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Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision

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Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision

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dc.contributor.author Pardo Pascual, Josep Eliseu es_ES
dc.contributor.author Almonacid Caballer, Jaime es_ES
dc.contributor.author Ruiz Fernández, Luis Ángel es_ES
dc.contributor.author Palomar-Vázquez, Jesús es_ES
dc.date.accessioned 2015-12-16T14:22:05Z
dc.date.available 2015-12-16T14:22:05Z
dc.date.issued 2012-08
dc.identifier.issn 0034-4257
dc.identifier.uri http://hdl.handle.net/10251/58901
dc.description.abstract A high precision geometric method for automated shoreline detection from Landsat TM and ETM+ imagery is presented. The methodology is based on the application of an algorithm that ensures accurate image geometric registration and the use of a new algorithm for sub-pixel shoreline extraction, both at the sub-pixel level. The analysis of the initial errors shows the influence that differences in reflectance of land cover types have over shoreline detection, allowing us to create a model to substantially reduce these errors. Three correction models were defined according to the type of gain used in the acquisition of the original Landsat images. Error assessment tests were applied on three artificially stabilised coastal segments that have a constant and well-defined land-water boundary. A testing set of 45 images (28 TM, 10 ETM high-gain and 7 ETM low-gain) was used. The mean error obtained in shoreline location ranges from 1.22 to 1.63. m, and the RMSE from 4.69 to 5.47. m. Since the errors follow a normal distribution, then the maximum error at a given probability can be estimated. The results confirm that the use of Landsat imagery for detection of instantaneous coastlines yields accuracy comparable to high-resolution techniques, showing the potential of Landsat TM and ETM images in those applications where the instantaneous lines are a good geomorphological descriptor. © 2012 Elsevier Inc. es_ES
dc.description.sponsorship The authors appreciate the financial support provided by the Spanish Ministerio de Ciencia e Innovacion and the Spanish Plan E in the framework of the Projects CGL2009-14220-C02-01 and CGL2010-19591. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation Spanish Ministerio de Ciencia e Innovación and the Spanish Plan E in the framework of the Projects CGL2009-14220-C02-01 and CGL2010-19591 es_ES
dc.relation.ispartof Remote Sensing of Environment es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Beach management es_ES
dc.subject Coastal processes es_ES
dc.subject Landsat images es_ES
dc.subject Shoreline subpixel detection es_ES
dc.subject Automatic extraction es_ES
dc.subject Coastal process es_ES
dc.subject Correction models es_ES
dc.subject Descriptors es_ES
dc.subject Error assessment es_ES
dc.subject Geometric method es_ES
dc.subject High precision es_ES
dc.subject High-gain es_ES
dc.subject High-resolution techniques es_ES
dc.subject Land-cover types es_ES
dc.subject Landsat imagery es_ES
dc.subject LANDSAT TM es_ES
dc.subject Maximum error es_ES
dc.subject Mean errors es_ES
dc.subject Multi-temporal image es_ES
dc.subject Sub pixels es_ES
dc.subject Subpixel detection es_ES
dc.subject Subpixel precision es_ES
dc.subject Algorithms es_ES
dc.subject Normal distribution es_ES
dc.subject Errors es_ES
dc.subject Accuracy assessment es_ES
dc.subject Beach nourishment es_ES
dc.subject Error correction es_ES
dc.subject Geomorphological response es_ES
dc.subject Image resolution es_ES
dc.subject Land cover es_ES
dc.subject Landsat thematic mapper es_ES
dc.subject Pixel es_ES
dc.subject Precision es_ES
dc.subject Probability es_ES
dc.subject Reflectance es_ES
dc.subject Satellite imagery es_ES
dc.subject Shoreline es_ES
dc.subject.classification INGENIERIA CARTOGRAFICA, GEODESIA Y FOTOGRAMETRIA es_ES
dc.title Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.rse.2012.02.024
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Cartográfica Geodesia y Fotogrametría - Departament d'Enginyeria Cartogràfica, Geodèsia i Fotogrametria es_ES
dc.description.bibliographicCitation Pardo Pascual, JE.; Almonacid Caballer, J.; Ruiz Fernández, LÁ.; Palomar-Vázquez, J. (2012). Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision. Remote Sensing of Environment. 123:1-11. doi:10.1016/j.rse.2012.02.024 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.rse.2012.02.024 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 11 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 123 es_ES
dc.relation.senia 222602 es_ES


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