Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM data

Autores
Borro, María Marta; Morandeira, Natalia Soledad; Salvia, Maria Mercedes; Minotti, Priscilla Gail; Perna, Pablo Alejandro; Kandus, Patricia
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We propose a methodology to identify and map shallow lakes (SL) in the Paraná River floodplain, the largest freshwater wetland ecosystem in temperate South America. The presence and number of SL offer various ecosystem services and habitats for wildlife biodiversity. Our approach involved a frequency analysis over a 1987?2010 time series of the Normalized Difference Vegetation Index (NDVI), derived from Landsat 5 and 7 TM/ETM data. Through descriptive statistics of samples of pixels and field work in different types of SL, we established an NDVI threshold of 0.34 below which we assumed the presence of water in each pixel. The standard deviation of the estimated SL area decreases with the number of images in the analysis, being less than 10% when at least 30 images are used. The mean SL area for the whole period was 112,691 ha (10.9% of the study area). The influence of the hydrological conditions on the resulting SL map was evaluated by analyzing twelve sets of images, which were selected to span the whole period and different time frames according to multiannual dry and wet periods and to relative water level within each period. The Kappa index was then calculated between pairs of resulting SL maps. We compared our maps with the available national and international cartographic documents and with other published maps that used one or a few Landsat images. Landsat images time series provide an accurate spatial and temporal resolution for SL identification in floodplains, particularly in temperate zones with a good provision of cloud free images. The method evaluated in this paper considers the dynamics of SL and reduces the uncertainties of the fuzzy boundaries. Thus, it provides a robust database of SL and its temporal behavior to establish future monitoring programs based on the recent launch of Landsat 8 satellite.
Fil: Borro, María Marta. Universidad Nacional de San Martin. Instituto de Investigación e Ingenieria Ambiental. Laboratorio de Ecologia, Teledeteccion y Ecoinformática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Morandeira, Natalia Soledad. Universidad Nacional de San Martin. Instituto de Investigación e Ingenieria Ambiental. Laboratorio de Ecologia, Teledeteccion y Ecoinformática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Salvia, Maria Mercedes. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina
Fil: Minotti, Priscilla Gail. Universidad Nacional de San Martin. Instituto de Investigación e Ingenieria Ambiental. Laboratorio de Ecologia, Teledeteccion y Ecoinformática; Argentina
Fil: Perna, Pablo Alejandro. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina
Fil: Kandus, Patricia. Universidad Nacional de San Martin. Instituto de Investigación e Ingenieria Ambiental. Laboratorio de Ecologia, Teledeteccion y Ecoinformática; Argentina
Materia
Shallow Lakes Map
Paraná River Floodplain
Wetlands
Landsat Time Series
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/21508
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM dataBorro, María MartaMorandeira, Natalia SoledadSalvia, Maria MercedesMinotti, Priscilla GailPerna, Pablo AlejandroKandus, PatriciaShallow Lakes MapParaná River FloodplainWetlandsLandsat Time Serieshttps://purl.org/becyt/ford/2.7https://purl.org/becyt/ford/2https://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1We propose a methodology to identify and map shallow lakes (SL) in the Paraná River floodplain, the largest freshwater wetland ecosystem in temperate South America. The presence and number of SL offer various ecosystem services and habitats for wildlife biodiversity. Our approach involved a frequency analysis over a 1987?2010 time series of the Normalized Difference Vegetation Index (NDVI), derived from Landsat 5 and 7 TM/ETM data. Through descriptive statistics of samples of pixels and field work in different types of SL, we established an NDVI threshold of 0.34 below which we assumed the presence of water in each pixel. The standard deviation of the estimated SL area decreases with the number of images in the analysis, being less than 10% when at least 30 images are used. The mean SL area for the whole period was 112,691 ha (10.9% of the study area). The influence of the hydrological conditions on the resulting SL map was evaluated by analyzing twelve sets of images, which were selected to span the whole period and different time frames according to multiannual dry and wet periods and to relative water level within each period. The Kappa index was then calculated between pairs of resulting SL maps. We compared our maps with the available national and international cartographic documents and with other published maps that used one or a few Landsat images. Landsat images time series provide an accurate spatial and temporal resolution for SL identification in floodplains, particularly in temperate zones with a good provision of cloud free images. The method evaluated in this paper considers the dynamics of SL and reduces the uncertainties of the fuzzy boundaries. Thus, it provides a robust database of SL and its temporal behavior to establish future monitoring programs based on the recent launch of Landsat 8 satellite.Fil: Borro, María Marta. Universidad Nacional de San Martin. Instituto de Investigación e Ingenieria Ambiental. Laboratorio de Ecologia, Teledeteccion y Ecoinformática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Morandeira, Natalia Soledad. Universidad Nacional de San Martin. Instituto de Investigación e Ingenieria Ambiental. Laboratorio de Ecologia, Teledeteccion y Ecoinformática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Salvia, Maria Mercedes. