Relationship between biophysical parameters and synthetic indices derived from hyperspectral field data in a coastal marsh from Buenos Aires Province, Argentina

Autores
Gonzalez Trilla, Gabriela Liliana; Pratolongo, Paula Daniela; Kandus, Patricia; Beget, Maria Eugenia; Di Bella, Carlos Marcelo; Marcovecchio, Jorge Eduardo
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Remote sensing tools allow the environmental evaluation of coastal wetlands at a landscape scale, but a deeper understanding is needed of the interactions between biophysical parameters and the electromagnetic signal. The goal of this work was to analyze and quantify the influence of the aboveground biomass and the Leaf Area Index (LAI) on the spectral response of Spartina densiflora marshes in Mar Chiquita coastal lagoon, Argentina. Spectral reflectance at high resolution was measured in S. densiflora canopies under natural conditions, manipulating standing crop by means of successive harvest. Reflectance data were acquired using a spectroradiometer in visible, near infrared (IR) and shortwave IR bands. Spectral Vegetation Indices (VI) were calculated for each standing crop-LAI situation. Several VI significantly correlated with standing crop and LAI, including indices 1) based on the red-IR edge (IR Index (IRI), 695/760 ratio, Simple Ratio (SR), Red Edge Inflection Point (REIP), and different variations of the Normalized Difference VI (NDVI Rouse, NDVI amber, NDVI NOAA, NDVI Landsat, NDVI Modis), 2) indices based on the sharp change green-IR (green NDVI (GNDVI), 800/550 ratio) and 3) indices with a correction for soil noise (OSAVI: Optimized Soil Adjusted VI (OSAVI), and Modified SAVI (MSAVI). The indices with significant regressions with standing crop and LAI were IRI, NDVIAmber and REIP. The total and green standing crop showed better adjustments than LAI, showing R2 values of 0.5. These values were obtained with REIP index. Results indicate that LAI and standing crop of S. densiflora stands could be determined from spectral data but estimations should be taken carefully in high biomass scenarios, because of indexes saturation at higher LAI values.
Instituto de Clima y Agua
Fil: Gonzalez Trilla, Gabriela Liliana. Universidad Nacional de San Martín. Instituto de Investigación e Ingeniería Ambiental. Laboratorio de Ecología, Teledetección y Ecoinformática; Argentina
Fil: Pratolongo, Paula Daniela. 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
Fil: Kandus, Patricia. Universidad Nacional de San Martín. Instituto de Investigación e Ingeniería Ambiental. Laboratorio de Ecología, Teledetección y Ecoinformática; Argentina
Fil: Beget, Maria Eugenia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Di Bella, Carlos Marcelo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina
Fil: Marcovecchio, Jorge Eduardo. 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
Fuente
Wetlands 36 (1) : 185–194. (February 2016)
Materia
Marisma
Teledetección
Biomasa
Marshes
Remote Sensing
Biomass
Leaf Area Index
Índice de Superficie Foliar
Buenos Aires
Spartina Densiflora
Cultivo en Pie
Spectral Indices
Standing Crop
Nivel de accesibilidad
acceso restringido
Condiciones de uso
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/3597
Acceder
id INTADig_12fba9399f32bef1bd54a3c79b40da3c
oai_identifier_str oai:localhost:20.500.12123/3597
network_acronym_str INTADig
repository_id_str l
network_name_str INTA Digital (INTA)
spelling Relationship between biophysical parameters and synthetic indices derived from hyperspectral field data in a coastal marsh from Buenos Aires Province, ArgentinaGonzalez Trilla, Gabriela LilianaPratolongo, Paula DanielaKandus, PatriciaBeget, Maria EugeniaDi Bella, Carlos MarceloMarcovecchio, Jorge EduardoMarismaTeledetecciónBiomasaMarshesRemote SensingBiomassLeaf Area IndexÍndice de Superficie FoliarBuenos AiresSpartina DensifloraCultivo en PieSpectral IndicesStanding CropRemote sensing tools allow the environmental evaluation of coastal wetlands at a landscape scale, but a deeper understanding is needed of the interactions between biophysical parameters and the electromagnetic signal. The goal of this work was to analyze and quantify the influence of the aboveground biomass and the Leaf Area Index (LAI) on the spectral response of Spartina densiflora marshes in Mar Chiquita coastal lagoon, Argentina. Spectral reflectance at high resolution was measured in S. densiflora canopies under natural conditions, manipulating standing crop by means of successive harvest. Reflectance data were acquired using a spectroradiometer in visible, near infrared (IR) and shortwave IR bands. Spectral Vegetation Indices (VI) were calculated for each standing crop-LAI situation. Several VI significantly correlated with standing crop and LAI, including indices 1) based on the red-IR edge (IR Index (IRI), 695/760 ratio, Simple Ratio (SR), Red Edge Inflection Point (REIP), and different variations of the Normalized