Border extrapolation using fractal attributes in remote sensing images

Autores
Cipolletti, Marina Paola; Delrieux, Claudio Augusto; Perillo, Gerardo Miguel E.; Piccolo, Maria Cintia
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In management, monitoring and rational use of natural resources the knowledge of precise and updated information is essential. Satellite images have become an attractive option for quantitative data extraction and morphologic studies, assuring a wide coverage without exerting negative environmental influence over the study area. However, the precision of such practice is limited by the spatial resolution of the sensors and the additional processing algorithms. The use of high resolution imagery (i.e., Ikonos) is very expensive for studies involving large geographic areas or requiring long term monitoring, while the use of less expensive or freely available imagery poses a limit in the geographic accuracy and physical precision that may be obtained. We developed a methodology for accurate border estimation that can be used for establishing high quality measurements with low resolution imagery. The method is based on the original theory by Richardson, taking advantage of the fractal nature of geographic features. The area of interest is downsampled at different scales and, at each scale, the border is segmented and measured. Finally, a regression of the dependence of the measured length with respect to scale is computed, which then allows for a precise extrapolation of the expected length at scales much finer than the originally available. The method is tested with both synthetic and satellite imagery, producing accurate results in both cases.
Fil: Cipolletti, Marina Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación En Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; Argentina
Fil: Delrieux, Claudio Augusto. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; Argentina
Fil: Perillo, Gerardo Miguel E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); Argentina. Universidad Nacional del Sur. Departamento de Geografía; Argentina
Fil: Piccolo, Maria Cintia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); Argentina. Universidad Nacional del Sur; Argentina
Materia
Perimeter
Extrapolation
Richardson
Fractal Dimension
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/11789
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Border extrapolation using fractal attributes in remote sensing imagesCipolletti, Marina PaolaDelrieux, Claudio AugustoPerillo, Gerardo Miguel E.Piccolo, Maria CintiaPerimeterExtrapolationRichardsonFractal Dimensionhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1In management, monitoring and rational use of natural resources the knowledge of precise and updated information is essential. Satellite images have become an attractive option for quantitative data extraction and morphologic studies, assuring a wide coverage without exerting negative environmental influence over the study area. However, the precision of such practice is limited by the spatial resolution of the sensors and the additional processing algorithms. The use of high resolution imagery (i.e., Ikonos) is very expensive for studies involving large geographic areas or requiring long term monitoring, while the use of less expensive or freely available imagery poses a limit in the geographic accuracy and physical precision that may be obtained. We developed a methodology for accurate border estimation that can be used for establishing high quality measurements with low resolution imagery. The method is based on the original theory by Richardson, taking advantage of the fractal nature of geographic features. The area of interest is downsampled at different scales and, at each scale, the border is segmented and measured. Finally, a regression of the dependence of the measured length with respect to scale is computed, which then allows for a precise extrapolation of the expected length at scales much finer than the originally available. The method is tested with both synthetic and satellite imagery, producing accurate results in both cases.Fil: Cipolletti, Marina Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación En Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; ArgentinaFil: Delrieux, Claudio Augusto. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; ArgentinaFil: Perillo, Gerardo Miguel E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); Argentina. Universidad Nacional del Sur. Departamento de Geografía; ArgentinaFil: Piccolo, Maria Cintia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); Argentina. Universidad Nacional del Sur; ArgentinaElsevier2014-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/11789Cipolletti, Marina Paola; Delrieux, Claudio Augusto; Perillo, Gerardo Miguel E.; Piccolo, Maria Cintia; Border extrapolation using fractal attributes in remote sensing images; Elsevier; Computers & Geosciences; 62; 1-2014; 25-340098-3004enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S009830041300246Xinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.cageo.2013.09.006info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:23:41Zoai:ri.conicet.gov.ar:11336/11789instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-10 13:23:41.906CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Border extrapolation using fractal attributes in remote sensing images
title Border extrapolation using fractal attributes in remote sensing images
spellingShingle Border extrapolation using fractal attributes in remote sensing images
Cipolletti, Marina Paola
Perimeter
Extrapolation
Richardson
Fractal Dimension
title_short Border extrapolation using fractal attributes in remote sensing images
title_full Border extrapolation using fractal attributes in remote sensing images
title_fullStr Border extrapolation using fractal attributes in remote sensing images
title_full_unstemmed Border extrapolation using fractal attributes in remote sensing images
title_sort Border extrapolation using fractal attributes in remote sensing images
dc.creator.none.fl_str_mv Cipolletti, Marina Paola
Delrieux, Claudio Augusto
Perillo, Gerardo Miguel E.