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; ArgentinaFil: Minotti, Priscilla Gail. Universidad Nacional de San Martin. Instituto de Investigación e Ingenieria Ambiental. Laboratorio de Ecologia, Teledeteccion y Ecoinformática; ArgentinaFil: Perna, Pablo Alejandro. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; ArgentinaFil: Kandus, Patricia. Universidad Nacional de San Martin. Instituto de Investigación e Ingenieria Ambiental. Laboratorio de Ecologia, Teledeteccion y Ecoinformática; ArgentinaElsevier Science2014-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/21508Borro, María Marta; Morandeira, Natalia Soledad; Salvia, Maria Mercedes; Minotti, Priscilla Gail; Perna, Pablo Alejandro; et al.; Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM data; Elsevier Science; Journal Of Hydrology; 512; 5-2014; 39-520022-1694CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0022169414001656info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jhydrol.2014.02.057info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:47:50Zoai:ri.conicet.gov.ar:11336/21508instacron: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:34982025-10-15 14:47:51.269CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM data
title Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM data
spellingShingle Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM data
Borro, María Marta
Shallow Lakes Map
Paraná River Floodplain
Wetlands
Landsat Time Series
title_short Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM data
title_full Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM data
title_fullStr Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM data
title_full_unstemmed Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM data
title_sort Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM data
dc.creator.none.fl_str_mv Borro, María Marta
Morandeira, Natalia Soledad
Salvia, Maria Mercedes
Minotti, Priscilla Gail
Perna, Pablo Alejandro
Kandus, Patricia
author Borro, María Marta
author_facet Borro, María Marta
Morandeira, Natalia Soledad
Salvia, Maria Mercedes
Minotti, Priscilla Gail
Perna, Pablo Alejandro
Kandus, Patricia
author_role author
author2 Morandeira, Natalia Soledad
Salvia, Maria Mercedes
Minotti, Priscilla Gail
Perna, Pablo Alejandro
Kandus, Patricia
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Shallow Lakes Map
Paraná River Floodplain
Wetlands
Landsat Time Series
topic Shallow Lakes Map
Paraná River Floodplain
Wetlands
Landsat Time Series
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.7
https://purl.org/becyt/ford/2
https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We propose a methodology to identify and map shallow lakes (SL) in the Paraná River floodplain, the largest freshwater wetland ecosystem in temperate South America. The presence and number of SL offer various ecosystem services and habitats for wildlife biodiversity. Our approach involved a frequency analysis over a 1987?2010 time series of the Normalized Difference Vegetation Index (NDVI), derived from Landsat 5 and 7 TM/ETM data. Through descriptive statistics of samples of pixels and field work in different types of SL, we established an NDVI threshold of 0.34 below which we assumed the presence of water in each pixel. The standard deviation of the estimated SL area decreases with the number of images in the analysis, being less than 10% when at least 30 images are used. The mean SL area for the whole period was 112,691 ha (10.9% of the study area). The influence of the hydrological conditions on the resulting SL map was evaluated by analyzing twelve sets of images, which were selected to span the whole period and different time frames according to multiannual dry and wet periods and to relative water level within each period. The Kappa index was then calculated between pairs of resulting SL maps. We compared our maps with the available national and international cartographic documents and with other published maps that used one or a few Landsat images. Landsat images time series provide an accurate spatial and temporal resolution for SL identification in floodplains, particularly in temperate zones with a good provision of cloud free images. The method evaluated in this paper considers the dynamics of SL and reduces the uncertainties of the fuzzy boundaries. Thus, it provides a robust database of SL and its temporal behavior to establish future monitoring programs based on the recent launch of Landsat 8 satellite.
