213-225https://github.com/mapillary/OpenSfM, Mapillary: Opensfmhttps://github.com/OpenDroneMap/OpenDroneMap, OpendronemapBradski, G., Kaehler, A., (2000) Dr. Dobb's Journal of Software Tools, 3https://www.altizure.comTriggs, B., McLauchlan, P.F., Hartley, R.I., Fitzgibbon, A.W., (1999) International Workshop on Vision Algorithms, pp. 298-372. , (Springer)Furukawa, Y., Ponce, J., (2010) IEEE Transactions on Pattern Analysis and Machine Intelligence, 32 (8), pp. 1362-1376Adorjan, M., (2016) Ein Kollaboratives Structure-from-Motion System, , (Technischen UniversitDotat Wien) Master's thesisPDAL Contributors 2018 PDAL: The Point Data Abstraction Library, , https://pdal.io/Chen, Z., Devereux, B., Gao, B., Amable, G., (2012) ISPRS Journal of Photogrammetry and Remote Sensing, 72, pp. 121-130Pingel, T.J., Clarke, K.C., McBride, W.A., (2013) ISPRS Journal of Photogrammetry and Remote Sensing, 77, pp. 21-30http://purl.org/coar/resource_type/c_c94fORIGINALdoi1010881742659612471012039.pdfapplication/pdf11990701https://repositorio.utb.edu.co/bitstream/20.500.12585/9234/1/doi1010881742659612471012039.pdfc4090e16f05db5bcd7acf1e04667d840MD51TEXTdoi1010881742659612471012039.pdf.txtdoi1010881742659612471012039.pdf.txtExtracted texttext/plain18143https://repositorio.utb.edu.co/bitstream/20.500.12585/9234/4/doi1010881742659612471012039.pdf.txt665e594a9f45b3ddbdbdf571dc0f962cMD54THUMBNAILdoi1010881742659612471012039.pdf.jpgdoi1010881742659612471012039.pdf.jpgGenerated Thumbnailimage/jpeg28981https://repositorio.utb.edu.co/bitstream/20.500.12585/9234/5/doi1010881742659612471012039.pdf.jpgb6ec5f914e66a83bebc954a745b081adMD5520.500.12585/9234oai:repositorio.utb.edu.co:20.500.12585/92342020-10-23 05:15:47.144Repositorio Institucional UTBrepositorioutb@utb.edu.co |