Piccolo, Maria Cintia
author Cipolletti, Marina Paola
author_facet Cipolletti, Marina Paola
Delrieux, Claudio Augusto
Perillo, Gerardo Miguel E.
Piccolo, Maria Cintia
author_role author
author2 Delrieux, Claudio Augusto
Perillo, Gerardo Miguel E.
Piccolo, Maria Cintia
author2_role author
author
author
dc.subject.none.fl_str_mv Perimeter
Extrapolation
Richardson
Fractal Dimension
topic Perimeter
Extrapolation
Richardson
Fractal Dimension
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In management, monitoring and rational use of natural resources the knowledge of precise and updated information is essential. Satellite images have become an attractive option for quantitative data extraction and morphologic studies, assuring a wide coverage without exerting negative environmental influence over the study area. However, the precision of such practice is limited by the spatial resolution of the sensors and the additional processing algorithms. The use of high resolution imagery (i.e., Ikonos) is very expensive for studies involving large geographic areas or requiring long term monitoring, while the use of less expensive or freely available imagery poses a limit in the geographic accuracy and physical precision that may be obtained. We developed a methodology for accurate border estimation that can be used for establishing high quality measurements with low resolution imagery. The method is based on the original theory by Richardson, taking advantage of the fractal nature of geographic features. The area of interest is downsampled at different scales and, at each scale, the border is segmented and measured. Finally, a regression of the dependence of the measured length with respect to scale is computed, which then allows for a precise extrapolation of the expected length at scales much finer than the originally available. The method is tested with both synthetic and satellite imagery, producing accurate results in both cases.
Fil: Cipolletti, Marina Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación En Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; Argentina
Fil: Delrieux, Claudio Augusto. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; Argentina
Fil: Perillo, Gerardo Miguel E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); Argentina. Universidad Nacional del Sur. Departamento de Geografía; Argentina
Fil: Piccolo, Maria Cintia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); Argentina. Universidad Nacional del Sur; Argentina
description In management, monitoring and rational use of natural resources the knowledge of precise and updated information is essential. Satellite images have become an attractive option for quantitative data extraction and morphologic studies, assuring a wide coverage without exerting negative environmental influence over the study area. However, the precision of such practice is limited by the spatial resolution of the sensors and the additional processing algorithms. The use of high resolution imagery (i.e., Ikonos) is very expensive for studies involving large geographic areas or requiring long term monitoring, while the use of less expensive or freely available imagery poses a limit in the geographic accuracy and physical precision that may be obtained. We developed a methodology for accurate border estimation that can be used for establishing high quality measurements with low resolution imagery. The method is based on the original theory by Richardson, taking advantage of the fractal nature of geographic features. The area of interest is downsampled at different scales and, at each scale, the border is segmented and measured. Finally, a regression of the dependence of the measured length with respect to scale is computed, which then allows for a precise extrapolation of the expected length at scales much finer than the originally available. The method is tested with both synthetic and satellite imagery, producing accurate results in both cases.
publishDate 2014
dc.date.none.fl_str_mv 2014-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/11789
Cipolletti, Marina Paola; Delrieux, Claudio Augusto; Perillo, Gerardo Miguel E.; Piccolo, Maria Cintia; Border extrapolation using fractal attributes in remote sensing images; Elsevier; Computers & Geosciences; 62; 1-2014; 25-34
0098-3004
url http://hdl.handle.net/11336/11789
identifier_str_mv Cipolletti, Marina Paola; Delrieux, Claudio Augusto; Perillo, Gerardo Miguel E.; Piccolo, Maria Cintia; Border extrapolation using fractal attributes in remote sensing images; Elsevier; Computers & Geosciences; 62; 1-2014; 25-34
0098-3004
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S009830041300246X
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.cageo.2013.09.006
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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