Fil: Borro, María Marta. Universidad Nacional de San Martin. Instituto de Investigación e Ingenieria Ambiental. Laboratorio de Ecologia, Teledeteccion y Ecoinformática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Morandeira, Natalia Soledad. Universidad Nacional de San Martin. Instituto de Investigación e Ingenieria Ambiental. Laboratorio de Ecologia, Teledeteccion y Ecoinformática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Salvia, Maria Mercedes. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina
Fil: Minotti, Priscilla Gail. Universidad Nacional de San Martin. Instituto de Investigación e Ingenieria Ambiental. Laboratorio de Ecologia, Teledeteccion y Ecoinformática; Argentina
Fil: Perna, Pablo Alejandro. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina
Fil: Kandus, Patricia. Universidad Nacional de San Martin. Instituto de Investigación e Ingenieria Ambiental. Laboratorio de Ecologia, Teledeteccion y Ecoinformática; Argentina
description We propose a methodology to identify and map shallow lakes (SL) in the Paraná River floodplain, the largest freshwater wetland ecosystem in temperate South America. The presence and number of SL offer various ecosystem services and habitats for wildlife biodiversity. Our approach involved a frequency analysis over a 1987?2010 time series of the Normalized Difference Vegetation Index (NDVI), derived from Landsat 5 and 7 TM/ETM data. Through descriptive statistics of samples of pixels and field work in different types of SL, we established an NDVI threshold of 0.34 below which we assumed the presence of water in each pixel. The standard deviation of the estimated SL area decreases with the number of images in the analysis, being less than 10% when at least 30 images are used. The mean SL area for the whole period was 112,691 ha (10.9% of the study area). The influence of the hydrological conditions on the resulting SL map was evaluated by analyzing twelve sets of images, which were selected to span the whole period and different time frames according to multiannual dry and wet periods and to relative water level within each period. The Kappa index was then calculated between pairs of resulting SL maps. We compared our maps with the available national and international cartographic documents and with other published maps that used one or a few Landsat images. Landsat images time series provide an accurate spatial and temporal resolution for SL identification in floodplains, particularly in temperate zones with a good provision of cloud free images. The method evaluated in this paper considers the dynamics of SL and reduces the uncertainties of the fuzzy boundaries. Thus, it provides a robust database of SL and its temporal behavior to establish future monitoring programs based on the recent launch of Landsat 8 satellite.
publishDate 2014
dc.date.none.fl_str_mv 2014-05
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/11336/21508
Borro, María Marta; Morandeira, Natalia Soledad; Salvia, Maria Mercedes; Minotti, Priscilla Gail; Perna, Pablo Alejandro; et al.; Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM data; Elsevier Science; Journal Of Hydrology; 512; 5-2014; 39-52
0022-1694
CONICET Digital
CONICET
url http://hdl.handle.net/11336/21508
identifier_str_mv Borro, María Marta; Morandeira, Natalia Soledad; Salvia, Maria Mercedes; Minotti, Priscilla Gail; Perna, Pablo Alejandro; et al.; Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM data; Elsevier Science; Journal Of Hydrology; 512; 5-2014; 39-52
0022-1694
CONICET Digital
CONICET
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/S0022169414001656
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jhydrol.2014.02.057
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
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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