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...

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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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oai_identifier_str oai:repositorio.utb.edu.co:20.500.12585/9234
network_acronym_str UTB2
network_name_str Repositorio Institucional UTB
repository_id_str
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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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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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