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dc.contributor.author
Genchi, Sibila Andrea  
dc.contributor.author
Vitale, Alejandro José  
dc.contributor.author
Perillo, Gerardo Miguel E.  
dc.contributor.author
Seitz, Carina  
dc.contributor.author
Delrieux, Claudio Augusto  
dc.date.available
2021-03-22T19:41:44Z  
dc.date.issued
2020-05-28  
dc.identifier.citation
Genchi, Sibila Andrea; Vitale, Alejandro José; Perillo, Gerardo Miguel E.; Seitz, Carina; Delrieux, Claudio Augusto; Mapping Topobathymetry in a Shallow Tidal Environment Using Low-Cost Technology; Multidisciplinary Digital Publishing Institute; Remote Sensing; 12; 9; 28-5-2020; 1-17; 1394  
dc.identifier.issn
2072-4292  
dc.identifier.uri
http://hdl.handle.net/11336/128771  
dc.description.abstract
Detailed knowledge of nearshore topography and bathymetry is required for a wide variety of purposes, including ecosystem protection, coastal management, and flood and erosion monitoring and research, among others. Both topography and bathymetry are usually studied separately; however, many scientific questions and challenges require an integrated approach. LiDAR technology is often the preferred data source for the generation of topobathymetric models, but because of its high cost, it is necessary to exploit other data sources. In this regard, the main goal of this study was to present a methodological proposal to generate a topobathymetric model, using low-cost unmanned platforms (unmanned aerial vehicle and unmanned surface vessel) in a very shallow/shallow and turbid tidal environment (Bahia Blanca estuary, Argentina). Moreover, a cross-analysis of the topobathymetric and the tide level data was conducted, to provide a classification of hydrogeomorphic zones. As a main result, a continuous terrain model was built, with a spatial resolution of approximately 0.08 m (topography) and 0.50 m (bathymetry). Concerning the structure from motion-derived topography, the accuracy gave a root mean square error of 0.09 m for the vertical plane. The best interpolated bathymetry (inverse distance weighting method), which was aligned to the topography (as reference), showed a root mean square error of 0.18 m (in average) and a mean absolute error of 0.05 m. The final topobathymetric model showed an adequate representation of the terrain, making it well suited for examining many landforms. This study helps to confirm the potential for remote sensing of shallow tidal environments by demonstrating how the data source heterogeneity can be exploited.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Multidisciplinary Digital Publishing Institute  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/  
dc.subject
HYDROGEOMORPHIC ZONES  
dc.subject
SHALLOW TIDAL ENVIRONMENT  
dc.subject
TOPOBATHYMETRY  
dc.subject
UNMANNED PLATFORMS  
dc.subject.classification
Otras Ciencias de la Computación e Información  
dc.subject.classification
Ciencias de la Computación e Información  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Mapping Topobathymetry in a Shallow Tidal Environment Using Low-Cost Technology  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2021-02-10T16:59:10Z  
dc.journal.volume
12  
dc.journal.number
9  
dc.journal.pagination
1-17; 1394  
dc.journal.pais
Suiza  
dc.journal.ciudad
Basilea  
dc.description.fil
Fil: Genchi, Sibila Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Geografía y Turismo; Argentina  
dc.description.fil
Fil: Vitale, Alejandro José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Nacional del Sur. Departamento de Geografía y Turismo; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina  
dc.description.fil
Fil: Perillo, Gerardo Miguel E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Nacional del Sur. Departamento de Geología; Argentina  
dc.description.fil
Fil: Seitz, Carina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Nacional del Sur. Departamento de Geología; Argentina  
dc.description.fil
Fil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina  
dc.journal.title
Remote Sensing  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2072-4292/12/9/1394  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.3390/rs12091394