Difference VI (NDVI Rouse, NDVI amber, NDVI NOAA, NDVI Landsat, NDVI Modis), 2) indices based on the sharp change green-IR (green NDVI (GNDVI), 800/550 ratio) and 3) indices with a correction for soil noise (OSAVI: Optimized Soil Adjusted VI (OSAVI), and Modified SAVI (MSAVI). The indices with significant regressions with standing crop and LAI were IRI, NDVIAmber and REIP. The total and green standing crop showed better adjustments than LAI, showing R2 values of 0.5. These values were obtained with REIP index. Results indicate that LAI and standing crop of S. densiflora stands could be determined from spectral data but estimations should be taken carefully in high biomass scenarios, because of indexes saturation at higher LAI values.Instituto de Clima y AguaFil: Gonzalez Trilla, Gabriela Liliana. Universidad Nacional de San Martín. Instituto de Investigación e Ingeniería Ambiental. Laboratorio de Ecología, Teledetección y Ecoinformática; ArgentinaFil: Pratolongo, Paula Daniela. 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; ArgentinaFil: Kandus, Patricia. Universidad Nacional de San Martín. Instituto de Investigación e Ingeniería Ambiental. Laboratorio de Ecología, Teledetección y Ecoinformática; ArgentinaFil: Beget, Maria Eugenia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Di Bella, Carlos Marcelo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; ArgentinaFil: Marcovecchio, Jorge Eduardo. 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; ArgentinaSpringer2018-10-16T12:51:21Z2018-10-16T12:51:21Z2016-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/3597https://link.springer.com/article/10.1007%2Fs13157-015-0715-6#citeas0277-52121943-6246 (Online)https://doi.org/10.1007/s13157-015-0715-6Wetlands 36 (1) : 185–194. (February 2016)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología AgropecuariaengBuenos Aires (province)info:eu-repo/semantics/restrictedAccess2025-09-04T09:47:37Zoai:localhost:20.500.12123/3597instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-04 09:47:37.862INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Relationship between biophysical parameters and synthetic indices derived from hyperspectral field data in a coastal marsh from Buenos Aires Province, Argentina
title Relationship between biophysical parameters and synthetic indices derived from hyperspectral field data in a coastal marsh from Buenos Aires Province, Argentina
spellingShingle Relationship between biophysical parameters and synthetic indices derived from hyperspectral field data in a coastal marsh from Buenos Aires Province, Argentina
Gonzalez Trilla, Gabriela Liliana
Marisma
Teledetección
Biomasa
Marshes
Remote Sensing
Biomass
Leaf Area Index
Índice de Superficie Foliar
Buenos Aires
Spartina Densiflora
Cultivo en Pie
Spectral Indices
Standing Crop
title_short Relationship between biophysical parameters and synthetic indices derived from hyperspectral field data in a coastal marsh from Buenos Aires Province, Argentina
title_full Relationship between biophysical parameters and synthetic indices derived from hyperspectral field data in a coastal marsh from Buenos Aires Province, Argentina
title_fullStr Relationship between biophysical parameters and synthetic indices derived from hyperspectral field data in a coastal marsh from Buenos Aires Province, Argentina
title_full_unstemmed Relationship between biophysical parameters and synthetic indices derived from hyperspectral field data in a coastal marsh from Buenos Aires Province, Argentina
title_sort Relationship between biophysical parameters and synthetic indices derived from hyperspectral field data in a coastal marsh from Buenos Aires Province, Argentina
dc.creator.none.fl_str_mv Gonzalez Trilla, Gabriela Liliana
Pratolongo, Paula Daniela
Kandus, Patricia
Beget, Maria Eugenia
Di Bella, Carlos Marcelo
Marcovecchio, Jorge Eduardo
author Gonzalez Trilla, Gabriela Liliana
author_facet Gonzalez Trilla, Gabriela Liliana
Pratolongo, Paula Daniela
Kandus, Patricia
Beget, Maria Eugenia
Di Bella, Carlos Marcelo
Marcovecchio, Jorge Eduardo
author_role author
author2 Pratolongo, Paula Daniela
Kandus, Patricia
Beget, Maria Eugenia
Di Bella, Carlos Marcelo
Marcovecchio, Jorge Eduardo
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Marisma
Teledetección
Biomasa
Marshes
Remote Sensing
Biomass
Leaf Area Index
Índice de Superficie Foliar
Buenos Aires
Spartina Densiflora
Cultivo en Pie
Spectral Indices
Standing Crop
topic Marisma
Teledetección
Biomasa
Marshes
Remote Sensing
Biomass
Leaf Area Index
Índice de Superficie Foliar
Buenos Aires
Spartina Densiflora
Cultivo en Pie
Spectral Indices
Standing Crop
dc.description.none.fl_txt_mv Remote sensing tools allow the environmental evaluation of coastal wetlands at a landscape scale, but a deeper understanding is needed of the interactions between biophysical parameters and the electromagnetic signal. The goal of this work was to analyze and quantify the influence of the aboveground biomass and the Leaf Area Index (LAI) on the spectral response of Spartina densiflora marshes in Mar Chiquita coastal lagoon, Argentina. Spectral reflectance at high resolution was measured in S. densiflora canopies under natural conditions, manipulating standing crop by means of successive harvest. Reflectance data were acquired using a spectroradiometer in visible, near infrared (IR) and shortwave IR bands. Spectral Vegetation Indices (VI) were calculated for each standing crop-LAI situation. Several VI significantly correlated with standing crop and LAI, including indices 1) based on the red-IR edge (IR Index (IRI), 695/760 ratio, Simple Ratio (SR), Red Edge Inflection Point (REIP), and different variations of the Normalized Difference VI (NDVI Rouse, NDVI amber, NDVI NOAA, NDVI Landsat, NDVI Modis), 2) indices based on the sharp change green-IR (green NDVI (GNDVI), 800/550 ratio) and 3) indices with a correction for soil noise (OSAVI: Optimized Soil Adjusted VI (OSAVI), and Modified SAVI (MSAVI). The indices with significant regressions with standing crop and LAI were IRI, NDVIAmber and REIP. The total and green standing crop showed better adjustments than LAI, showing R2 values of 0.5. These values were obtained with REIP index. Results indicate that LAI and standing crop of S. densiflora stands could be determined from spectral data but estimations should be taken carefully in high biomass scenarios, because of indexes saturation at higher LAI values.
Instituto de Clima y Agua
Fil: Gonzalez Trilla, Gabriela Liliana. Universidad Nacional de San Martín. Instituto de Investigación e Ingeniería Ambiental. Laboratorio de Ecología, Teledetección y Ecoinformática; Argentina
Fil: Pratolongo, Paula Daniela. 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
Fil: Kandus, Patricia. Universidad Nacional de San Martín. Instituto de Investigación e Ingeniería Ambiental. Laboratorio de Ecología, Teledetección y Ecoinformática; Argentina
Fil: Beget, Maria Eugenia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Di Bella, Carlos Marcelo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina
Fil: Marcovecchio, Jorge Eduardo. 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
description Remote sensing tools allow the environmental evaluation of coastal wetlands at a landscape scale, but a deeper understanding is needed of the interactions between biophysical parameters and the electromagnetic signal. The goal of this work was to analyze and quantify the influence of the aboveground biomass and the Leaf Area Index (LAI) on the spectral response of Spartina densiflora marshes in Mar Chiquita coastal lagoon, Argentina. Spectral reflectance at high resolution was measured in S. densiflora canopies under natural conditions, manipulating standing crop by means of successive harvest. Reflectance data were acquired using a spectroradiometer in visible, near infrared (IR) and shortwave IR bands. Spectral Vegetation Indices (VI) were calculated for each standing crop-LAI situation. Several VI significantly correlated with standing crop and LAI, including indices 1) based on the red-IR edge (IR Index (IRI), 695/760 ratio, Simple Ratio (SR), Red Edge Inflection Point (REIP), and different variations of the Normalized Difference VI (NDVI Rouse, NDVI amber, NDVI NOAA, NDVI Landsat, NDVI Modis), 2) indices based on the sharp change green-IR (green NDVI (GNDVI), 800/550 ratio) and 3) indices with a correction for soil noise (OSAVI: Optimized Soil Adjusted VI (OSAVI), and Modified SAVI (MSAVI). The indices with significant regressions with standing crop and LAI were IRI, NDVIAmber and REIP. The total and green standing crop showed better adjustments than LAI, showing R2 values of 0.5. These values were obtained with REIP index. Results indicate that LAI and standing crop of S. densiflora stands could be determined from spectral data but estimations should be taken carefully in high biomass scenarios, because of indexes saturation at higher LAI values.
publishDate 2016
dc.date.none.fl_str_mv 2016-02
2018-10-16T12:51:21Z
2018-10-16T12:51:21Z
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/20.500.12123/3597
https://link.springer.com/article/10.1007%2Fs13157-015-0715-6#citeas
0277-5212
1943-6246 (Online)
https://doi.org/10.1007/s13157-015-0715-6
url http://hdl.handle.net/20.500.12123/3597
https://link.springer.com/article/10.1007%2Fs13157-015-0715-6#citeas
https://doi.org/10.1007/s13157-015-0715-6
identifier_str_mv 0277-5212
1943-6246 (Online)
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
eu_rights_str_mv restrictedAccess
dc.format.none.fl_str_mv application/pdf
dc.coverage.none.fl_str_mv Buenos Aires (province)
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv Wetlands 36 (1) : 185–194. (February 2016)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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score 12.623145

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